Social engineering / phishing | Latest Threats | Microsoft Security Blog http://approjects.co.za/?big=en-us/security/blog/threat-intelligence/social-engineering-phishing/ Expert coverage of cybersecurity topics Thu, 13 Mar 2025 20:27:30 +0000 en-US hourly 1 https://wordpress.org/?v=6.7.2 Phishing campaign impersonates Booking .com, delivers a suite of credential-stealing malware http://approjects.co.za/?big=en-us/security/blog/2025/03/13/phishing-campaign-impersonates-booking-com-delivers-a-suite-of-credential-stealing-malware/ Thu, 13 Mar 2025 15:00:00 +0000 Starting in December 2024, leading up to some of the busiest travel days, Microsoft Threat Intelligence identified a phishing campaign that impersonates online travel agency Booking.com and targets organizations in the hospitality industry. The campaign uses a social engineering technique called ClickFix to deliver multiple credential-stealing malware in order to conduct financial fraud and theft. […]

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Starting in December 2024, leading up to some of the busiest travel days, Microsoft Threat Intelligence identified a phishing campaign that impersonates online travel agency Booking.com and targets organizations in the hospitality industry. The campaign uses a social engineering technique called ClickFix to deliver multiple credential-stealing malware in order to conduct financial fraud and theft. As of February 2025, this campaign is ongoing.

This phishing attack specifically targets individuals in hospitality organizations in North America, Oceania, South and Southeast Asia, and Northern, Southern, Eastern, and Western Europe, that are most likely to work with Booking.com, sending fake emails purporting to be coming from the agency.

In the ClickFix technique, a threat actor attempts to take advantage of human problem-solving tendencies by displaying fake error messages or prompts that instruct target users to fix issues by copying, pasting, and launching commands that eventually result in the download of malware. This need for user interaction could allow an attack to slip through conventional and automated security features. In the case of this phishing campaign, the user is prompted to use a keyboard shortcut to open a Windows Run window, then paste and launch a command that the phishing page adds to the clipboard.

Microsoft tracks this campaign as Storm-1865, a cluster of activity related to phishing campaigns leading to payment data theft and fraudulent charges. Organizations can reduce the impact of phishing attacks by educating users on recognizing such scams. This blog includes additional recommendations to help users and defenders defend against these threats.

Phishing campaign using the ClickFix social engineering technique

In this campaign, Storm-1865 identifies target organizations in the hospitality sector and targets individuals at those organizations likely to work with Booking.com. Storm-1865 then sends a malicious email impersonating Booking.com to the targeted individual. The content of the email varies greatly, referencing negative guest reviews, requests from prospective guests, online promotion opportunities, account verification, and more.

A screenshot of a email
Figure 1. A sample phishing email, purporting to be from a prospective guest.
A screenshot of a contact us
Figure 2. Another sample phishing email, purportedly requiring the recipient to address negative feedback about a hotel.
A screenshot of a security alert
Figure 3. Another sample phishing email, purportedly requiring the recipient to verify their Booking.com account.

The email includes a link, or a PDF attachment containing one, claiming to take recipients to Booking.com. Clicking the link leads to a webpage that displays a fake CAPTCHA overlayed on a subtly visible background designed to mimic a legitimate Booking.com page. This webpage gives the illusion that Booking.com uses additional verification checks, which might give the targeted user a false sense of security and therefore increase their chances of getting compromised.

The fake CAPTCHA is where the webpage employs the ClickFix social engineering technique to download the malicious payload. This technique instructs the user to use a keyboard shortcut to open a Windows Run window, then paste and launch a command that the webpage adds to the clipboard:

A screenshot of a computer
Figure 4. A screenshot of the fake Booking.com webpage, with the fake CAPTCHA overlay outlining the ClickFix process.

The command downloads and launches malicious code through mshta.exe:

A black letter on a white background
Figure 5. An example of the mshta.exe command that the targeted user launches.

This campaign delivers multiple families of commodity malware, including XWorm, Lumma stealer, VenomRAT, AsyncRAT, Danabot, and NetSupport RAT. Depending on the specific payload, the specific code launched through mshta.exe varies. Some samples have downloaded PowerShell, JavaScript, and portable executable (PE) content.

All these payloads include capabilities to steal financial data and credentials for fraudulent use, which is a hallmark of Storm-1865 activity. In 2023, Storm-1865 targeted hotel guests using Booking.com with similar social engineering techniques and malware. In 2024, Storm-1865 targeted buyers using e-commerce platforms with phishing messages leading to fraudulent payment webpages. The addition of ClickFix to this threat actor’s tactics, techniques, and procedures (TTPs) shows how Storm-1865 is evolving its attack chains to try to slip through conventional security measures against phishing and malware.

A diagram of a computer program
Figure 6. Diagram illustrating the stages of the infection process in this campaign.

Attribution

The threat actor that Microsoft tracks as Storm-1865 encapsulates a cluster of activity conducting phishing campaigns, leading to payment data theft and fraudulent charges. These campaigns have been ongoing with increased volume since at least early 2023 and involve messages sent through vendor platforms, such as online travel agencies and e-commerce platforms, and email services, such as Gmail or iCloud Mail.

Recommendations

Users can follow the recommendations below to spot phishing activity. Organizations can reduce the impact of phishing attacks by educating users on recognizing these scams.

Check the sender’s email address to ensure it’s legitimate. Assess whether the sender is categorized as first-time, infrequent, or marked as “[External]” by your email provider. Hover over the address to ensure that the full address is legitimate. Keep in mind that legitimate organizations do not send unsolicited email messages or make unsolicited phone calls to request personal or financial information. Always navigate to those organizations directly to sign into your account.

Contact the service provider directly. If you receive a suspicious email or message, contact the service provider directly using official contact forms listed on the official website.

Be wary of urgent calls to action or threats. Remain cautious of email notifications that call to click, call, or open an attachment immediately. Phishing attacks and scams often create a false sense of urgency to trick targets into acting without first scrutinizing the message’s legitimacy.

Hover over links to observe the full URL. Sometimes, malicious links are embedded into an email to trick the recipient. Simply clicking the link could let a threat actor download malware onto your device. Before clicking a link, ensure the full URL is legitimate. For best practice, rather than following a link from an email, search for the company website directly in your browser and navigate from there.

Search for typos. Phishing emails often contain typos, including within the body of the email, indicating that the sender is not a legitimate, professional source, or within the email domain or URL, as mentioned previously. Companies rarely send out messages without proofreading content, so multiple spelling and grammar mistakes can signal a scam message. In addition, check for very subtle misspellings of legitimate domains, a technique known as typosquatting. For example, you might see micros0ft[.]com, where the second o has been replaced by 0, or rnicrosoft[.]com, where the m has been replaced by r and n.

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

  • Pilot and deploy phishing-resistant authentication methods for users.
  • Enforce multi-factor authentication (MFA) on all accounts, remove users excluded from MFA, and strictly require MFA from all devices in all locations at all times.
  • Configure Microsoft Defender for Office 365 to recheck links on click. Safe Links provides URL scanning and rewriting of inbound email messages in mail flow, and time-of-click verification of URLs and links in email messages, other Microsoft 365 applications such as Teams, and other locations such as SharePoint Online. Safe Links scanning occurs in addition to the regular anti-spam and anti-malware protection in inbound email messages in Microsoft Exchange Online Protection (EOP). Safe Links scanning can help protect your organization from malicious links used in phishing and other attacks.
  • Encourage users to use Microsoft Edge and other web browsers that support Microsoft Defender SmartScreen, which identifies and blocks malicious websites, including phishing sites, scam sites, and sites that host malware.
  • Turn on cloud-delivered protection in Microsoft Defender Antivirus or the equivalent for your antivirus product to cover rapidly evolving attack tools and techniques. Cloud-based machine learning protections block a majority of new and unknown variants.
  • Enable network protection to prevent applications or users from accessing malicious domains and other malicious content on the internet.
  • Enable investigation and remediation in full automated mode to allow Microsoft Defender for Endpoint to take immediate action on alerts to resolve breaches, significantly reducing alert volume.
  • Enable Zero-hour auto purge (ZAP) in Office 365 to quarantine sent mail in response to newly acquired threat intelligence and retroactively neutralize malicious phishing, spam, or malware messages that have already been delivered to mailboxes.

Microsoft Defender XDR customers can turn on attack surface reduction rules to prevent common attack techniques:

Detection details

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

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

Microsoft Defender Antivirus

Microsoft Defender Antivirus detects threat components as the following malware:

Microsoft Defender for Endpoint

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

  • Suspicious command in RunMRU registry
  • Suspicious PowerShell command line
  • Use of living-off-the-land binary to run malicious code
  • Possible theft of passwords and other sensitive web browser information
  • Suspicious DPAPI Activity
  • Suspicious mshta process launched
  • Suspicious phishing activity detected

Microsoft Defender for Office 365

Microsoft Defender for Office 365 detects malicious activity associated with this threat through the following alerts:

  • This URL has known registrant pattern for malicious activity.
  • This URL impersonates booking.com
  • This PDF has generic phishing traits.
  • This URL has generic phishing traits.

Microsoft Security Copilot

Security Copilot customers can use the standalone experience to create their own prompts or run the following pre-built promptbooks to automate incident response or investigation tasks related to this threat:

  • Incident investigation
  • Microsoft User analysis
  • Threat actor profile
  • Threat Intelligence 360 report based on MDTI article
  • Vulnerability impact assessment

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

Threat intelligence reports

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

Microsoft Defender Threat Intelligence

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 query to find related activity in their networks:

Network connections to known C2 infrastructure related to this activity

Look for network connections with known C2 infrastructure.

let c2Servers = dynamic(['92.255.57.155','147.45.44.131','176.113.115.170','31.177.110.99','185.7.214.54','176.113.115.225','87.121.221.124','185.149.146.164']);
DeviceNetworkEvents
| where RemoteIP has_any(c2Servers)
| project Timestamp, DeviceId, DeviceName, LocalIP, RemoteIP, 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.

Below are the queries using 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.

Hunt normalized Network Session events using the ASIM unifying parser _Im_NetworkSession for IOCs:

let lookback = 30d;
let ioc_ip_addr = dynamic(['92.255.57.155','147.45.44.131','176.113.115.170','31.177.110.99','185.7.214.54','176.113.115.225','87.121.221.124','185.149.146.164']); 
_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

Hunt normalized Web Session events using the ASIM unifying parser _Im_WebSession for IOCs:

let lookback = 30d;
let ioc_ip_addr = dynamic(['92.255.57.155','147.45.44.131','176.113.115.170','31.177.110.99','185.7.214.54','176.113.115.225','87.121.221.124','185.149.146.164']); 
_Im_WebSession(starttime=todatetime(ago(lookback)), endtime=now())
| where DstIpAddr has_any (ioc_ip_addr)
 | summarize imWS_mintime=min(TimeGenerated), imWS_maxtime=max(TimeGenerated), EventCount=count() by SrcIpAddr, DstIpAddr, Url, Dvc, EventProduct, EventVendor

Hunt normalized File events using the ASIM unifying parser imFileEvent for IOCs:

let ioc_sha_hashes =dynamic(["01ec22c3394eb1661255d2cc646db70a66934c979c2c2d03df10127595dc76a6"," f87600e4df299d51337d0751bcf9f07966282be0a43bfa3fd237bf50471a981e ","0c96efbde64693bde72f18e1f87d2e2572a334e222584a1948df82e7dcfe241d"]);  imFileEvent
  | where SrcFileSHA256 in (ioc_sha_hashes) or TargetFileSHA256 in (ioc_sha_hashes)
  | extend AccountName = tostring(split(User, @'\')[1]), AccountNTDomain = tostring(split(User, @'\')[0])
  | extend AlgorithmType = "SHA256"

Indicators of compromise

IndicatorTypeDescription
92.255.57[.]155IP addressC2 server delivering XWorm
147.45.44[.]131IP addressC2 server delivering Danabot
176.113.115[.]170IP addressC2 server delivering LummaStealer
31.177.110[.]99IP addressC2 server delivering Danabot
185.7.214[.]54IP addressC2 server delivering XWorm
176.113.115[.]225IP addressC2 server delivering LummaStealer
87.121.221[.]124IP addressC2 server delivering Danabot
185.149.146[.]164IP addressC2 server delivering AsyncRAT
01ec22c3394eb1661255d2cc646db70a66934c979c2c2d03df10127595dc76a6  File hash (SHA-256)Danabot malware
f87600e4df299d51337d0751bcf9f07966282be0a43bfa3fd237bf50471a981eFile hash (SHA-256)Danabot malware
0c96efbde64693bde72f18e1f87d2e2572a334e222584a1948df82e7dcfe241d  File hash (SHA-256)Danabot malware

References

Learn more

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

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

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

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Malvertising campaign leads to info stealers hosted on GitHub http://approjects.co.za/?big=en-us/security/blog/2025/03/06/malvertising-campaign-leads-to-info-stealers-hosted-on-github/ Thu, 06 Mar 2025 17:00:00 +0000 Microsoft detected a large-scale malvertising campaign in early December 2024 that impacted nearly one million devices globally. The attack originated from illegal streaming websites embedded with malvertising redirectors and ultimately redirected users to GitHub to deliver initial access payloads as the start of a modular and multi-stage attack chain.

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In early December 2024, Microsoft Threat Intelligence detected a large-scale malvertising campaign that impacted nearly one million devices globally in an opportunistic attack to steal information. The attack originated from illegal streaming websites embedded with malvertising redirectors, leading to an intermediary website where the user was then redirected to GitHub and two other platforms. The campaign impacted a wide range of organizations and industries, including both consumer and enterprise devices, highlighting the indiscriminate nature of the attack.

Learn more about this malvertising campaign's multi-stage attack chain

Listen to the Microsoft Threat Intelligence podcast

GitHub was the primary platform used in the delivery of the initial access payloads and is referenced throughout this blog post; however, Microsoft Threat Intelligence also observed one payload hosted on Discord and another hosted on Dropbox.

The GitHub repositories, which were taken down, stored malware used to deploy additional malicious files and scripts. Once the initial malware from GitHub gained a foothold on the device, the additional files deployed had a modular and multi-stage approach to payload delivery, execution, and persistence. The files were used to collect system information and to set up further malware and scripts to exfiltrate documents and data from the compromised host. This activity is tracked under the umbrella name Storm-0408 that we use to track numerous threat actors associated with remote access or information-stealing malware and who use phishing, search engine optimization (SEO), or malvertising campaigns to distribute malicious payloads.

In this blog, we provide our analysis of this large-scale malvertising campaign, detailing our findings regarding the redirection chain and various payloads used across the multi-stage attack chain. We further provide recommendations for mitigating the impact of this threat, detection details, indicators of compromise (IOCs), and hunting guidance to locate related activity. By sharing this research, we aim to raise awareness about the tactics, techniques, and procedures (TTPs) used in this widespread activity so organizations can better prepare and implement effective mitigation strategies to protect their systems and data.

We would like to thank the GitHub security team for their prompt response and collaboration in taking down the malicious repositories.

GitHub activity and redirection chain

Since at least early December 2024, multiple hosts downloaded first-stage payloads from malicious GitHub repositories. The users were redirected to GitHub through a series of other redirections. Analysis of the redirector chain determined the attack likely originated from illegal streaming websites where users can watch pirated videos. The streaming websites embedded malvertising redirectors within movie frames to generate pay-per-view or pay-per-click revenue from malvertising platforms. These redirectors subsequently routed traffic through one or two additional malicious redirectors, ultimately leading to another website, such as a malware or tech support scam website, which then redirected to GitHub.

Multiple stages of malware were deployed in this campaign, as listed below, and the several different stages of activity that occurred depended on the payload dropped during the second stage.

  • The first-stage payload that was hosted on GitHub served as the dropper for the next stage of payloads.
  • The second-stage files were used to conduct system discovery and to exfiltrate system information that was Base64-encoded into the URL and sent over HTTP to an IP address. The information collected included data on memory size, graphic details, screen resolution, operating system (OS), and user paths.
  • Various third-stage payloads were deployed depending on the second-stage payload. In general, the third-stage payload conducted additional malicious activities such as command and control (C2) to download additional files and to exfiltrate data, as well as defense evasion techniques.

The full redirect chain was composed of four to five layers. Microsoft researchers determined malvertising redirectors were contained within an iframe on illegal streaming websites.

A screenshot of code from a streaming video website and iframe showing the malvertising redirector URL
Figure 1. Code from website of streaming video and iframe showing malvertising redirector URL

There were several redirections that occurred before arriving at the malicious content stored on GitHub.

A diagram of the redirection chain first depicting the illegal streaming website with iframe followed by the malicious redirector and counter, which redirects to the malvertising distributor, which finally lands on the malicious content hosted on GitHub.
Figure 2. Redirection chain from pirate streaming website to malware files on GitHub

Attack chain

Once the redirection to GitHub occurred, the malware hosted on GitHub established the initial foothold on the user’s device and functioned as a dropper for additional payload stages and running malicious code. The additional payloads included information stealers to collect system and browser information on the compromised device, of which most were either Lumma stealer or an updated version of Doenerium. Depending on the initial payload, the deployment of NetSupport, a remote monitoring and management (RMM) software, was also often deployed alongside the infostealer. Besides the information stealers, PowerShell, JavaScript, VBScript, and AutoIT scripts were run on the host. The threat actors incorporated use of living-off-the-land binaries and scripts (LOLBAS) like PowerShell.exe, MSBuild.exe, and RegAsm.exe for C2 and data exfiltration of user data and browser credentials.

After the initial foothold was gained, the activity led to a modular and multi-stage approach to payload delivery, execution, and persistence. Each stage dropped another payload with a different function, as outlined below. Actions conducted across these stages include system discovery (memory, GPU, OS, signed-in users, and others), opening browser credential files, Data Protection API (DPAPI) crypt data calls, and other functions such as obfuscated script execution and named pipe creations to conduct data exfiltration. Persistence was achieved through modification of the registry run keys and the addition of a shortcut file to the Windows Startup folder.

Several stages of malicious activity to conduct deployment of additional malware, collections, and exfiltration of data to a C2 were observed. While not every single initial payload followed these exact steps, this is an overall view of what occurred across most incidents analyzed:

A diagram generally displaying the four stages. The first stage involves the malvertising website redirecting users to GitHub pages, leading to a payload downloading from the repo. In the second stage, the payload performs system discovery and exfiltrates collected system information and stage-two payloads drop additional payloads. In the third stage, if the payload is a PowerShell script, it downloads NetSupport RAT from C2, sets persistence, and it may deliver a Lumma Stealer payload using MSBuild.exe for exfiltration. If the third stage payload is an .exe, it creates and runs a .cmd file and drops renamed AutoIT interpreter with a .com file extension, leading to the fourth stage. In the final stage, AutoIT launches binary and may drop an AutoIT interpreter with .scr file extensions, where a JavaScript file is dropped for running and persistence of those files. Finally, the AutoIT payload uses RegAsm.exe or PowerShell.exe to open files, enable browser remote debugging, and exfiltrate data. PowerShell may be deployed to set exclusion paths for Defender and/or drop NetSupport.
Figure 3. General depiction of the four stages

First-stage payload: Establishing a foothold on the host

During the first stage, a payload is dropped onto the user’s device from the binary hosted on GitHub, establishing a foothold on that device. As of mid-January 2025, the first-stage payloads discovered were digitally signed with a newly created certificate. A total of twelve different certificates were identified, all of which have been revoked.

Most of these initial payloads dropped the following legitimate files to leverage their functionality. These files were either leveraged by the first-stage payload or by later-stage payloads, depending on the actions being conducted.

File nameFunction
app-64.7zThis is a compressed archive that stores the second-stage payload and additional dropped files.
app.asarThis is an archive file specific to Electron applications, which are directly installed programs.
d3dcompiler_47.dllThis file is often included in DirectX redistributables, which are commonly bundled with Microsoft installers for games and graphics applications.
elevate.exeThis file is used by various installers and scripts to run processes with elevated privileges, not specific to Microsoft.
ffmpeg.dllThis file is associated with FFmpeg, a popular multimedia framework used to handle video, audio, and other multimedia files and streams.
libEGL.dllThis file is part of the ANGLE project, which is often found in applications that use OpenGL Embedded Systems (ES), including some web browsers and games.
libEGLESv2.dllThis file is part of the ANGLE project, which is often found in applications that use OpenGL ES, including some web browsers and games.
LICENSES.chromium.htmlThis file could contain information about the system or browser.
nsis7z.dllThis file is associated with the plugins for the Nullsoft Scriptable Install System (NSIS), which is used to create installers for various software.
StdUtils.dllThis file is associated with the plugins for the NSIS.
System.dllThis file is part of the .NET Framework assembly, typically included in Microsoft installers for applications that rely on the .NET Framework.
vk_swiftshader.dllThis file is associated with SwiftShader, which is used in applications that need a CPU-based implementation of the Vulkan API.
vulkan-1.dllThis file is associated with applications that use the Vulkan Graphics API, such as games and graphics software.

Depending on the first-stage payload that was initially established on the compromised device, Microsoft observed different second-stage payloads and several different methods for delivering these payloads to the device.

Second-stage payload: System discovery, collection, and exfiltration

The main purpose of the second-stage payload is to conduct system discovery and collect that data for exfiltration to the C2. The system information collected includes data such as memory size, graphic card details, screen resolution, operating system, user paths, and a reference to the second-stage payload’s file name.

This was accomplished by querying the registry key HKEY_LOCAL_MACHINE\SOFTWARE\Microsoft\Windows NT\CurrentVersion\ProductName for the Windows OS version and running commands, such as the echo command, to gather the device’s name (%COMPUTERNAME%) and domain name (%USERDOMAIN%).

System data collected by the second-stage payload is Base64-encoded and exfiltrated as a query parameter to an IP address.

Screenshot of code depicting the typical format of the URL observed when exfiltrating information collected from the compromised device.
Figure 4. Typical format of the URL observed when exfiltrating information collected from the compromised device

Third-stage payload: PowerShell and .exe binary

Depending on the second-stage payload, either one or multiple executables are dropped onto the compromised device, and sometimes an accompanying encoded PowerShell script. These files initiate a chain of events that conduct command execution, payload delivery, defensive evasion, persistence, C2 communications, and data exfiltration. The analysis of the dropped executables is first discussed below, followed by review of the PowerShell scripts observed.

Third-stage .exe analysis

The second-stage payloads run the dropped third-stage executables using the command prompt (for example, cmd.exe  /d /s /c “”C:\Users\<user>\AppData\Local\Temp\ApproachAllan.exe””). The /c flag ensures that the command runs and exits quickly. When the third-stage .exe runs, it drops a command file (.cmd) and launches it using the command prompt (for example, “cmd.exe” /c copy Beauty Beauty.cmd && Beauty.cmd). The .cmd file performs several actions, such as running tasklist, to initiate the discovery of running programs. This is followed by the findstr to search for keywords associated with security software:

findstr keywordAssociated software
wrsaWebroot SecureAnywhere
opssvcQuick Heal
AvastUIAvast Antivirus
AVGUIAVG Antivirus
bdservicehostBitdefender Antivirus
nsWscSvcNorton Security
ekrnESET
SophosHealthSophos

The .cmd file also concatenates multiple files into one with a single character file name: “cmd /c copy /b ..\Verzeichnis + ..\Controlling + ..\Constitute + ..\Enjoyed + ..\Confusion + ..\Min +..\Statutory J”. This single character filename is used next.

Following this, the third-stage .exe produces an AutoIT v3 interpreter file that is renamed from the typical file name of AutoIt3.exe and uses a .com file extension. The .cmd file initiates the execution of the .com file against the single character binary (such as Briefly.com J). Note, most of the second-stage payloads follow this progression chain, and as mentioned a second-stage payload can also drop multiple executables, all following the same process. For example:

First stage

  • X-essentiApp.exe

Second stage

  • Ionixnignx.exe

Third stage

  • EverybodyViewing.exe
  • ReliefOrganizational.exe
  • InflationWinston.exe

Third-stage command files

  • Beauty.cmd
  • Possess.cmd
  • Villa.cmd

Fourth-stage AutoIT .com files

  • Alexandria.com
  • Kills.com
  • Briefly.com

We observed multiple .com files originating from different dropped executables, each performing distinct functions while occasionally overlapping in behavior. These files facilitate persistence, process injection, remote debugging, and data exfiltration through various mechanisms. One .com file, such as Alexandria.com, drops a .scr file (another renamed AutoIT interpreter), and a .js (JavaScript) file with the same name as the .scr file. The purpose of the JavaScript file is to ensure persistence by creating a .url internet shortcut that points to the JavaScript file and is placed in the Startup folder, ensuring that the .scr file executes when the .js file executes (through Wscript.exe) upon user sign-in. Alternatively, persistence can be achieved using scheduled task creation. The .scr file can initiate C2 connections, enable remote debugging on Chrome or Edge within a hidden desktop session, or create TCP listening sockets on ports 9220-9229. This functionality allows threat actors to monitor browsing activity and interact with an active browser instance. These files can also open sensitive data files, indicating their role in facilitating post-exploitation activities.

Another .com file, such as affiliated.com, also focuses on remote debugging and browser monitoring. In addition to remote monitoring, affiliated.com initiates network connections to Telegram, Let’s Encrypt, and threat actor domains, potentially for C2 or exfiltration. It also accesses DPAPI to decrypt sensitive stored credentials and retrieve browser data.

The final observed .com file, such as Briefly.com, exhibits behavior similar to affiliated.com but extends its capabilities to include screenshot capture, data exfiltration, and PowerShell-based execution. This file accesses browser and user data for collection, establishes connections to Pastebin and additional C2 domains, and drops the fourth-stage PowerShell script.

The order in which these .com files run is not strictly defined, as one or multiple files can perform overlapping functions depending on the third-stage payload. In many cases, the .com files also leverage LOLBAS like RegAsm.exe by dropping a legitimate file into the %TEMP% directory or injecting malicious code into it using NtAllocateVirtualMemory and SetThreadContext API function calls. RegAsm.exe is used to establish C2 connections over TCP ports 15647 or 9000, exfiltrating data, accessing DPAPI for decryption, monitoring keystrokes using the WH_KEYBOARD_LL hook, and more. This flexibility in execution allows threat actors to tailor their approach based on environmental factors, such as security configurations and user activity.

Browser data files seen accessed:

  • \AppData\Roaming\Mozilla\Firefox\Profiles\<user profile uid>.default-release\cookies.sqlite
  • \AppData\Roaming\Mozilla\Firefox\Profiles\<user profile uid>.default-release\formhistory.sqlite
  • \AppData\Roaming\Mozilla\Firefox\Profiles\<user profile uid>.default-release\key4.db
  • \AppData\Roaming\Mozilla\Firefox\Profiles\<user profile uid>.default-release\logins.json
  • \AppData\Local\Google\Chrome\User Data\Default\Web Data
  • \AppData\Local\Google\Chrome\User Data\Default\Login Data
  • \AppData\Local\Microsoft\Edge\User Data\Default\Login Data

User data file paths seen accessed:

  • C:\\Users\<user>\\OneDrive
  • C:\\Users\<user>\\Documents
  • C:\\Users\<user>\\Downloads

Third-stage PowerShell analysis

If a PowerShell script is also dropped by the second-stage payload, it includes Base64-obfuscated commands to conduct actions, such as use curl to download additional files like NetSupport from the C2, create persistence for the NetSupport RAT, and exfiltrate system information to C2 servers. To ensure no errors or the progress meter is displayed on the compromised device, the curl command is often used with the –silent option when downloading files from the C2. PowerShell is often configured to run without restrictions with the -ExecutionPolicy Bypass parameter.

As an example, in some of the incidents, when the second-stage payload runs, a PowerShell script is dropped and executed. The script sends the compromised device’s name to the C2 and downloads NetSupport RAT from the same C2.

  • Second-stage payload: Squarel.exe
  • PowerShell script: SHA-256: d70ccae7914fc8c36c9e11b2a7f10bebd7f5696e78d8836554f4990b0f688dbb
  • C2 domain: keikochio[.]com
  • NetSupport RAT: SHA-256: 32a828e2060e92b799829a12e3e87730e9a88ecfa65a4fc4700bdcc57a52d995

In another case, a second-stage payload drops a PowerShell script, which connects to hxxps://ipinfo[.]io to gather the compromised device’s external-facing IP address. This information is sent to a Telegram chat, then drops presentationhost.exe (a renamed NetSupport binary) and remcmdstub.exe (NetSupport Command Manager) into the %TEMP% directory. Finally, the PowerShell script establishes persistence for presentationhost.exe by adding it to the auto-start extensibility points (ASEP) registry keys. When it runs, the NetSupport RAT connects to the C2 and captures a screenshot of the compromised device’s desktop. It also delivers a Lumma executable that drops a VBScript file with the same name. The VBScript file runs encoded PowerShell to initiate C2 connections and launches MSBuild.exe to enable Chrome remote debugging on a hidden desktop. Additionally, presentationhost.exe initiates remcmdstub.exe, which leverages iScrPaint.exe (iTop Screen Recorder) to run MSBuild.exe and access browser credential files for exfiltration. The iScrPaint.exe file also establishes persistence by placing a .lnk shortcut in the Windows Startup folder, ensuring it runs on system reboot.

  • Second-stage payload: Application.exe
  • PowerShell script: SHA-256: 483796a64f004a684a7bc20c1ddd5c671b41a808bc77634112e1703052666a64
  • C2: hxxp://5.10.250[.]240/fakeurl.htm

The last observed third-stage PowerShell script was dropped by three second-stage payloads. The script sends the compromised device’s name to the C2 server. It then changes the working directory to $env:APPDATA, before using Start-BitsTransfer to download NetSupport from the C2. To evade detection, it modifies system security settings forcing TLS1.2 for encrypted C2 communication. These files are extracted into a newly created WinLibraryClient directory under AppData and then are launched. The script establishes persistence for the client32.exe (NetSupport RAT) by modifying the ASEP registry. Client32.exe initiates C2 connections to hxxp://79.132.128[.]77/fakeurl.htm.

  • Second-stage payloads: SalmonSamurai.exe, LakerBaker.exe, and DisplayPhotoViewer.exe
  • PowerShell script: SHA-256: 670218cfc5c16d06762b6bc74cda4902087d812e72c52d6b9077c4c4164856b6
  • C2 domain: stocktemplates[.]net

Additionally, one observed execution included registry enumeration of HKCU:\Software\Microsoft\Windows\CurrentVersion\Uninstall\ to identify installed applications and security software. It also queries the system’s domain status using Windows Management Instrumentation (WMI) and scans for cryptocurrency wallets, including Ledger Live, Trezor Suite, KeepKey, BCVault, OneKey, and BitBox, indicating potential financial data theft.

Fourth-stage PowerShell analysis

Depending on the .com file that ran (like Briefly.com), the renamed AutoIT file may drop a PowerShell script (SHA-256: 2a29c9904d1860ea3177da7553c8b1bf1944566e5bc1e71340d9e0ff079f0bd3). The obfuscated PowerShell code uses the Add-MpPreference cmdlet to modify Microsoft Defender to add in exclusion paths for Microsoft Defender, so the specified folders are not scanned.

Screenshot of code depicting the deobfuscated commands to add exclusion paths to Windows Defender.
Figure 5. Deobfuscated commands to add exclusion paths to Windows Defender

The script above is sometimes followed by an instance of Base64-encoded PowerShell commands. The PowerShell commands perform the following actions:

  • Sends a web request to hxxps://360[.]net and closes the response.
  • Sends a web request to hxxps://baidu[.]com and closes the response.
  • Downloads data from hxxps://klipcatepiu0[.]shop/int_clp_sha.txt using a web client.
  • Writes the downloaded data to a memory stream and saves it as a .zip file named null.zip (SHA-256: f07b8e5622598c228bfc9bff50838a3c4fffd88c436a7ef77e6214a40b0a2bae) in the C:\Users\<Username>\AppData\Local\Temp directory.

Recommendations

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

Strengthen Microsoft Defender for Endpoint configuration

  • Ensure that tamper protection is enabled in Microsoft Defender for Endpoint. 
  • Enable network protection in Microsoft Defender for Endpoint. 
  • Turn on web protection.
  • Run endpoint detection and response (EDR) in block mode so that Microsoft Defender for Endpoint can block malicious artifacts, even when your non-Microsoft antivirus does not detect the threat or when Microsoft Defender Antivirus is running in passive mode. EDR in block mode works behind the scenes to remediate malicious artifacts that are detected post-breach.     
  • Configure investigation and remediation in full automated mode to let Microsoft Defender for Endpoint take immediate action on alerts to resolve breaches, significantly reducing alert volume.  
  • Microsoft Defender XDR customers can turn on the following attack surface reduction rules to prevent common attack techniques used by threat actors. 
    • Block executable files from running unless they meet a prevalence, age, or trusted list criterion 
    • Block execution of potentially obfuscated scripts
    • Block JavaScript or VBScript from launching downloaded executable content
    • Block process creations originating from PSExec and WMI commands
    • Block credential stealing from the Windows local security authority subsystem 
    • Block use of copied or impersonated system tools

Strengthen operating environment configuration

  • Require multifactor authentication (MFA). While certain attacks such as adversary-in-the-middle (AiTM) phishing attempt to circumvent MFA, implementation of MFA remains an essential pillar in identity security and is highly effective at stopping a variety of threats.
  • Implement Entra ID Conditional Access authentication strength to require phishing-resistant authentication for employees and external users for critical apps.
  • Encourage users to use Microsoft Edge and other web browsers that support Microsoft Defender SmartScreen, which identifies and blocks malicious websites, including phishing sites, scam sites, and sites that host malware.
  • Enable Network Level Authentication for Remote Desktop Service connections.
  • Enable Local Security Authority (LSA) protection to block credential stealing from the Windows local security authority subsystem. 
  • AppLocker can restrict specific software tools prohibited within the organization, such as reconnaissance, fingerprinting, and RMM tools, or grant access to only specific users.

Microsoft Defender XDR detections

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

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

Microsoft Defender Antivirus

Microsoft Defender Antivirus detects threat components as the following malware:

Microsoft Defender for Endpoint

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

  • Possible theft of passwords and other sensitive web browser information
  • Possible Lumma Stealer activity
  • Renamed AutoIt tool
  • Use of living-off-the-land binary to run malicious code
  • Suspicious startup item creation
  • Suspicious Scheduled Task Process Launched
  • Suspicious DPAPI Activity
  • Suspicious implant process from a known emerging threat
  • Security software tampering
  • Suspicious activity linked to a financially motivated threat actor detected
  • Ransomware-linked threat actor detected
  • A file or network connection related to a ransomware-linked emerging threat activity group detected
  • Information stealing malware activity
  • Possible NetSupport Manager activity
  • Suspicious sequence of exploration activities
  • Defender detection bypass
  • Suspicious Location of Remote Management Software
  • A process was injected with potentially malicious code
  • Process hollowing detected
  • Suspicious PowerShell download or encoded command execution
  • Suspicious PowerShell command line
  • Suspicious behavior by cmd.exe was observed
  • Suspicious Security Software Discovery
  • Suspicious discovery indicative of Virtualization/Sandbox Evasion
  • A process was launched on a hidden desktop
  • Monitored keystrokes
  • Suspicious Process Discovery
  • Suspicious Javascript process
  • A suspicious file was observed
  • Anomaly detected in ASEP registry

Microsoft Defender for Cloud

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

  • Detected suspicious combination of HTA and PowerShell
  • Suspicious PowerShell Activity Detected
  • Traffic detected from IP addresses recommended for blocking
  • Attempted communication with suspicious sinkholed domain
  • Communication with suspicious domain identified by threat intelligence
  • Detected obfuscated command line
  • Detected suspicious named pipe communications

Microsoft Security Copilot

Security Copilot customers can use the standalone experience to create their own prompts or run the following pre-built promptbooks to automate incident response or investigation tasks related to this threat:

  • Incident investigation
  • Microsoft User analysis
  • Threat actor profile
  • Threat Intelligence 360 report based on MDTI article
  • Vulnerability impact assessment

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

Threat intelligence reports

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

Microsoft Defender Threat Intelligence

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 query to find related activity in their networks:

Github-hosted first-stage payload certificate serial numbers

let specificSerialNumbers = dynamic(["70093af339876742820d7941", "15042512e67e8275f3f7f36b", "5608cab7e2ce34d53abcbb73",
 "0fa27d2553f24da79d1cc6bd8773ee9a", "7a7bf2ae0cbc0f5500db2946", "30d6c83a715bddb32e7956fe52d6b352",
  "301385aa36fae635e74bb88e", "30013cbbb16a7fd3c57f82707fb99c32", "5d00264a6b804ae6b28d9b16",
   "3a9c76f8304f77bd271921d9982f1ab6", "01f2c6c363767056abd80e9c", "0b09c88c0c8d15bed51a9eb4440f4bb0"]); 
union
(
    DeviceFileCertificateInfo
    | where CertificateSerialNumber in (specificSerialNumbers)
    | project DeviceName, CertificateSerialNumber, Signer, SHA1, IsSigned, Issuer, Timestamp
),
(
    DeviceTvmCertificateInfo
    | where SerialNumber in (specificSerialNumbers)
    | project DeviceId, SerialNumber, SignatureAlgorithm, Thumbprint, Path, IssueDate, ExpirationDate
)

Dropbox-hosted first-stage payload certificate serial number

Surface devices that may contain first-stage payloads hosted on Dropbox related to this activity. This query will search for the unique serial number of the known certificate related to this activity.

let specificSerialNumbers = dynamic(["7a7bf2ae0cbc0f5500db2946"]); 
union
(
    DeviceFileCertificateInfo
    | where CertificateSerialNumber in (specificSerialNumbers)
    | project DeviceName, CertificateSerialNumber, Signer, SHA1, IsSigned, Issuer, Timestamp
),
(
    DeviceTvmCertificateInfo
    | where SerialNumber in (specificSerialNumbers)
    | project DeviceId, SerialNumber, SignatureAlgorithm, Thumbprint, Path, IssueDate, ExpirationDate
)

Second-stage C2 IP addresses

Surface devices that may have communicated with second stage C2 IP addresses related to this activity.

let ipAddressToSearch = dynamic(["159.100.18.192", "192.142.10.246", "79.133.46.35", "84.200.24.191", "84.200.24.26", "89.187.28.253", "185.92.181.1"]);
union isfuzzy=true
(
    AzureDiagnostics
    | where identity_claim_ipaddr_s == ipAddressToSearch or conditions_sourceIP_s == ipAddressToSearch or CallerIPAddress == ipAddressToSearch or clientIP_s == ipAddressToSearch or clientIp_s == ipAddressToSearch or primaryIPv4Address_s == ipAddressToSearch or conditions_destinationIP_s == ipAddressToSearch
    | project Timestamp = TimeGenerated, Table = "AzureDiagnostics", IPAddress = coalesce(identity_claim_ipaddr_s, conditions_sourceIP_s, CallerIPAddress, clientIP_s, clientIp_s, primaryIPv4Address_s, conditions_destinationIP_s), AdditionalInfo = tostring(AdditionalFields)
),
(
    IdentityQueryEvents
    | where IPAddress == ipAddressToSearch or DestinationIPAddress == ipAddressToSearch
    | project Timestamp, Table = "IdentityQueryEvents", IPAddress = coalesce(IPAddress, DestinationIPAddress), AdditionalInfo = Query
),
(
    AADSignInEventsBeta
    | where IPAddress == ipAddressToSearch
    | project Timestamp, Table = "AADSignInEventsBeta", IPAddress, AdditionalInfo = UserAgent
),
(
    Heartbeat
    | where ComputerIP == ipAddressToSearch
    | project Timestamp = TimeGenerated, Table = "Heartbeat", IPAddress = ComputerIP, AdditionalInfo = OSName
),
(
    CloudAppEvents
    | where IPAddress == ipAddressToSearch
    | project Timestamp, Table = "CloudAppEvents", IPAddress, AdditionalInfo = UserAgent
),
(
    DeviceNetworkEvents
    | where LocalIP == ipAddressToSearch or RemoteIP == ipAddressToSearch
    | project Timestamp, Table = "DeviceNetworkEvents", IPAddress = coalesce(LocalIP, RemoteIP), AdditionalInfo = InitiatingProcessCommandLine
),
(
    AADUserRiskEvents
    | where IpAddress == ipAddressToSearch
    | project Timestamp = TimeGenerated, Table = "AADUserRiskEvents", IPAddress = IpAddress, AdditionalInfo = RiskEventType
),
(
    AADNonInteractiveUserSignInLogs
    | where IPAddress == ipAddressToSearch
    | project Timestamp = TimeGenerated, Table = "AADNonInteractiveUserSignInLogs", IPAddress, AdditionalInfo = UserAgent
),
(
    MicrosoftAzureBastionAuditLogs
    | where TargetVMIPAddress == ipAddressToSearch or ClientIpAddress == ipAddressToSearch
    | project Timestamp = TimeGenerated, Table = "MicrosoftAzureBastionAuditLogs", IPAddress = coalesce(TargetVMIPAddress, ClientIpAddress), AdditionalInfo = UserAgent
)
| sort by Timestamp desc

Fourth-stage C2 IP addresses

Surface devices that may have communicated with fourth stage C2 IP addresses related to this activity.

let ipAddressToSearch = dynamic(["45.141.84.60", "91.202.233.18", "154.216.20.131", "5.10.250.240", "79.132.128.77"]);
union isfuzzy=true
(
    AzureDiagnostics
    | where identity_claim_ipaddr_s == ipAddressToSearch or conditions_sourceIP_s == ipAddressToSearch or CallerIPAddress == ipAddressToSearch or clientIP_s == ipAddressToSearch or clientIp_s == ipAddressToSearch or primaryIPv4Address_s == ipAddressToSearch or conditions_destinationIP_s == ipAddressToSearch
    | project Timestamp = TimeGenerated, Table = "AzureDiagnostics", IPAddress = coalesce(identity_claim_ipaddr_s, conditions_sourceIP_s, CallerIPAddress, clientIP_s, clientIp_s, primaryIPv4Address_s, o),
(
    IdentityQueryEvents
    | where IPAddress == ipAddressToSearch or DestinationIPAddress == ipAddressToSearch
    | project Timestamp, Table = "IdentityQueryEvents", IPAddress = coalesce(IPAddress, DestinationIPAddress), AdditionalInfo = Query
),
(
    AADSignInEventsBeta
    | where IPAddress == ipAddressToSearch
    | project Timestamp, Table = "AADSignInEventsBeta", IPAddress, AdditionalInfo = UserAgent
),
(
    Heartbeat
    | where ComputerIP == ipAddressToSearch
    | project Timestamp = TimeGenerated, Table = "Heartbeat", IPAddress = ComputerIP, AdditionalInfo = OSName
),
(
    CloudAppEvents
    | where IPAddress == ipAddressToSearch
    | project Timestamp, Table = "CloudAppEvents", IPAddress, AdditionalInfo = UserAgent
),
(
    DeviceNetworkEvents
    | where LocalIP == ipAddressToSearch or RemoteIP == ipAddressToSearch
    | project Timestamp, Table = "DeviceNetworkEvents", IPAddress = coalesce(LocalIP, RemoteIP), AdditionalInfo = InitiatingProcessCommandLine
),
(
    AADUserRiskEvents
    | where IpAddress == ipAddressToSearch
    | project Timestamp = TimeGenerated, Table = "AADUserRiskEvents", IPAddress = IpAddress, AdditionalInfo = RiskEventType
),
(
    AADNonInteractiveUserSignInLogs
    | where IPAddress == ipAddressToSearch
    | project Timestamp = TimeGenerated, Table = "AADNonInteractiveUserSignInLogs", IPAddress, AdditionalInfo = UserAgent
),
(
    MicrosoftAzureBastionAuditLogs
    | where TargetVMIPAddress == ipAddressToSearch or ClientIpAddress == ipAddressToSearch
    | project Timestamp = TimeGenerated, Table = "MicrosoftAzureBastionAuditLogs", IPAddress = coalesce(TargetVMIPAddress, ClientIpAddress), AdditionalInfo = UserAgent
)
| sort by Timestamp desc

Browser remote debugging 

Identify AutoIT scripts launching chromium-based browsers (such as chrome.exe, msedge.exe, brave.exe) in remote debugging mode.

DeviceProcessEvents 
| where InitiatingProcessVersionInfoInternalFileName == "AutoIt3.exe" // Check for "AutoIt" scripts, even if it's renamed.  
| where ProcessCommandLine has "--remote-debugging-port" // Identify Chromium based browsers (chrome.exe, msedge.exe, brave.exe etc) being launched in remote debugging mode. 
| project DeviceId, Timestamp, InitiatingProcessParentFileName, InitiatingProcessFileName, InitiatingProcessFolderPath, InitiatingProcessVersionInfoInternalFileName, InitiatingProcessCommandLine, FileName, ProcessCommandLine

DPAPI decryption via AutoIT

Identify DPAPI decryption activity originating from AutoIT scripts.

DeviceEvents
| where ActionType == "DpapiAccessed"
| where InitiatingProcessVersionInfoInternalFileName == "AutoIt3.exe"
| where (AdditionalFields has_any("Google Chrome", "Microsoft Edge") and AdditionalFields has_any("SPCryptUnprotect"))
| extend json = parse_json(AdditionalFields)
| extend dataDesp = tostring(json.DataDescription.PropertyValue)
| extend opType = tostring(json.OperationType.PropertyValue)
| where (dataDesp in~ ("Google Chrome", "Microsoft Edge") and opType =~ "SPCryptUnprotect")
| project Timestamp, ReportId, DeviceId, ActionType, InitiatingProcessParentFileName, InitiatingProcessFileName, InitiatingProcessVersionInfoInternalFileName, InitiatingProcessCommandLine, AdditionalFields, dataDesp, opType

DPAPI decryption via LOLBAS binaries

Identify DPAPI decryption activity originating from LOLBAS binaries (RegAsm.exe and MSBuild.exe).

DeviceEvents
| where ActionType == "DpapiAccessed"
| where InitiatingProcessFileName has_any ("RegAsm.exe", "MSBuild.exe")
| where (AdditionalFields has_any("Google Chrome", "Microsoft Edge") and  AdditionalFields has_any("SPCryptUnprotect"))
| extend json = parse_json(AdditionalFields)
| extend dataDesp = tostring(json.DataDescription.PropertyValue)
| extend opType = tostring(json.OperationType.PropertyValue)
| where (dataDesp in~ ("Google Chrome", "Microsoft Edge") and opType =~ "SPCryptUnprotect")
| project Timestamp, ReportId, DeviceId, ActionType, InitiatingProcessParentFileName, InitiatingProcessFileName, InitiatingProcessVersionInfoInternalFileName, InitiatingProcessCommandLine, AdditionalFields, dataDesp, opType

Sensitive browser file access via AutoIT

Identify AutoIT scripts (renamed or otherwise) accessing sensitive browser files.

let browserDirs = pack_array(@"\Google\Chrome\User Data\", @"\Microsoft\Edge\User Data\", @"\Mozilla\Firefox\Profiles\"); 
let browserSensitiveFiles = pack_array("Web Data", "Login Data", "key4.db", "formhistory.sqlite", "cookies.sqlite", "logins.json", "places.sqlite", "cert9.db");
DeviceEvents
| where AdditionalFields has_any ("FileOpenSource") // Filter for "File Open" events.
| where InitiatingProcessVersionInfoInternalFileName == "AutoIt3.exe"
| where (AdditionalFields has_any(browserDirs) or  AdditionalFields has_any(browserSensitiveFiles)) 
| extend json = parse_json(AdditionalFields)
| extend File_Name = tostring(json.FileName.PropertyValue)
| where (File_Name has_any (browserDirs) and File_Name has_any (browserSensitiveFiles))
| project Timestamp, ReportId, DeviceId, InitiatingProcessParentFileName, InitiatingProcessFileName, InitiatingProcessVersionInfoInternalFileName, InitiatingProcessCommandLine, File_Name

Sensitive browser file access via LOLBAS binaries

Identify LOLBAS binaries (RegAsm.exe and MSBuild.exe) accessing sensitive browser files.

let browserDirs = pack_array(@"\Google\Chrome\User Data\", @"\Microsoft\Edge\User Data\", @"\Mozilla\Firefox\Profiles\"); 
let browserSensitiveFiles = pack_array("Web Data", "Login Data", "key4.db", "formhistory.sqlite", "cookies.sqlite", "logins.json", "places.sqlite", "cert9.db");
DeviceEvents
| where AdditionalFields has_any ("FileOpenSource") // Filter for "File Open" events.
| where InitiatingProcessFileName has_any ("RegAsm.exe", "MSBuild.exe")
 | where (AdditionalFields has_any(browserDirs) or  AdditionalFields has_any(browserSensitiveFiles)) 
| extend json = parse_json(AdditionalFields)
| extend File_Name = tostring(json.FileName.PropertyValue)
| where (File_Name has_any (browserDirs) and File_Name has_any (browserSensitiveFiles))
| project Timestamp, ReportId, DeviceId, InitiatingProcessParentFileName, InitiatingProcessFileName, InitiatingProcessVersionInfoInternalFileName, InitiatingProcessCommandLine, File_Name

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.

Indicators of compromise

Streaming website domains with malicious iframe

Indicator Type 
 movies7[.]net Domain
 0123movie[.]art Domain

Malicious iframe redirector domains

Indicator Type 
 fle-rvd0i9o8-moo[.]com Domain
 0cbcq8mu[.]com Domain

Malvertisement distributor

Indicator Type 
 widiaoexhe[.]top Domain

Malvertising website domains

Indicator Type 
widiaoexhe[.]top Domain
predictivdisplay[.]com Domain
buzzonclick[.]com Domain
pulseadnetwork[.]com Domain
onclickalgo[.]comDomain
liveadexchanger[.]comDomain
greatdexchange[.]comDomain
dexpredict[.]comDomain
onclickperformance[.]comDomain

GitHub referral URLs

Indicator Type 
hxxps://pmpdm[.]com/webcheck35/URL
hxxps://startherehosting[.]net/todaypage/URL
hxxps://kassalias[.]com/pageagain/URL
hxxps://sacpools[.]com/pratespage/URL
hxxps://dreamstorycards[.]com/amzpage/URL
hxxps://primetimeessentials[.]com/newpagyes/URL
hxxps://razorskigrips[.]com/perfect/URL
hxxps://lakeplacidluxuryhomes[.]com/webpage37URL
hxxps://ageless-skincare[.]com/gn/URL
hxxps://clarebrownmusic[.]com/goodday/URL
hxxps://razorskigrips[.]com/gn/URL
hxxps://compass-point-yachts[.]com/nicepage77/pro77.phpURL
hxxps://razorskigrips[.]com/goodk/URL
hxxps://lilharts[.]com/propage6/URL
hxxps://enricoborino[.]com/propage66/URL
hxxps://afterpm[.]com/pricedpage/URL
hxxps://eaholloway[.]com/updatepage333/URL
hxxps://physicaltherapytustin[.]com/webhtml/URL
hxxps://physicaltherapytustin[.]com/web-X/URL
hxxps://razorskigrips[.]com/newnewpage/URL
hxxps://statsace[.]com/web_us/URL
hxxps://nationpains[.]com/safeweb3/URL
hxxps://vjav[.]com/URL
hxxps://thegay[.]com/URL
hxxps://olopruy[.]com/URL
hxxps://desi-porn[.]tube/URL
hxxps://cumpaicizewoa[.]net/partitial/URL
hxxps://ak.ptailadsol[.]net/partitial/URL
hxxps://egrowz[.]com/webview/URL
hxxps://or-ipo[.]com/nice/URL

GitHub URLs

Indicator Type 
hxxps://github[.]com/down4up/ URL
hxxps://github[.]com/g1lsetup/iln77URL
hxxps://github[.]com/g1lsetup/v2025URL
hxxps://github[.]com/git2312now/DownNew152/URL
hxxps://github[.]com/muhammadshahblis/URL
hxxps://github[.]com/JimelecarURL
hxxps://github[.]com/kloserwURL
hxxps://github[.]com/kopersparan/URL
hxxps://github[.]com/zotokilowaURL
hxxps://github[.]com/colvfile/bmx84542URL
hxxps://github[.]com/colvfile/yesyes333URL
hxxps://github[.]com/mp3andmovies/URL
hxxps://github[.]com/anatfile/newlURL
hxxps://github[.]com/downloadprov/wwwURL
hxxps://github[.]com/abdfilesup/readyyesURL
hxxps://objects.githubusercontent[.]com/github-production-release-asset-2e65be/898537481URL
hxxps://objects.githubusercontent[.]com/github-production-release-asset-2e65be/898072392/ URL
hxxps://objects.githubusercontent[.]com/github-production-release-asset-2e65be/902107140URL
hxxps://objects.githubusercontent[.]com/github-production-release-asset-2e65be/902405338URL
hxxps://objects.githubusercontent[.]com/github-production-release-asset-2e65be/901430321/URL
hxxps://objects.githubusercontent[.]com/github-production-release-asset-2e65be/903047306/URL
hxxps://objects.githubusercontent[.]com/github-production-release-asset-2e65be/899121225URL
hxxps://objects.githubusercontent[.]com/github-production-release-asset-2e65be/899472962/URL
hxxps://objects.githubusercontent[.]com/github-production-release-asset-2e65be/900979287/URL
hxxps://objects.githubusercontent[.]com/github-production-release-asset-2e65be/901553970URL
hxxps://objects.githubusercontent[.]com/github-production-release-asset-2e65be/901617842/URL
hxxps://objects.githubusercontent[.]com/github-production-release-asset-2e65be/897657726URL
hxxps://objects.githubusercontent[.]com/github-production-release-asset-2e65be/903499100/URL
hxxps://objects.githubusercontent[.]com/github-production-release-asset-2e65be/903509708/URL
hxxps://objects.githubusercontent[.]com/github-production-release-asset-2e65be/915668132/URL

DropBox URL

Indicator Type
 hxxps://uc8ce1a0cf2efa109cd4540c0c22.dl.dropboxusercontent[.]com/cd/0/get/CgHUWBzFWtX1ZE6CwwKXVb1EvW4tnDYYhbX8Iqj70VZ5e2uwYlkAq6V-xQcjX0NMjbOJrN3_FjuanOjW66WdjPHNw2ptSNdXZi4Sey6511OjeNGuzMwxtagHQe5qFOFpY2xyt1sWeMfLwwHkvGGFzcKY/file?dl=1# URL

Discord URL

Indicator Type
hxxps://cdn.discordapp[.]com/attachments/1316109420995809283/1316112071376769165/NativeApp_G4QLIQRa.exe URL

First stage GitHub-hosted payloads

FilenameSHA-256
NanoPhanoTool.execd207b81505f13d46d94b08fb5130ddae52bd1748856e6b474688e590933a718
Squarel_JhZjXa.exeb87ff3da811a598c284997222e0b5a9b60b7f79206f8d795781db7b2abd41439
PriceApp_1jth1MMk.exeef2d8f433a896575442c13614157261b32dd4b2a1210aca3be601d301feb1fef
Paranoide.exe5550ea265b105b843f6b094979bfa0d04e1ee2d1607b2e0d210cd0dea8aab942
AliasApp.exe0c2d5b2a88a703df4392e060a7fb8f06085ca3e88b0552f7a6a9d9ef8afdda03
X-essentiApp.exed8ae7fbb8db3b027a832be6f1acc44c7f5aebfdcb306cd297f7c30f1594d9c45
QilawatProtone.exe823d37f852a655088bb4a81d2f3a8bfd18ea4f31e7117e5713aeb9e0443ccd99
ElectronApp.exe588071382ac2bbff6608c5e7f380c8f85cdd9e6df172c5edbdfdb42eb74367dc
NativeApp_dRRgoZqi.exedd8ce4a2fdf4af4d3fc4df88ac867efb49276acdcacaecb0c91e99110477dbf2
NativeApp_G5L1NHZZ.exe380920dfcdec5d7704ad1af1ce35feba7c3af1b68ffa4588b734647f28eeabb7
NativeApp_86hwwNjq.exe96cc7c9fc7ffbda89c920b2920327a62a09f8cb4fcf400bbfb02de82cdd8dba1
NativeApp_01C02RhQ.exe800c5cd5ec75d552f00d0aca42bdade317f12aa797103b9357d44962e8bcd37a
App_aeIGCY3g.exeafdc1a1e1e934f18be28465315704a12b2cd43c186fbee94f7464392849a5ad0
Pictore.exede6fcdf58b22a51d26eacb0e2c992d9a894c1894b3c8d70f4db80044dacb7430
ScenarioIT.exef677be06af71f81c93b173bdcb0488db637d91f0d614df644ebed94bf48e6541
CiscoProton.exe7b88f805ed46f4bfc3aa58ef94d980ff57f6c09b86c14afa750fc41d32b7ada8
Alarmer.exedc8e5cae55181833fa9f3dd0f9af37a2112620fd47b22e2fd9b4a1b05c68620f
AevellaAi.2.exe3e8ef8ab691f2d5b820aa7ac805044e5c945d8adcfc51ee79d875e169f925455
avs.exed2e9362ae88a795e6652d65b9ae89d8ff5bdebbfec8692b8358aa182bc8ce7a4
mrg.exe113290aaa5c0b0793d50de6819f2b2eead5e321e9300d91b9a36d62ba8e5bbc1
mrg.exe732b4874ac1a1d4326fc1d71d16910fce2835ceb87e76ad4ef2e40b1e948a6cc
Application.exeaea0892bf9a533d75256212b4f6eaede2c4c9e47f0725fc3c61730ccfba25ec8
Application.exeea2e21d0c09662a0f9b42d95ce706b5ed26634f20b9b5027ec681635a4072453
SalmonSamurai.exe83679dfd6331a0a0d829c0f3aed5112b69a7024ff1ceebf7179ba5c2b4d21fc5
Arendada.exe47ef2b7e8f35167fab1ecdd5ddb73d41e40e6a126f4da7540c1c0394195cb3df
Arduino.exe92d457b286fb63d2f5ec9413fd234643448c5f8d2c0763e43ed5cf27ab47eb02
SecondS.exe9d5c551f076449af0dbd7e05e1c2e439d6f6335b3dd07a8fa1b819c250327f39
ultraedit.msi0e20bea91c3b70259a7b6eef3bff614ce9b6df25e078bc470bfef9489c9c76e6

First-stage Dropbox-hosted payload

FilenameSHA-256
App_File-x38.3.exec0bc1227bdc56fa601c1c5c0527a100d7c251966e40b2a5fa89b39a2197dda67

First-stage Discord-hosted payload

FilenameSHA-256
NativeApp_G4QLIQRa.exe87200e8b43a6707cd66fc240d2c9e9da7f3ed03c8507adf7c1cfe56ba1a9c57d

Certificate signatures of GitHub-hosted payloads

Indicator 
c855f7541e50c98a5ae09f840fa06badb97ab46c
94c21e6384f2ffb72bd856c1c40b788f314b5298
74df2582af3780d81a8071e260c2b04259efc35a
07728484b1bb8702a87c6e5a154e0d690af2ff38
901f3fe4e599cd155132ce2b6bf3c5f6d1e0387c
be7156bd07dd7f72521fae4a3d6f46c48dd2ce9e
686b7ebba606303b5085633fcaa0685272b4d9b9
74a8215a54f52f792d351d66bd56a0ac626474fb
561620a3f0bf4fb96898a99252b85b00c468e5af
8137f599ac036b0eaae9486158e40e90ebdbce94
E9007755cfe5643d18618786de1995914098307f

Certificate signature of Dropbox-hosted payload

Indicator 
 fa6146f1fdad58b8db08411c459cb70acf82846d

Second-stage payloads

File nameSHA-256
NanoTool.exe9f958b85dc42ac6301fe1abfd4b11316b637c0b8c0bf627c9b141699dc18e885
Squarel.exe29539039c19995d788f24329ebb960eaf5d86b1f8df76272284d08a63a034d42
ParanoidResolver.exe1f73a00b5a7ac31ffc89abbedef17ee2281cf065423a3644787f6c622295ff29
AliasInstall.exe997671c13bb78a9acc658e2c3a1abf06aedc4f1f4f1e5fd8d469a912fc93993b
IoNixNginx.exe1d8ab53874b2edfb058dd64da8a61d92c8a8e302cc737155e0d718dbe169ba36
QilawatProton.exe 885f8a704f1b3aaa2c4ddf7eab779d87ecb1290853697a1e6fb6341c4f825968
ProtonEditor.exe48f422bf2b878d142f376713a543d113e9f964f6761d15d4149a4d71441739e5
AlEditor.exe 9daa63046978d7097ea20bfbb543d82374cf44ba37f966b87488f63daf20999e
Scielfic.exe6ec86b4e200144084e07407200a5294985054bdaddb3d6c56358fc0657e48157
Pictore.exe18959833da3df8d5d8d19c3fce496c55aa70140824d3a942fe43d547b9a8c065
AlarmWalker Solid.exe552f23590bdf301f481e62a9ce3c279bab887d64f4ba3ea3d81a348e3eff6c45
Aevella.exe 2a738f41b42f47b64be7dc2d16a4068472b860318537b5076814891a7d00b3bb
Application.exe5b50d0d67db361da72af2af20763b0dde9e5e86b792676acb9750f32221e955c
ArchiverApp.execfeac95017edbfe9a0ad8f24e7539f54482012d11dc79b7b6f41ff4ff742d9c6
LakerBaker.exeaf7454ca632dead16a36da583fb89f640f70df702163f5a22ba663e985f80d88
NanoTool.exeefdcd37ee0845e0145084c2a10432e61b1b4bf6b44ecd41d61a54b10e3563650
DisplayPhotoViewer.exe86ae0078776c0411504cf97f4369512013306fcf568cc1dc7a07e180dde08eda
CheryLady Application.exe773d3cb5edef063fb5084efcd8d9d7ac7624b271f94706d4598df058a89f77fd
SalmonSamurai.exe40abba1e7da7b3eaad08a6e3be381a9fc2ab01b59638912029bc9a4aa1e0c7a7
Heaveen Application.exe39dbf19d5c642d48632bfaf2f83518cfbd2b197018642ea1f2eb3d81897cf17d
Cisco Application.exe234971ecd1bf152c903841fac81bdaa288954a2757a73193174cde02fa6f937b
Simplify.exe221615de3d66e528494901fb5bd1725ecda336af33fe758426295f659141b931
SecondS.tmp5185f953be3d0842416d679582b233fdc886301441e920cb9d11642b3779d153

Second-stage C2s

Indicator Type 
159.100.18[.]192 C2
192.142.10[.]246 C2
79.133.46[.]35C2
84.200.24[.]191C2
84.200.24[.]26C2
89.187.28[.]253 C2
185.92.181[.]1C2
188.245.94[.]250 C2

Third-stage payloads: .exe and PowerShell files

File nameSHA-256
ApproachAllan.exe4e5fafffb633319060190a098b9ea156ec0243eb1279d78d27551e507d937947
DiscoConvicted.exe008aed5e3528e2c09605af26b3cda88419efb29b85ed122cab59913c18f7dc75
AwesomeTrader.exe21d4252a6492270f24282f8de9e985c9b8c61412f42d169ff4b128fd689d4753
CiteLips.exec9713c06526673bf18dbdaf46ea61ca9dd8fefe8ceec3be06c63db17e01e3741
RepublicChoir.exef649f66116a3351b60aa914e0b1944c2181485b1cf251fc9c1f6dab8a9db426b
6Zh7MvxYtHTBFX90Mn.exeb96360d48c2755ded301dd017b37dfdce921bdea7731c4b31958d945c8a0b8f5
ExclusivePottery.exe54c8a4f58b548c0cf6dbea2522e258723263ccde11d23e48985bdd1fd3535ce2
squarel.ps1d70ccae7914fc8c36c9e11b2a7f10bebd7f5696e78d8836554f4990b0f688dbb
MadCountries.exe9fe2c00641ece18898267b3c6e4ee0cb82ffefbc270c0767c441c3f38b63a12a
HockeyTract.exef136fa82ff73271708afe744f4e6a19cd5039e08ecd3ddad8e4d238f338f4d58
BruneiPlugins.exe453de65c9cc2dc62a67c502cd8bc26968acad9a671c1e095312c1fa6db4a7c74
CnnCylinder.exea76548a500d81dbb6f50419784a9b0323f5e42245ac7067af2adee0558167116
specreal.ps1d70ccae7914fc8c36c9e11b2a7f10bebd7f5696e78d8836554f4990b0f688dbb
InflationWinston.exedfbba64219fc63815db538ae8b51e07ec7132f4b39ba4a556c64bd3a5f024c2d
netsup.ps1 d70ccae7914fc8c36c9e11b2a7f10bebd7f5696e78d8836554f4990b0f688dbb
CfUltra.exe7880714c47260dba1fd4a4e4598e365b2a5ed0ad17718d8d192d28cf75660584
CalvinShoppercom.exe345a898d5eab800b7b7cbd455135c5474c5f0a9c366df3beb110f225ba734519
EscortUnavailable.exe258efd913cccdb70273c9410070f093337d5574b74c683c1cdff33baff9ffd7c
DisagreeProceed.exe9c82a2190930ec778688779a5ad52537d8b0856c8142c71631b308f1f8f0e772
BarbieBiblical.exe34f43bfc0a6f0d0f70b6eee0fa29c6dc62596ab2b867bbabd27c68153ea47f24
MysqlManaging.exeef1f9d507a137a4112ac92c576fc44796403eb53d71fe2ddb00376419c8a604e
PillsHarvest.exe4af3898ba3cf8b420ea1e6c5ce7cdca7775a4c9b78f67b493a9c73465432f1d3
BelfastProt.exead470bffbd120fc3a6c2c2e52af3c12f9f0153e76fee5e2b489a3d1870bdff03
HowardLikelihood.execc08892ace9ac746623b9d0178cd4d149f6a9ab10467fb9059d16f2c0038dcf9
SorryRequiring.exe4a2346d453b2ac894b67625640347c15e74e3091a9aa15629c3a808caaff1b2b
SearchMed.exeb0aab51b5e4a9cdd5b3d2785e4dea1ec06b20bc00e4015ccd79e0ba395a20fbd
RepublicChoir.exef649f66116a3351b60aa914e0b1944c2181485b1cf251fc9c1f6dab8a9db426b
DesignersCrawford.exee8452a65a452abdb4b2e629f767a038e0792e6e2393fb91bf17b27a0ce28c936
HumanitarianProvinces.exe25cfd6e6a9544990093566d5ea9d7205a60599bfda8c0f4d59fca31e58a7640b
ResetEngaging.exe51fbc196175f4fb9f38d843ee53710cde943e5caf1b0552624c7b65e6c231f7e
EducationalDerby.exe4a9a8c46ff96e4f066f51ff7e64b1c459967e0cdeb74b6de02cf1033e31c1c7b
StringsGrill.exef2a8840778484a56f1215f0fa8f6e8b0fb805fce99e62c01ff0a1f541f1d6808
CongressionalMechanics.exe2060509a63180c2f5075faf88ce7079c48903070c1c6b09fa3f9d6db05b8d9da
SexuallyWheat.exed39075915708d012f12b7410cd63e19434d630b2b7dbe60bd72ce003cd2efeaf
PerceptionCircuits.exe0e7dd3aa100d9e22d367cb995879ac4916cb4feb1c6085e06139e02cc7270bba
WWv63SKrHflebBd4VW.ps1483796a64f004a684a7bc20c1ddd5c671b41a808bc77634112e1703052666a64
WritingsShanghai.exefa131ea3ce9a9456e1d37065c7f7385ce98ffa329936b5fdd0fd0e78ade88ecb
IUService.exed5a6714ab95caa92ef1a712465a44c1827122b971bdb28ffa33221e07651d6f7
RttHlp.exe8aed681ad8d660257c10d2f0e85ae673184055a341901643f27afc38e5ef8473
ASmartService.exe75712824b916c1dc8978f65c060340dc69b1efa0145dddbf54299689b9f4a118
ClaireSpecifically.exe746abef4bde48da9f9bff3c23dd6edf8f1bea4b568df2a7d369cb30536ec9ce0
report.exe6daccc09f5f843b1fa4adde64ad282511f591a641cb474e123fed922167df6ae
xh6yIa7PXFCsasc0H5.exe5f17501193f5f823f419329bc20534461a7195aa4c456e27af6b0df5b0788041
yL6Iwcawoz3KDjg60m.exe5ecb4240fae36893973fb306c52c7e548308ebcfba6d101aad4e083407968a96
CustomsCampbell.exe5b80c7d65bb655ccb6e3264f4459a968edcda28084e0ddde16698f642b2d7d83
HoldemRover.exe4c60cdd1ee4045eb0b3bfda8326802d17565f3d1ff6829ac05775ebc6d9ca2dc
QUCvpZLobnhvno5v1t.exe4bac608722756c80c29fee6f73949c011ea78243e5267e86b7b20b3beeb79f9e
EmilyHaiti.exe3221f1356a91d4f06d1deee988be04597cc11bc1cab199ba9c43b9d80dfa88bd
PIPIPOO.exe15bf7a141a5a5e7e5c19ffbfbb5b781ae8db52d9ba5ffeb1364964580ed55b13
ReliefOrganizational.exe02533f92d522d47b9d630375633803dd8d6b4723e87d914cd29460d404134a66
HelloWorld.ps1670218cfc5c16d06762b6bc74cda4902087d812e72c52d6b9077c4c416485
251.zip0997201124780f11a16662a0d718b1a3ef3202c5153191f93511d7ecd0de4d8d
251.exe4b50e7fba5e33bac30b98494361d5ab725022c38271b3eb89b9c4aab457dca78

Fourth-stage AutoIT, NetSupport RAT, PowerShell, and Lumma

File name(s)SHA-256
Korea.com
Fabric.com
Affiliated.com
Weeks.com
Briefly.com
Denmark.com
Tanzania.com
Cookies.com
Spice.com
SophieHub.scr
SpaceWarp.scr
SkillSync.scr
Quantify.scr
HealthPulse
CogniFlow.scr
ArgonautGuard.scr
865347471135bb5459ad0e647e75a14ad91424b6f13a5c05d9ecd9183a8a1cf4
Warrant.com
Ford.com
AutoIt3.exe
Seq.com
Underwear.com
1300262a9d6bb6fcbefc0d299cce194435790e70b9c7b4a651e202e90a32fd49
Presentationhost.exe18df68d1581c11130c139fa52abb74dfd098a9af698a250645d6a4a65efcbf2d
erLX7UsT.ps12a29c9904d1860ea3177da7553c8b1bf1944566e5bc1e71340d9e0ff079f0bd3
675aff18abddc.exeadf5a9c2db09a782b3080fc011d45eb6eb597d8b475c3c27755992b1d7796e91
675aff18abddc.vbs5f2b66cf3370323f5be9d7ed8a0597bffea8cc1f76cd96ebb5a8a9da3a1bdc71
251.exe707a23dcd031c4b4969a021bc259186ca6fd4046d6b7b1aaffc90ba40b2a603b

Third-stage C2s

Indicator Type
hxxp://keikochio[.]com/staz/gribs.zip C2
hxxp://keikochio[.]com/incall.php?=compName=<computer name> C2
hxxps://stocktemplates[.]net/input.php?compName=<computer name> C2
hxxp://89.23.96[.]126/?v=3&event=ready&url=hxxp://188.245.94[.]250:443/auto/28cd7492facfd54e11d48e52398aefa7/251.exe C2

Fourth-stage C2s

Indicator Type 
45.141.84[.]60 IP address
91.202.233[.]18 IP address
154.216.20[.]131 IP address
5.10.250[.]240 IP address
79.132.128[.]77 IP address
hxxps://shortlearn[.]clickURL
hxxps://wrathful-jammy[.]cyouURL
hxxps://mycomp[.]cyouURL
hxxps://kefuguy[.]shopURL
hxxps://lumdukekiy[.]shopURL
hxxps://lumquvonee[.]shopURL
hxxps://klipcatepiu0[.]shopURL
hxxps://gostrm[.]shopURL
hxxps://ukuhost[.]netURL
hxxps://silversky[.]clubURL
hxxps://pub.culture-quest[.]shopURL
hxxps://se-blurry[.]bizURL
hxxps://zinc-sneark[.]bizURL
hxxps://dwell-exclaim[.]bizURL
hxxps://formy-spill[.]bizURL
hxxps://covery-mover[.]bizURL
hxxps://dare-curbys[.]bizURL
hxxps://impend-differ[.]bizURL
hxxps://dreasd[.]xyzURL
hxxps://ikores[.]sbsURL
hxxps://violettru[.]clickURL
hxxps://marshal-zhukov[.]comURL
hxxps://tailyoveriw[.]myURL

Fourth-stage testing connectivity sites

Indicator Type 
hxxps://baidu.comURL
hxxps://360.netURL
hxxps://praxlonfire73.liveURL

References

Learn more

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

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

Hear more about this discovery and how threat actors in this campaign leverage trusted platforms and advanced techniques to achieve their malicious goals in this episode of the Microsoft Threat Intelligence podcast, hosted by Sherrod DeGrippo: https://thecyberwire.com/podcasts/microsoft-threat-intelligence/39/notes. To hear stories and insights from the Microsoft Threat Intelligence community about the ever-evolving threat landscape, listen to the Microsoft Threat Intelligence podcast: https://thecyberwire.com/podcasts/microsoft-threat-intelligence.

The post Malvertising campaign leads to info stealers hosted on GitHub appeared first on Microsoft Security Blog.

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Storm-2372 conducts device code phishing campaign http://approjects.co.za/?big=en-us/security/blog/2025/02/13/storm-2372-conducts-device-code-phishing-campaign/ Fri, 14 Feb 2025 01:00:00 +0000 Microsoft Threat Intelligence Center discovered an active and successful device code phishing campaign by a threat actor we track as Storm-2372. Our ongoing investigation indicates that this campaign has been active since August 2024 with the actor creating lures that resemble messaging app experiences including WhatsApp, Signal, and Microsoft Teams. Storm-2372’s targets during this time have included government, non-governmental organizations (NGOs), information technology (IT) services and technology, defense, telecommunications, health, higher education, and energy/oil and gas in Europe, North America, Africa, and the Middle East. Microsoft assesses with medium confidence that Storm-2372 aligns with Russian interests, victimology, and tradecraft.

The post Storm-2372 conducts device code phishing campaign appeared first on Microsoft Security Blog.

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UPDATE (February 14, 2025): Within the past 24 hours, Microsoft has observed Storm-2372 shifting to using the specific client ID for Microsoft Authentication Broker in the device code sign-in flow. More details below.

Executive summary:

Today we’re sharing that Microsoft discovered cyberattacks being launched by a group we call Storm-2372, who we assess with moderate confidence aligns with Russia’s interests and tradecraft. The attacks appear to have been ongoing since August 2024 and have targeted governments, NGOs, and a wide range of industries in multiple regions. The attacks use a specific phishing technique called “device code phishing” that tricks users to log into productivity apps while Storm-2372 actors capture the information from the log in (tokens) that they can use to then access compromised accounts. These tokens are part of an industry standard and, while these phishing lures used Microsoft and other apps to trick users, they do not reflect an attack unique to Microsoft nor have we found any vulnerabilities in our code base enabling this activity.

Microsoft Threat Intelligence Center discovered an active and successful device code phishing campaign by a threat actor we track as Storm-2372. Our ongoing investigation indicates that this campaign has been active since August 2024 with the actor creating lures that resemble messaging app experiences including WhatsApp, Signal, and Microsoft Teams. Storm-2372’s targets during this time have included government, non-governmental organizations (NGOs), information technology (IT) services and technology, defense, telecommunications, health, higher education, and energy/oil and gas in Europe, North America, Africa, and the Middle East. Microsoft assesses with moderate confidence that Storm-2372 aligns with Russian interests, victimology, and tradecraft.  

In device code phishing, threat actors exploit the device code authentication flow to capture authentication tokens, which they then use to access target accounts, and further gain access to data and other services that the compromised account has access to. This technique could enable persistent access as long as the tokens remain valid, making this attack technique attractive to threat actors.

The phishing attack identified in this blog masquerades as Microsoft Teams meeting invitations delivered through email. When targets click the meeting invitation, they are prompted to authenticate using a threat actor-generated device code. The actor then receives the valid access token from the user interaction, stealing the authenticated session.

Because of the active threat represented by Storm-2372 and other threat actors exploiting device code phishing techniques, we are sharing our latest research, detections, and mitigation guidance on this campaign to raise awareness of the observed tactics, techniques, and procedures (TTPs), educate organizations on how to harden their attack surfaces, and disrupt future operations by this threat actor. Microsoft uses Storm designations as a temporary name given to an unknown, emerging, or developing cluster of threat activity, allowing Microsoft to track it as a unique set of information until we reach high confidence about the origin or identity of the threat actor behind the activity.

Microsoft Threat Intelligence Center continues to track campaigns launched by Storm-2372, and, when able, directly notifies customers who have been targeted or compromised, providing them with the necessary information to help secure their environments. Microsoft is also tracking other groups using similar techniques, including those documented by Volexity in their recent publication.

How does device code phishing work?

A device code authentication flow is a numeric or alphanumeric code used to authenticate an account from an input-constrained device that does not have the ability to perform an interactive authentication using a web flow and thus must perform this authentication on another device to sign-in. In device code phishing, threat actors exploit the device code authentication flow.

During the attack, the threat actor generates a legitimate device code request and tricks the target into entering it into a legitimate sign-in page. This grants the actor access and enables them to capture the authentication—access and refresh—tokens that are generated, then use those tokens to access the target’s accounts and data. The actor can also use these phished authentication tokens to gain access to other services where the user has permissions, such as email or cloud storage, without needing a password. The threat actor continues to have access so long as the tokens remain valid. The attacker can then use the valid access token to move laterally within the environment.

Diagram showing the device code phishing attack chain
Figure 1. Device code phishing attack cycle

Storm-2372 phishing lure and access

Storm-2372’s device code phishing campaign has been active since August 2024. Observed early activity indicates that Storm-2372 likely targeted potential victims using third-party messaging services including WhatsApp, Signal, and Microsoft Teams, falsely posing as a prominent person relevant to the target to develop rapport before sending subsequent invitations to online events or meetings via phishing emails.

Screenshots of Signal messages from threat actor
Figure 2. Sample messages from the threat actor posing as a prominent person and building rapport on Signal

The invitations lure the user into completing a device code authentication request emulating the experience of the messaging service, which provides Storm-2372 initial access to victim accounts and enables Graph API data collection activities, such as email harvesting.

Screenshot of Microsoft Teams lure
Figure 3. Example of lure used in phishing campaign

On the device code authentication page, the user is tricked into entering the code that the threat actor included as the ID for the fake Teams meeting invitation.

Post-compromise activity

Once the victim uses the device code to authenticate, the threat actor receives the valid access token. The threat actor then uses this valid session to move laterally within the newly compromised network by sending additional phishing messages containing links for device code authentication to other users through intra-organizational emails originating from the victim’s account.

Screenshot of device code authentication page
Figure 4. Legitimate device code authentication page

Additionally, Microsoft observed Storm-2372 using Microsoft Graph to search through messages of the account they’ve compromised. The threat actor was using keyword searching to view messages containing words such as username, password, admin, teamviewer, anydesk, credentials, secret, ministry, and gov. Microsoft then observed email exfiltration via Microsoft Graph of the emails found from these searches.

February 14, 2025 update:

Within the past 24 hours, Microsoft has observed Storm-2372 shifting to using the specific client ID for Microsoft Authentication Broker in the device code sign-in flow. Using this client ID enables Storm-2372 to receive a refresh token that can be used to request another token for the device registration service, and then register an actor-controlled device within Entra ID. With the same refresh token and the new device identity, Storm-2372 is able to obtain a Primary Refresh Token (PRT) and access an organization’s resources. We have observed Storm-2372 using the connected device to collect emails.

The actor has also been observed to use proxies that are regionally appropriate for the targets, likely in an attempt to further conceal the suspicious sign in activity.

While many of the mitigations and queries listed below still apply in this scenario, alerts involving anomalous token or PRT activity surrounding close-in-time device registrations may also be a useful method for identifying this shift in technique. Additionally, enrollment restrictions – limiting the user permissions that can enroll devices into your Microsoft Entra ID environment – can also help to address this attack behavior.

Attribution

The actor that Microsoft tracks as Storm-2372 is a suspected nation-state actor working toward Russian state interests. It notably has used device code phishing to compromise targets of interest. Storm-2372 likely initially approaches targets through third-party messaging services, posing as a prominent individual relevant to the target to develop rapport before sending invites to online events or meetings. These invites lure the user into device code authentication that grants initial access to Storm-2372 and enables Graph API data collection activities such as email harvesting.

Storm-2372 targets include government, NGOs, IT services and technology, defense, telecommunications, health, higher education, and energy/oil and gas in Europe, North America, Africa, and the Middle East.

Mitigation and protection guidance

To harden networks against the Storm-2372 activity described above, defenders can implement the following:

  • Only allow device code flow where necessary. Microsoft recommends blocking device code flow wherever possible. Where necessary, configure Microsoft Entra ID’s device code flow in your Conditional Access policies.
  • Educate users about common phishing techniques. Sign-in prompts should clearly identify the application being authenticated to. As of 2021, Microsoft Azure interactions prompt the user to confirm (“Cancel” or “Continue”) that they are signing in to the app they expect, which is an option frequently missing from phishing sign-ins.
  • If suspected Storm-2372 or other device code phishing activity is identified, revoke the user’s refresh tokens by calling revokeSignInSessions. Consider setting a Conditional Access Policy to force re-authentication for users.
  • Implement a sign-in risk policy to automate response to risky sign-ins. A sign-in risk represents the probability that a given authentication request isn’t authorized by the identity owner. A sign-in risk-based policy can be implemented by adding a sign-in risk condition to Conditional Access policies that evaluates the risk level of a specific user or group. Based on the risk level (high/medium/low), a policy can be configured to block access or force multi-factor authentication.
    • When a user is a high risk and Conditional access evaluation is enabled, the user’s access is revoked, and they are forced to re-authenticate.
    • For regular activity monitoring, use Risky sign-in reports, which surface attempted and successful user access activities where the legitimate owner might not have performed the sign-in. 

The following best practices further help improve organizational defenses against phishing and other credential theft attacks:

  • Require multifactor authentication (MFA). While certain attacks such as device code phishing attempt to evade MFA, implementation of MFA remains an essential pillar in identity security and is highly effective at stopping a variety of threats.
  • Centralize your organization’s identity management into a single platform. If your organization is a hybrid environment, integrate your on-premises directories with your cloud directories. If your organization is using a third-party for identity management, ensure this data is being logged in a SIEM or connected to Microsoft Entra to fully monitor for malicious identity access from a centralized location. The added benefits to centralizing all identity data is to facilitate implementation of Single Sign On (SSO) and provide users with a more seamless authentication process, as well as configure Entra ID’s machine learning models to operate on all identity data, thus learning the difference between legitimate access and malicious access quicker and easier. It is recommended to synchronize all user accounts except administrative and high privileged ones when doing this to maintain a boundary between the on-premises environment and the cloud environment, in case of a breach.
  • Secure accounts with credential hygiene: practice the principle of least privilege and audit privileged account activity in your Entra ID environments to slow and stop attackers.

Microsoft Defender XDR detections

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

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

Microsoft Defender for Office 365

Microsoft Defender for Office 365 detects malicious activity associated with this threat through the following alerts:

  • This email has traits consistent with phishing
  • This HTML has traits consistent with phishing

Microsoft Entra ID Protection

The following Microsoft Entra ID Protection risk detections inform Entra ID user risk events and can indicate associated threat activity, including unusual user activity consistent with known attack patterns identified by Microsoft Threat Intelligence research:

Hunting queries

Microsoft Defender XDR

The following query can help identify possible device code phishing attempts:

let suspiciousUserClicks = materialize(UrlClickEvents
    | where ActionType in ("ClickAllowed", "UrlScanInProgress", "UrlErrorPage") or IsClickedThrough != "0"
    | where UrlChain has_any ("microsoft.com/devicelogin", "login.microsoftonline.com/common/oauth2/deviceauth")
    | extend AccountUpn = tolower(AccountUpn)
    | project ClickTime = Timestamp, ActionType, UrlChain, NetworkMessageId, Url, AccountUpn);
//Check for Risky Sign-In in the short time window
let interestedUsersUpn = suspiciousUserClicks
    | where isnotempty(AccountUpn)
    | distinct AccountUpn;
let suspiciousSignIns = materialize(AADSignInEventsBeta
    | where ErrorCode == 0
    | where AccountUpn in~ (interestedUsersUpn)
    | where RiskLevelDuringSignIn in (10, 50, 100)
    | extend AccountUpn = tolower(AccountUpn)
    | join kind=inner suspiciousUserClicks on AccountUpn
    | where (Timestamp - ClickTime) between (-2min .. 7min)
    | project Timestamp, ReportId, ClickTime, AccountUpn, RiskLevelDuringSignIn, SessionId, IPAddress, Url
);
//Validate errorCode 50199 followed by success in 5 minute time interval for the interested user, which suggests a pause to input the code from the phishing email
let interestedSessionUsers = suspiciousSignIns
    | where isnotempty(AccountUpn)
    | distinct AccountUpn;
let shortIntervalSignInAttemptUsers = materialize(AADSignInEventsBeta
    | where AccountUpn in~ (interestedSessionUsers)
    | where ErrorCode in (0, 50199)
    | summarize ErrorCodes = make_set(ErrorCode) by AccountUpn, CorrelationId, SessionId
    | where ErrorCodes has_all (0, 50199)
    | distinct AccountUpn);
suspiciousSignIns
| where AccountUpn in (shortIntervalSignInAttemptUsers)

This following query from public research surfaces newly registered devices, and can be a useful in conjunction with anomalous or suspicious user or token activity:

CloudAppEvents
| where AccountDisplayName == "Device Registration Service"
| extend ApplicationId_ = tostring(ActivityObjects[0].ApplicationId)
| extend ServiceName_ = tostring(ActivityObjects[0].Name)
| extend DeviceName = tostring(parse_json(tostring(RawEventData.ModifiedProperties))[1].NewValue)
| extend DeviceId = tostring(parse_json(tostring(parse_json(tostring(RawEventData.ModifiedProperties))[6].NewValue))[0])
| extend DeviceObjectId_ = tostring(parse_json(tostring(RawEventData.ModifiedProperties))[0].NewValue)
| extend UserPrincipalName = tostring(RawEventData.ObjectId)
| project TimeGenerated, ServiceName_, DeviceName, DeviceId, DeviceObjectId_, UserPrincipalName

Microsoft Sentinel

Microsoft Sentinel customers can use the following queries to detect phishing attempts and email exfiltration attempts via Graph API. While these queries are not specific to threat actors, they can help you stay vigilant and safeguard your organization from phishing attacks:

References

Learn more

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

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

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

The post Storm-2372 conducts device code phishing campaign appeared first on Microsoft Security Blog.

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New Star Blizzard spear-phishing campaign targets WhatsApp accounts http://approjects.co.za/?big=en-us/security/blog/2025/01/16/new-star-blizzard-spear-phishing-campaign-targets-whatsapp-accounts/ Thu, 16 Jan 2025 17:00:00 +0000 In mid-November 2024, Microsoft Threat Intelligence observed the Russian threat actor we track as Star Blizzard sending their typical targets spear-phishing messages, this time offering the supposed opportunity to join a WhatsApp group. This is the first time we have identified a shift in Star Blizzard’s longstanding tactics, techniques, and procedures (TTPs) to leverage a […]

The post New Star Blizzard spear-phishing campaign targets WhatsApp accounts appeared first on Microsoft Security Blog.

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In mid-November 2024, Microsoft Threat Intelligence observed the Russian threat actor we track as Star Blizzard sending their typical targets spear-phishing messages, this time offering the supposed opportunity to join a WhatsApp group. This is the first time we have identified a shift in Star Blizzard’s longstanding tactics, techniques, and procedures (TTPs) to leverage a new access vector. Star Blizzard’s targets are most commonly related to government or diplomacy (both incumbent and former position holders), defense policy or international relations researchers whose work touches on Russia, and sources of assistance to Ukraine related to the war with Russia.

In our last blog post about Star Blizzard, we discussed how the threat actor targeted dozens of civil society organizations—journalists, think tanks, and non-governmental organizations (NGOs)—between January 2023 and August 2024 by deploying spear-phishing campaigns to exfiltrate sensitive information and interfere in their activities. Since October 3, 2024, Microsoft and the US Department of Justice have seized or taken down more than 180 websites related to that activity. While this coordinated action had a short-term impact on Star Blizzard’s phishing operations, we noted at the time that after this threat actor’s active infrastructure was exposed, they swiftly transitioned to new domains to continue their operations, indicating that the threat actor is highly resilient to operational disruptions.

We assess the threat actor’s shift to compromising WhatsApp accounts is likely in response to the exposure of their TTPs by Microsoft Threat Intelligence and other organizations, including national cybersecurity agencies. While this campaign appears to have wound down at the end of November, we are highlighting the new shift as a sign that the threat actor could be seeking to change its TTPs in order to evade detection.

As part of our continuous monitoring, analysis, and reporting on the threat landscape, we are sharing our information on Star Blizzard’s latest activity to raise awareness of this threat actor’s shift in tradecraft and to educate organizations on how to harden their attack surfaces against this and similar activity. We also directly notify customers who have been targeted or compromised, providing them with the necessary information to help secure their environments.

Targeting WhatsApp account data

Star Blizzard’s new spear-phishing campaign, while novel in that it uses and targets WhatsApp for the first time, exhibits familiar spear-phishing TTPs for Star Blizzard, with the threat actor initiating email contact with their targets, to engage them, before sending them a second message containing a malicious link. The sender address used by the threat actor in this campaign impersonates a US government official, continuing Star Blizzard’s practice of impersonating known political/diplomatic figures, to further ensure target engagement. The initial email sent to targets contains a quick response (QR) code purporting to direct users to join a WhatsApp group on “the latest non-governmental initiatives aimed at supporting Ukraine NGOs.” This code, however, is intentionally broken and will not direct the user towards any valid domain; this is an effort to coax the target recipient into responding.

A close-up of a text
Figure 1. Star Blizzard initial spear-phishing email with broken QR code

When the recipient responds, Star Blizzard sends a second email containing a Safe Links-wrapped t[.]ly shortened link as the alternative link to join the WhatsApp group.

A black text on a white background
Figure 2. Star Blizzard follow-on spear-phishing email with URL link

When this link is followed, the target is redirected to a webpage asking them to scan a QR code to join the group. However, this QR code is actually used by WhatsApp to connect an account to a linked device and/or the WhatsApp Web portal. This means that if the target follows the instructions on this page, the threat actor can gain access to the messages in their WhatsApp account and have the capability to exfiltrate this data using existing browser plugins, which are designed for exporting WhatsApp messages from an account accessed via WhatsApp Web.

Screenshot of the phish attempt displaying a legitimate WhatsApp webpage called To join the US-Ukraine NGOs Group, followed by instructions directing the user to scan the redacted QR code to link their device.
Figure 3. Malicious Star Blizzard phish attempt using WhatsApp linking QR code

While this campaign was limited and appeared to have terminated at the end of November, it nevertheless marked a break in long-standing Star Blizzard TTPs and highlighted the threat actor’s tenacity in continuing spear-phishing campaigns to gain access to sensitive information even in the face of repeated degradations of their operations.

Microsoft Threat Intelligence recommends that all email users belonging to sectors that Star Blizzard typically targets always remain vigilant when dealing with email, especially emails containing links to external resources. These targets are most commonly related to:

  • Government or diplomacy (incumbent and former position holders)
  • Research into defense policy or international relations when related to Russia
  • Assistance to Ukraine related to the ongoing conflict with Russia

When in doubt, contact the person you think is sending the email using a known and previously used email address to verify that the email was indeed sent by them.

Mitigations

To harden networks against the Star Blizzard activity listed above, defenders can implement the following:

  • Implement Microsoft Defender for Endpoint on Android and iOS, which includes anti-phishing capabilities that also apply to QR code phishing attacks, blocking phishing sites from being accessed. 
  • Enable network protection in Microsoft Defender for Endpoint
  • Ensure that tamper protection is enabled in Microsoft Dender for Endpoint
  • Run endpoint detection and response in block mode so that Microsoft Defender for Endpoint can block malicious artifacts, even when your non-Microsoft antivirus does not detect the threat or when Microsoft Defender Antivirus is running in passive mode.
  • Configure investigation and remediation in full automated mode to let Microsoft Defender for Endpoint take immediate action on alerts to resolve breaches, significantly reducing alert volume.
  • Turn on PUA protection in block mode in Microsoft Defender Antivirus
  • Turn on cloud-delivered protection in Microsoft Defender Antivirus or the equivalent for your antivirus product to cover rapidly evolving attacker tools and techniques.
  • Turn on Microsoft Defender Antivirus real-time protection.
  • Encourage users to use Microsoft Edge and other web browsers that support SmartScreen, which identifies and blocks malicious websites, including phishing sites, scam sites, and sites that host malware.
  • Turn on Safe Links and Safe Attachments for Office 365.
  • Use the Attack Simulator in Microsoft Defender for Office 365 to run realistic, yet safe, simulated phishing and password attack campaigns. Utilize the QR code payload in attack simulation training scenarios to mirror Star Blizzard’s and other threat actor’s QR code spear-phishing techniques.

Microsoft Defender XDR detections

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

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

Microsoft Defender for Endpoint

The following alerts might indicate threat activity associated with this threat. These alerts, however, can be triggered by unrelated threat activity and are not monitored in the status cards provided with this report.

  • Star Blizzard activity group

Hunting queries

Microsoft Defender XDR

Surface events that may have communicated with the Star Blizzard C2s

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

Microsoft Sentinel

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

While the below queries are not linked to any specific threat actor, they are effective in detecting potential phishing attempts. Implementing these queries can help you stay vigilant and safeguard your organization from phishing attacks

Microsoft Security Copilot

Security Copilot customers can use the standalone experience to create their own prompts or run the following pre-built promptbooks to automate incident response or investigation tasks related to this threat:

  • Incident investigation
  • Microsoft User analysis
  • Threat actor profile
  • Threat Intelligence 360 report based on MDTI article

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

Threat intelligence reports

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

Microsoft Defender Threat Intelligence

Microsoft Security Copilot customers can also use the Microsoft Security Copilot integration in Microsoft Defender Threat Intelligence, either in the Security Copilot standalone portal or in the embedded experience in the Microsoft Defender portal to get more information about this threat actor.

Indicators of compromise

IndicatorTypeLast seen
civilstructgeo[.]orgDomainOctober 2024
aerofluidthermo[.]orgDomainOctober 2024

References

Learn more

For further information on the threats detailed in this blog post, refer to these additional Microsoft blogs:

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

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

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

The post New Star Blizzard spear-phishing campaign targets WhatsApp accounts appeared first on Microsoft Security Blog.

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Microsoft shares latest intelligence on North Korean and Chinese threat actors at CYBERWARCON http://approjects.co.za/?big=en-us/security/blog/2024/11/22/microsoft-shares-latest-intelligence-on-north-korean-and-chinese-threat-actors-at-cyberwarcon/ Fri, 22 Nov 2024 11:00:00 +0000 At CYBERWARCON 2024, Microsoft Threat Intelligence analysts will share research and insights on North Korean and Chinese threat actors representing years of threat actor tracking, infrastructure monitoring and disruption, and their attack tooling.

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

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This year at CYBERWARCON, Microsoft Threat Intelligence analysts are sharing research and insights representing years of threat actor tracking, infrastructure monitoring and disruption, and attacker tooling.

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

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

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

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

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

Sapphire Sleet: Social engineering leading to cryptocurrency theft

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

Masquerading as a venture capitalist

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

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

Posing as recruiters

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

Screenshot of two LinkedIn profiles of fake recruiters
Figure 1. LinkedIn profiles of fake recruiters. LinkedIn accounts identified to be related to this attack have been taken down.

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

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

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

North Korean IT workers: The triple threat

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

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

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

Facilitators complicate tracking of IT worker ecosystem

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

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

  • Creating or renting their bank account to the North Korean IT worker
  • Creating LinkedIn accounts to be used for contacting recruiters to obtain work
  • Purchasing mobile phone numbers or SIM cards
  • Creating additional accounts on freelance job sites
Attack chain diagram showing the North Korean IT worker ecosystem from setting up, doing remote work, and getting payment.
Figure 2. The North Korean IT worker ecosystem

Fake profiles and portfolios with the aid of AI

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

screenshot of developer profile of a North Korean IT worker
Figure 3. Example profile used by North Korean IT workers that has since been taken down.

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

Screenshot of a LinkedIn profile of a North Korean IT worker
Figure 4. An example of a North Korean IT worker LinkedIn profile that has since been taken down.

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

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

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

Photos showing how AI used to modify photos for North Korean IT worker used in resumes and profiles
Figure 5. Use of AI apps to modify photos used for North Korean IT workers’ resumes and profiles
Screenshot of resumes of North Korea IT workers
Figure 6. Examples of resumes for North Korean IT workers. These two resumes use different versions of the same photo.

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

Screenshot of repository with supposed photos of North Korean IT workers
Figure 7. Photos of potential North Korean IT workers

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

Getting payment for remote work

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

Protecting organizations from North Korean IT workers

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

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

Storm-2077: No targets left behind

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

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

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

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

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

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

CYBERWARCON Recap

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

Learn more

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

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

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

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

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​​Cyber Signals Issue 8 | Education under siege: How cybercriminals target our schools​​ http://approjects.co.za/?big=en-us/security/blog/2024/10/10/cyber-signals-issue-8-education-under-siege-how-cybercriminals-target-our-schools/ Thu, 10 Oct 2024 11:00:00 +0000 ​This edition of Cyber Signals delves into the cybersecurity challenges facing classrooms and campuses, highlighting the critical need for robust defenses and proactive measures. From personal devices to virtual classes and research stored in the cloud, the digital footprint of school districts, colleges, and universities has multiplied exponentially.​

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Introduction | Security snapshot | Threat briefing
Defending against attacks | Expert profile 

Education is essentially an “industry of industries,” with K-12 and higher education enterprises handling data that could include health records, financial data, and other regulated information. At the same time, their facilities can host payment processing systems, networks that are used as internet service providers (ISPs), and other diverse infrastructure. The cyberthreats that Microsoft observes across different industries tend to be compounded in education, and threat actors have realized that this sector is inherently vulnerable. With an average of 2,507 cyberattack attempts per week, universities are prime targets for malware, phishing, and IoT vulnerabilities.¹ 

Security staffing and IT asset ownership also affect education organizations’ cyber risks. School and university systems, like many enterprises, often face a shortage of IT resources and operate a mix of both modern and legacy IT systems. Microsoft observes that in the United States, students and faculty are more likely to use personal devices in education compared to Europe, for example. Regardless of ownership however, in these and other regions, busy users do not always have a security mindset. 

A mortarboard with QR code design on top, next to the text

This edition of Cyber Signals delves into the cybersecurity challenges facing classrooms and campuses, highlighting the critical need for robust defenses and proactive measures. From personal devices to virtual classes and research stored in the cloud, the digital footprint of school districts, colleges, and universities has multiplied exponentially.  

We are all defenders. 

Section header with the text “Security Snapshot.”
Two icons, each beside a text bubble containing a stat about cyber threats against educational institutions.
Section header with the text “Threat briefing.”

A uniquely valuable and vulnerable environment 

The education sector’s user base is very different from a typical large commercial enterprise. In the K-12 environment, users include students as young as six years old. Just like any public or private sector organization, there is a wide swath of employees in school districts and at universities including administration, athletics, health services, janitorial, food service professionals, and others. Multiple activities, announcements, information resources, open email systems, and students create a highly fluid environment for cyberthreats.

Virtual and remote learning have also extended education applications into households and offices. Personal and multiuser devices are ubiquitous and often unmanaged—and students are not always cognizant about cybersecurity or what they allow their devices to access.

Education is also on the front lines confronting how adversaries test their tools and their techniques. According to data from Microsoft Threat Intelligence, the education sector is the third-most targeted industry, with the United States seeing the greatest cyberthreat activity.

Cyberthreats to education are not only a concern in the United States. According to the United Kingdom’s Department of Science Innovation and Technology 2024 Cybersecurity Breaches Survey, 43% of higher education institutions in the UK reported experiencing a breach or cyberattack at least weekly.² 

QR codes provide an easily disguised surface for phishing cyberattacks

Today, quick response (QR) codes are quite popular—leading to increased risks of phishing cyberattacks designed to gain access to systems and data. Images in emails, flyers offering information about campus and school events, parking passes, financial aid forms, and other official communications all frequently contain QR codes. Physical and virtual education spaces might be the most “flyer friendly” and QR code-intensive environments anywhere, given how big a role handouts, physical and digital bulletin boards, and other casual correspondence help students navigate a mix of curriculum, institutional, and social correspondence. This creates an attractive backdrop for malicious actors to target users who are trying to save time with a quick image scan. 

Recently the United States Federal Trade Commission issued a consumer alert on the rising threat of malicious QR codes being used to steal login credentials or deliver malware.³

Microsoft Defender for Office 365 telemetry shows that approximately more than 15,000 messages with malicious QR codes are targeted toward the educational sector daily—including phishing, spam, and malware. 

Legitimate software tools can be used to quickly generate QR codes with embedded links to be sent in email or posted physically as part of a cyberattack. And those images are hard for traditional email security solutions to scan, making it even more important for faculty and students to use devices and browsers with modern web defenses. 

Targeted users in the education sector may use personal devices without endpoint security. QR codes essentially enable the threat actor to pivot to these devices. QR code phishing (since its purpose is to target mobile devices) is compelling evidence of mobile devices being used as an attack vector into enterprises—such as personal accounts and bank accounts—and the need for mobile device protection and visibility. Microsoft has significantly disrupted QR code phishing attacks. This shift in tactics is evident in the substantial decrease in daily phishing emails intercepted by our system, dropping from 3 million in December 2023 to just 179,000 by March 2024. 

A pie chart in front of a blue background
Source: Microsoft incident response engagements.

Universities present their own unique challenges. Much of university culture is based on collaboration and sharing to drive research and innovation. Professors, researchers, and other faculty operate under the notion that technology, science—simply knowledge itself—should be shared widely. If someone appearing as a student, peer, or similar party reaches out, they’re often willing to discuss potentially sensitive topics without scrutinizing the source. 

University operations also span multiple industries. University presidents are effectively CEOs of healthcare organizations, housing providers, and large financial organizations—the industry of industries factor, again. Therefore, top leaders can can be prime targets for anyone attacking those sectors.

The combination of value and vulnerability found in education systems has attracted the attention of a spectrum of cyberattackers—from malware criminals employing new techniques to nation-state threat actors engaging in old-school spy craft.  

Microsoft continually monitors threat actors and threat vectors worldwide. Here are some key issues we’re seeing for education systems. 

Email systems in schools offer wide spaces for compromise 

The naturally open environment at most universities forces them to be more relaxed in their email hygiene. They have a lot of emails amounting to noise in the system, but are often operationally limited in where and how they can place controls, because of how open they need to be for alumni, donors, external user collaboration, and many other use cases.  

Education institutions tend to share a lot of announcements in email. They share informational diagrams around local events and school resources. They commonly allow external mailers from mass mailing systems to share into their environments. This combination of openness and lack of controls creates a fertile ground for cyberattacks.

AI is increasing the premium on visibility and control  

Cyberattackers recognizing higher education’s focus on building and sharing can survey all visible access points, seeking entry into AI-enabled systems or privileged information on how these systems operate. If on-premises and cloud-based foundations of AI systems and data are not secured with proper identity and access controls, AI systems become vulnerable. Just as education institutions adapted to cloud services, mobile devices and hybrid learning—which introduced new waves of identities and privileges to govern, devices to manage, and networks to segment—they must also adapt to the cyber risks of AI by scaling these timeless visibility and control imperatives.

Nation-state actors are after valuable IP and high-level connections 

Universities handling federally funded research, or working closely with defense, technology, and other industry partners in the private sector, have long recognized the risk of espionage. Decades ago, universities focused on telltale physical signs of spying. They knew to look for people showing up on campus taking pictures or trying to get access to laboratories. Those are still risks, but today the dynamics of digital identity and social engineering have greatly expanded the spy craft toolkit. 

Universities are often epicenters of highly sensitive intellectual property. They may be conducting breakthrough research. They may be working on high-value projects in aerospace, engineering, nuclear science, or other sensitive topics in partnership with multiple government agencies.  

For cyberattackers, it can be easier to first compromise somebody in the education sector who has ties to the defense sector and then use that access to more convincingly phish a higher value target.  

Universities also have experts in foreign policy, science, technology, and other valuable disciplines, who may willingly offer intelligence, if deceived in social-engineering cyberattacks employing false or stolen identities of peers and others who appear to be in individuals’ networks or among trusted contacts. Apart from holding valuable intelligence themselves, compromised accounts of university employees can become springboards into further campaigns against wider government and industry targets.

Nation-state actors targeting education 

Subsection header with Sandstorm icon and the text “Iran.”

Peach Sandstorm

Peach Sandstorm has used password spray attacks against the education sector to gain access to infrastructure used in those industries, and Microsoft has also observed the organization using social engineering against targets in higher education.  

Mint Sandstorm 

Microsoft has observed a subset of this Iranian attack group targeting high-profile experts working on Middle Eastern affairs at universities and research organizations. These sophisticated phishing attacks used social engineering to compel targets to download malicious files including a new, custom backdoor called MediaPl. 

Mabna Institute  

In 2023, the Iranian Mabna Institute conducted intrusions into the computing systems of at least 144 United States universities and 176 universities in 21 other countries.  

The stolen login credentials were used for the benefit of Iran’s Islamic Revolutionary Guard Corps and were also sold within Iran through the web. Stolen credentials belonging to university professors were used to directly access university library systems. 

Subsection header with Sleet icon and the text “North Korea.”

Emerald Sleet

This North Korean group primarily targets experts in East Asian policy or North and South Korean relations. In some cases, the same academics have been targeted by Emerald Sleet for nearly a decade.  

Emerald Sleet uses AI to write malicious scripts and content for social engineering, but these attacks aren’t always about delivering malware. There’s also an evolving trend where they simply ask experts for policy insight that could be used to manipulate negotiations, trade agreements, or sanctions. 

Moonstone Sleet 

Moonstone Sleet is another North Korean actor that has been taking novel approaches like creating fake companies to forge business relationships with educational institutions or a particular faculty member or student.  

One of the most prominent attacks from Moonstone Sleet involved creating a fake tank-themed game used to target individuals at educational institutions, with a goal to deploy malware and exfiltrate data. 

Subsection header with Storm icon and the text “Groups in development.”

Storm-1877  

This actor largely engages in cryptocurrency theft using a custom malware family that they deploy through various means. The ultimate goal of this malware is to steal crypto wallet addresses and login credentials for crypto platforms.  

Students are often the target for these attacks, which largely start on social media. Storm-1877 targets students because they may not be as aware of digital threats as professionals in industry. 

Section header with the text “Defending against attacks.”

A new security curriculum 

Due to education budget and talent constraints and the inherent openness of its environment, solving education security is more than a technology problem. Security posture management and prioritizing security measures can be a costly and challenging endeavor for these institutions—but there is a lot that school systems can do to protect themselves.  

Maintaining and scaling core cyberhygiene will be key to securing school systems. Building awareness of security risks and good practices at all levels—students, faculty, administrators, IT staff, campus staff, and more—can help create a safer environment.  

For IT and security professionals in the education sector, doing the basics and hardening the overall security posture is a good first step. From there, centralizing the technology stack can help facilitate better monitoring of logging and activity to gain a clearer picture into the overall security posture and any vulnerabilities. 

Oregon State University 

Oregon State University (OSU), an R1 research-focused university, places a high priority on safeguarding its research to maintain its reputation. In 2021, it experienced an extensive cybersecurity incident unlike anything before. The cyberattack revealed gaps in OSU’s security operations.

“The types of threats that we’re seeing, the types of events that are occurring in higher education, are much more aggressive by cyber adversaries.”

—David McMorries, Chief Information Security Officer at Oregon State University

In response to this incident, OSU created its Security Operations Center (SOC), which has become the centerpiece of the university’s security effort. AI has also helped automate capabilities and helped its analysts, who are college students, learn how to quickly write code—such as threat hunting with more advanced hunting queries. 

Arizona Department of Education 

A focus on Zero Trust and closed systems is an area that the Arizona Department of Education (ADE) takes further than the state requirements. It blocks all traffic from outside the United States from its Microsoft 365 environment, Azure, and its local datacenter.

“I don’t allow anything exposed to the internet on my lower dev environments, and even with the production environments, we take extra care to make sure that we use a network security group to protect the app services.”

—Chris Henry, Infrastructure Manager at the Arizona Department of Education 

Three icons on a whiteboard background, each beside a text bubble containing information on defending against cyberattacks.

Follow these recommendations:  

  • The best defense against QR code attacks is to be aware and pay attention. Pause, inspect the code’s URL before opening it, and don’t open QR codes from unexpected sources, especially if the message uses urgent language or contains errors. 
  • Consider implementing “protective domain name service,” a free tool that helps prevent ransomware and other cyberattacks by blocking computer systems from connecting to harmful websites. Prevent password spray attacks with a stringent password and deploy multifactor authentication.  
  • Educate students and staff about their security hygiene, and encourage them to use multifactor authentication or passwordless protections. Studies have shown that an account is more than 99.9% less likely to be compromised when using multifactor authentication.   
Section header with the text “Expert profile”

Corey Lee has always had an interest in solving puzzles and crimes. He started his college career at Penn State University in criminal justice, but soon realized his passion for digital forensics after taking a course about investigating a desktop computer break-in.  

After completing his degree in security and risk analysis, Corey came to Microsoft focused on gaining cross-industry experience. He’s worked on securing everything from federal, state, and local agencies to commercial enterprises, but today he focuses on the education sector.  

Headshot of Corey Lee next to his quote.

After spending time working across industries, Corey sees education through a different lens—the significantly unique industry of industries. The dynamics at play inside the education sector include academic institutions, financial services, critical infrastructure like hospitals and transportation, and partnerships with government agencies. According to Corey, working in such a broad field allows him to leverage skillsets from multiple industries to address specific problems across the landscape. 

The fact that education could also be called underserved from a cybersecurity standpoint is another compelling challenge, and part of Corey’s personal mission. The education industry needs cybersecurity experts to elevate the priority of protecting school systems. Corey works across the public and industry dialogue, skilling and readiness programs, incident response, and overall defense to protect not just the infrastructure of education, but students, parents, teachers, and staff. 

Today, Corey is focused reimagining student security operations centers, including how to inject AI into the equation and bring modern technology and training to the table. By growing the cybersecurity work force in education and giving them new tools, he’s working to elevate security in the sector in a way that’s commensurate with how critical the industry is for the future. 

Next steps with Microsoft Security

To learn more about Microsoft Security solutions, visit our website. Bookmark the Security blog to keep up with our expert coverage on security matters. Also, follow us on LinkedIn (Microsoft Security) and X (@MSFTSecurity) for the latest news and updates on cybersecurity.


¹Global Cyberattacks Continue to Rise with Africa and APAC Suffering Most, Check Point Blog. April 27, 2023.

²Cyber security breaches survey 2024: education institutions annex, The United Kingdom Department for Science, Innovation & Technology. April 9, 2024

³Scammers hide harmful links in QR codes to steal your information, Federal Trade Commission (Alvaro Puig), December 6, 2023.

Methodology: Snapshot and cover stat data represent telemetry from Microsoft Defender for Office 365 showing how a QR code phishing attack was disrupted by image detection technology and how Security Operations teams can respond to this threat. Platforms like Microsoft Entra provided anonymized data on threat activity, such as malicious email accounts, phishing emails, and attacker movement within networks. Additional insights are from the 78 trillion daily security signals processed by Microsoft each day, including the cloud, endpoints, the intelligent edge, and telemetry from Microsoft platforms and services including Microsoft Defender. Microsoft categorizes threat actors into five key groups: influence operations; groups in development; and nation-state, financially motivated, and private sector offensive actors. The new threat actors naming taxonomy aligns with the theme of weather.  

© 2024 Microsoft Corporation. All rights reserved. Cyber Signals is for informational purposes only. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS DOCUMENT. This document is provided “as is.” Information and views expressed in this document, including URL and other Internet website references, may change without notice. You bear the risk of using it. This document does not provide you with any legal rights to any intellectual property in any Microsoft product. 

The post ​​Cyber Signals Issue 8 | Education under siege: How cybercriminals target our schools​​ appeared first on Microsoft Security Blog.

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File hosting services misused for identity phishing http://approjects.co.za/?big=en-us/security/blog/2024/10/08/file-hosting-services-misused-for-identity-phishing/ Tue, 08 Oct 2024 16:00:00 +0000 Since mid-April 2024, Microsoft has observed an increase in defense evasion tactics used in campaigns abusing file hosting services like SharePoint, OneDrive, and Dropbox. These campaigns use sophisticated techniques to perform social engineering, evade detection, and compromise identities, and include business email compromise (BEC) attacks.

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Microsoft has observed campaigns misusing legitimate file hosting services increasingly use defense evasion tactics involving files with restricted access and view-only restrictions. While these campaigns are generic and opportunistic in nature, they involve sophisticated techniques to perform social engineering, evade detection, and expand threat actor reach to other accounts and tenants. These campaigns are intended to compromise identities and devices, and most commonly lead to business email compromise (BEC) attacks to propagate campaigns, among other impacts such as financial fraud, data exfiltration, and lateral movement to endpoints.

Legitimate hosting services, such as SharePoint, OneDrive, and Dropbox, are widely used by organizations for storing, sharing, and collaborating on files. However, the widespread use of such services also makes them attractive targets for threat actors, who exploit the trust and familiarity associated with these services to deliver malicious files and links, often avoiding detection by traditional security measures.

Importantly, Microsoft takes action against malicious users violating the Microsoft Services Agreement in how they use apps like SharePoint and OneDrive. To help protect enterprise accounts from compromise, by default both Microsoft 365 and Office 365 support multi-factor authentication (MFA) and passwordless sign-in. Consumers can also go passwordless with their Microsoft account. Because security is a team sport, Microsoft also works with third parties like Dropbox to share threat intelligence and protect mutual customers and the wider community.

In this blog, we discuss the typical attack chain used in campaigns misusing file hosting services and detail the recently observed tactics, techniques, and procedures (TTPs), including the increasing use of certain defense evasion tactics. To help defenders protect their identities and data, we also share mitigation guidance to help reduce the impact of this threat, and detection details and hunting queries to locate potential misuse of file hosting services and related threat actor activities. By understanding these evolving threats and implementing the recommended mitigations, organizations can better protect themselves against these sophisticated campaigns and safeguard digital assets.

Attack overview

Phishing campaigns exploiting legitimate file hosting services have been trending throughout the last few years, especially due to the relative ease of the technique. The files are delivered through different approaches, including email and email attachments like PDFs, OneNote, and Word files, with the intent of compromising identities or devices. These campaigns are different from traditional phishing attacks because of the sophisticated defense evasion techniques used.

Since mid-April 2024, we observed threat actors increasingly use these tactics aimed at circumventing defense mechanisms:

  • Files with restricted access: The files sent through the phishing emails are configured to be accessible solely to the designated recipient. This requires the recipient to be signed in to the file-sharing service—be it Dropbox, OneDrive, or SharePoint—or to re-authenticate by entering their email address along with a one-time password (OTP) received through a notification service.
  • Files with view-only restrictions: To bypass analysis by email detonation systems, the files shared in these phishing attacks are set to ‘view-only’ mode, disabling the ability to download and consequently, the detection of embedded URLs within the file.

An example attack chain is provided below, depicting the updated defense evasion techniques being used across stages 4, 5, and 6:

Attack chain diagram. Step 1, attacker compromises a user of a trusted vendor via password spray/AiTM​ attack. Step 2, attacker replays stolen token a few hours later to sign into the user’s file hosting app​. Step 3, attacker creates a malicious file in the compromised user’s file hosting app​. Step 4, attacker shares the file with restrictions to a group of targeted recipients. Step 5, targeted recipient accesses the automated email notification with the suspicious file. Step 6, recipient is required to re-authenticate before accessing the shared file​. Step 7, recipient accesses the malicious shared file link​, directing to an AiTM page. Step 8, recipient submits password and MFA, compromising the user’s session token. Lastly, step 9, file shared on the compromised user’s file hosting app is used for further AiTM and BEC attack​s.
Figure 1. Example attack chain

Initial access

The attack typically begins with the compromise of a user within a trusted vendor. After compromising the trusted vendor, the threat actor hosts a file on the vendor’s file hosting service, which is then shared with a target organization. This misuse of legitimate file hosting services is particularly effective because recipients are more likely to trust emails from known vendors, allowing threat actors to bypass security measures and compromise identities. Often, users from trusted vendors are added to allow lists through policies set by the organization on Exchange Online products, enabling phishing emails to be successfully delivered.

While file names observed in these campaigns also included the recipients, the hosted files typically follow these patterns:

  • Familiar topics based on existing conversations
    • For example, if the two organizations have prior interactions related to an audit, the shared files could be named “Audit Report 2024”.
  • Familiar topics based on current context
    • If the attack has not originated from a trusted vendor, the threat actor often impersonates administrators or help desk or IT support personnel in the sender display name and uses a file name such as “IT Filing Support 2024”, “Forms related to Tax submission”, or “Troubleshooting guidelines”.
  • Topics based on urgency
    • Another common technique observed by the threat actors creating these files is that they create a sense of urgency with the file names like “Urgent:Attention Required” and “Compromised Password Reset”.

Defense evasion techniques

Once the threat actor shares the files on the file hosting service with the intended users, the file hosting service sends the target user an automated email notification with a link to access the file securely. This email is not a phishing email but a notification for the user about the sharing action. In scenarios involving SharePoint or OneDrive, the file is shared from the user’s context, with the compromised user’s email address as the sender. However, in the Dropbox scenario, the file is shared from no-reply@dropbox[.]com. The files are shared through automated notification emails with the subject: “<User> shared <document> with you”. To evade detections, the threat actor deploys the following additional techniques:

  • Only the intended recipient can access the file
    • The intended recipient needs to re-authenticate before accessing the file
    • The file is accessible only for a limited time window
  • The PDF shared in the file cannot be downloaded

These techniques make detonation and analysis of the sample with the malicious link almost impossible since they are restricted.

Identity compromise

When the targeted user accesses the shared file, the user is prompted to verify their identity by providing their email address:

Screenshot of the SharePoint identity verification page
Figure 2. Screenshot of SharePoint identity verification

Next, an OTP is sent from no-reply@notify.microsoft[.]com. Once the OTP is submitted, the user is successfully authorized and can view a document, often masquerading as a preview, with a malicious link, which is another lure to make the targeted user click the “View my message” access link.

graphical user interface, application
Figure 3. Final landing page post authorization

This link redirects the user to an adversary-in-the-middle (AiTM) phishing page, where the user is prompted to provide the password and complete multifactor authentication (MFA). The compromised token can then be leveraged by the threat actor to perform the second stage BEC attack and continue the campaign.

Microsoft recommends the following mitigations to reduce the impact of this threat:

Appendix

Microsoft Defender XDR detections

Microsoft Defender XDR raises the following alerts by combining Microsoft Defender for Office 365 URL click and Microsoft Entra ID Protection risky sign-ins signal.

  • Risky sign-in after clicking a possible AiTM phishing URL
  • User compromised through session cookie hijack
  • User compromised in a known AiTM phishing kit

Hunting queries

Microsoft Defender XDR 

The file sharing events related to the activity in this blog post can be audited through the CloudAppEvents telemetry. Microsoft Defender XDR customers can run the following query to find related activity in their networks: 

Automated email notifications and suspicious sign-in activity

By correlating the email from the Microsoft notification service or Dropbox automated notification service with a suspicious sign-in activity, we can identify compromises, especially from securely shared SharePoint or Dropbox files.

let usersWithSuspiciousEmails = EmailEvents
    | where SenderFromAddress in ("no-reply@notify.microsoft.com", "no-reply@dropbox.com") or InternetMessageId startswith "<OneTimePasscode"
    | where isnotempty(RecipientObjectId)
    | distinct RecipientObjectId;
AADSignInEventsBeta
| where AccountObjectId in (usersWithSuspiciousEmails)
| where RiskLevelDuringSignIn == 100

Files share contents and suspicious sign-in activity

In the majority of the campaigns, the file name involves a sense of urgency or content related to finance or credential updates. By correlating the file share emails with suspicious sign-ins, compromises can be detected. (For example: Alex shared “Password Reset Mandatory.pdf” with you). Since these are observed as campaigns, validating that the same file has been shared with multiple users in the organization can support the detection.

let usersWithSuspiciousEmails = EmailEvents
    | where Subject has_all ("shared", "with you")
    | where Subject has_any ("payment", "invoice", "urgent", "mandatory", "Payoff", "Wire", "Confirmation", "password")
    | where isnotempty(RecipientObjectId)
    | summarize RecipientCount = dcount(RecipientObjectId), RecipientList = make_set(RecipientObjectId) by Subject
    | where RecipientCount >= 10
    | mv-expand RecipientList to typeof(string)
    | distinct RecipientList;
AADSignInEventsBeta
| where AccountObjectId in (usersWithSuspiciousEmails)
| where RiskLevelDuringSignIn == 100

BEC: File sharing tactics based on the file hosting service used

To initiate the file sharing activity, these campaigns commonly use certain action types depending on the file hosting service being leveraged. Below are the action types from the audit logs recorded for the file sharing events. These action types can be used to hunt for activities related to these campaigns by replacing the action type for its respective application in the queries below this table.

ApplicationAction typeDescription
OneDrive/
SharePoint
AnonymousLinkCreatedLink created for the document, anyone with the link can access, prevalence is rare since mid-April 2024
SharingLinkCreatedLink created for the document, accessible for everyone, prevalence is rare since mid-April 2024
AddedToSharingLinkComplete list of users with whom the file is shared is available in this event
SecureLinkCreatedLink created for the document, specifically can be accessed only by a group of users. List will be available in the AddedToSecureLink Event
AddedToSecureLinkComplete list of users with whom the file is securely shared is available in this event
DropboxCreated shared linkA link for a file to be shared with external user created
Added shared folder to own DropboxA shared folder was added to the user’s Dropbox account
Added users and/or groups to shared file/folderThese action types include the list of external users with whom the files have been shared.
Changed the audience of the shared link
Invited user to Dropbox and added them to shared file/folder

OneDrive or SharePoint: The following query highlights that a specific file has been shared by a user with multiple participants. Correlating this activity with suspicious sign-in attempts preceding this can help identify lateral movements and BEC attacks.

let securelinkCreated = CloudAppEvents
    | where ActionType == "SecureLinkCreated"
    | project FileCreatedTime = Timestamp, AccountObjectId, ObjectName;
let filesCreated = securelinkCreated
    | where isnotempty(ObjectName)
    | distinct tostring(ObjectName);
CloudAppEvents
| where ActionType == "AddedToSecureLink"
| where Application in ("Microsoft SharePoint Online", "Microsoft OneDrive for Business")
| extend FileShared = tostring(RawEventData.ObjectId)
| where FileShared in (filesCreated)
| extend UserSharedWith = tostring(RawEventData.TargetUserOrGroupName)
| extend TypeofUserSharedWith = RawEventData.TargetUserOrGroupType
| where TypeofUserSharedWith == "Guest"
| where isnotempty(FileShared) and isnotempty(UserSharedWith)
| join kind=inner securelinkCreated on $left.FileShared==$right.ObjectName
// Secure file created recently (in the last 1day)
| where (Timestamp - FileCreatedTime) between (1d .. 0h)
| summarize NumofUsersSharedWith = dcount(UserSharedWith) by FileShared
| where NumofUsersSharedWith >= 20

Dropbox: The following query highlights that a file hosted on Dropbox has been shared with multiple participants.

CloudAppEvents
| where ActionType in ("Added users and/or groups to shared file/folder", "Invited user to Dropbox and added them to shared file/folder")
| where Application == "Dropbox"
| where ObjectType == "File"
| extend FileShared = tostring(ObjectName)
| where isnotempty(FileShared)
| mv-expand ActivityObjects
| where ActivityObjects.Type == "Account" and ActivityObjects.Role == "To"
| extend SharedBy = AccountId
| extend UserSharedWith = tostring(ActivityObjects.Name)
| summarize dcount(UserSharedWith) by FileShared, AccountObjectId
| where dcount_UserSharedWith >= 20

Microsoft Sentinel

Microsoft Sentinel customers can use the resources below to find related activities similar to those described in this post:

The following query identifies files with specific keywords that attackers might use in this campaign that have been shared through OneDrive or SharePoint using a Secure Link and accessed by over 10 unique users. It captures crucial details like target users, client IP addresses, timestamps, and file URLs to aid in detecting potential attacks:

let OperationName = dynamic(['SecureLinkCreated', 'AddedToSecureLink']);
OfficeActivity
| where Operation in (OperationName)
| where OfficeWorkload in ('OneDrive', 'SharePoint')
| where SourceFileName has_any ("payment", "invoice", "urgent", "mandatory", "Payoff", "Wire", "Confirmation", "password", "paycheck", "bank statement", "bank details", "closing", "funds", "bank account", "account details", "remittance", "deposit", "Reset")
| summarize CountOfShares = dcount(TargetUserOrGroupName), 
            make_list(TargetUserOrGroupName), 
            make_list(ClientIP), 
            make_list(TimeGenerated), 
            make_list(SourceRelativeUrl) by SourceFileName, OfficeWorkload
| where CountOfShares > 10

Considering that the attacker compromises users through AiTM,  possible AiTM phishing attempts can be detected through the below rule:

In addition, customers can also use the following identity-focused queries to detect and investigate anomalous sign-in events that may be indicative of a compromised user identity being accessed by a threat actor:

Learn more

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

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

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

The post File hosting services misused for identity phishing appeared first on Microsoft Security Blog.

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Threat actors misusing Quick Assist in social engineering attacks leading to ransomware http://approjects.co.za/?big=en-us/security/blog/2024/05/15/threat-actors-misusing-quick-assist-in-social-engineering-attacks-leading-to-ransomware/ Wed, 15 May 2024 16:00:00 +0000 Microsoft Threat Intelligence has observed Storm-1811 misusing the client management tool Quick Assist to target users in social engineering attacks that lead to malware like Qakbot followed by Black Basta ransomware deployment.

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June 2024 update: At the end of May 2024, Microsoft Threat Intelligence observed Storm-1811 using Microsoft Teams as another vector to contact target users. Microsoft assesses that the threat actor uses Teams to send messages and initiate calls in an attempt to impersonate IT or help desk personnel. This activity leads to Quick Assist misuse, followed by credential theft using EvilProxy, execution of batch scripts, and use of SystemBC for persistence and command and control.

Since mid-April 2024, Microsoft Threat Intelligence has observed the threat actor Storm-1811 misusing the client management tool Quick Assist to target users in social engineering attacks. Storm-1811 is a financially motivated cybercriminal group known to deploy Black Basta ransomware. The observed activity begins with impersonation through voice phishing (vishing), followed by delivery of malicious tools, including remote monitoring and management (RMM) tools like ScreenConnect and NetSupport Manager, malware like Qakbot, Cobalt Strike, and ultimately Black Basta ransomware.

MITIGATE THIS THREAT

Get recommendations

Quick Assist is an application that enables a user to share their Windows or macOS device with another person over a remote connection. This enables the connecting user to remotely connect to the receiving user’s device and view its display, make annotations, or take full control, typically for troubleshooting. Threat actors misuse Quick Assist features to perform social engineering attacks by pretending, for example, to be a trusted contact like Microsoft technical support or an IT professional from the target user’s company to gain initial access to a target device.

RANSOMWARE AS A SERVICE

Protect users and orgs

In addition to protecting customers from observed malicious activity, Microsoft is investigating the use of Quick Assist in these attacks and is working on improving the transparency and trust between helpers and sharers, and incorporating warning messages in Quick Assist to alert users about possible tech support scams. Microsoft Defender for Endpoint detects components of activity originating from Quick Assist sessions as well as follow-on activity, and Microsoft Defender Antivirus detects the malware components associated with this activity.

TECH SUPPORT SCAMS

Report scam

Organizations can also reduce the risk of attacks by blocking or uninstalling Quick Assist and other remote management tools if the tools are not in use in their environment. Quick Assist is installed by default on devices running Windows 11. Additionally, tech support scams are an industry-wide issue where scammers use scare tactics to trick users into unnecessary technical support services. Educating users on how to recognize such scams can significantly reduce the impact of social engineering attacks

Social engineering

One of the social engineering techniques used by threat actors to obtain initial access to target devices using Quick Assist is through vishing attacks. Vishing attacks are a form of social engineering that involves callers luring targets into revealing sensitive information under false pretenses or tricking targets into carrying out actions on behalf of the caller.

For example, threat actors might attempt to impersonate IT or help desk personnel, pretending to conduct generic fixes on a device. In other cases, threat actors initiate link listing attacks – a type of email bombing attack, where threat actors sign up targeted emails to multiple email subscription services to flood email addresses indirectly with subscribed content. Following the email flood, the threat actor impersonates IT support through phone calls to the target user, claiming to offer assistance in remediating the spam issue.

At the end of May 2024, Microsoft observed Storm-1811 using Microsoft Teams to send messages to and call target users. Tenants created by the threat actor are used to impersonate help desk personnel with names displayed as “Help Desk”, “Help Desk IT”, “Help Desk Support”, and “IT Support”. Microsoft has taken action to mitigate this by suspending identified accounts and tenants associated with inauthentic behavior. Apply security best practices for Microsoft Teams to safeguard Teams users.

During the call, the threat actor persuades the user to grant them access to their device through Quick Assist. The target user only needs to press CTRL + Windows + Q and enter the security code provided by the threat actor, as shown in the figure below.

Screenshot of Quick Assist prompt to enter security code
Figure 1. Quick Assist prompt to enter security code

After the target enters the security code, they receive a dialog box asking for permission to allow screen sharing. Selecting Allow shares the user’s screen with the actor.

Screenshot of Quick Assist dialog box asking permission to allow screen sharing
Figure 2. Quick Assist dialog box asking permission to allow screen sharing

Once in the session, the threat actor can select Request Control, which if approved by the target, grants the actor full control of the target’s device.

Screenshot of Quick Assist dialog box asking permission to allow control
Figure 3. Quick Assist dialog box asking permission to allow control

Follow-on activity leading to Black Basta ransomware

Once the user allows access and control, the threat actor runs a scripted cURL command to download a series of batch files or ZIP files used to deliver malicious payloads. Some of the batch scripts observed reference installing fake spam filter updates requiring the targets to provide sign-in credentials. In several cases, Microsoft Threat Intelligence identified such activity leading to the download of Qakbot, RMM tools like ScreenConnect and NetSupport Manager, and Cobalt Strike.

Screenshot of two lines of cURL commands
Figure 4. Examples of cURL commands to download batch files and ZIP files

Qakbot has been used over the years as a remote access vector to deliver additional malicious payloads that led to ransomware deployment. In this recent activity, Qakbot was used to deliver a Cobalt Strike Beacon attributed to Storm-1811.

ScreenConnect was used to establish persistence and conduct lateral movement within the compromised environment. NetSupport Manager is a remote access tool used by multiple threat actors to maintain control over compromised devices. An attacker might use this tool to remotely access the device, download and install additional malware, and launch arbitrary commands.

The mentioned RMM tools are commonly used by threat actors because of their extensive capabilities and ability to blend in with the environment. In some cases, the actors leveraged the OpenSSH tunneling tool to establish a secure shell (SSH) tunnel for persistence. 

After the threat actor installs the initial tooling and the phone call is concluded, Storm-1811 leverages their access and performs further hands-on-keyboard activities such as domain enumeration and lateral movement.

In cases where Storm-1811 relies on Teams messages followed by phone calls and remote access through Quick Assist, the threat actor uses BITSAdmin to download batch files and ZIP files from a malicious site, for example antispam3[.]com. Storm-1811 also provides the target user with malicious links that redirect the user to an EvilProxy phishing site to input credentials. EvilProxy is an adversary-in-the-middle (AiTM) phishing kit used to capture passwords, hijack a user’s sign-in session, and skip the authentication process. Storm-1811 was also observed deploying SystemBC, a post-compromise commodity remote access trojan (RAT) and proxy tool typically used to establish command-and-control communication, establish persistence in a compromised environment, and deploy follow-on malware, notably ransomware.

In several cases, Storm-1811 uses PsExec to deploy Black Basta ransomware throughout the network. Black Basta is a closed ransomware offering (exclusive and not openly marketed like ransomware as a service) distributed by a small number of threat actors who typically rely on other threat actors for initial access, malicious infrastructure, and malware development. Since Black Basta first appeared in April 2022, Black Basta attackers have deployed the ransomware after receiving access from Qakbot and other malware distributors, highlighting the need for organizations to focus on attack stages prior to ransomware deployment to reduce the threat. In the next sections, we share recommendations for improving defenses against this threat, including best practices when using Quick Assist and mitigations for reducing the impact of Black Basta and other ransomware.

Recommendations

Microsoft recommends the following best practices to protect users and organizations from attacks and threat actors that misuse Quick Assist:

  • Consider blocking or uninstalling Quick Assist and other remote monitoring and management tools if these tools are not in use in your environment. If your organization utilizes another remote support tool such as Remote Help, block or remove Quick Assist as a best practice. Remote Help is part of the Microsoft Intune Suite and provides authentication and security controls for helpdesk connections.
  • Educate users about protecting themselves from tech support scams. Tech support scams are an industry-wide issue where scammers use scary tactics to trick users into unnecessary technical support services.
  • Only allow a helper to connect to your device using Quick Assist if you initiated the interaction by contacting Microsoft Support or your IT support staff directly. Don’t provide access to anyone claiming to have an urgent need to access your device.
  • If you suspect that the person connecting to your device is conducting malicious activity, disconnect from the session immediately and report to your local authorities and/or any relevant IT members within your organization.
  • Users who have been affected by a tech support scam can also use the Microsoft technical support scam form to report it.

Microsoft recommends the following mitigations to reduce the impact of this threat:

  • Educate users about protecting personal and business information in social media, filtering unsolicited communication, identifying lure links in phishing emails, and reporting reconnaissance attempts and other suspicious activity.
  • Educate users about preventing malware infections, such as ignoring or deleting unsolicited and unexpected emails or attachments sent through instant messaging applications or social networks as well as suspicious phone calls.
  • Invest in advanced anti-phishing solutions that monitor incoming emails and visited websites. Microsoft Defender for Office 365 brings together incident and alert management across email, devices, and identities, centralizing investigations for email-based threats.
  • Educate Microsoft Teams users to verify ‘External’ tagging on communication attempts from external entities, be cautious about what they share, and never share their account information or authorize sign-in requests over chat.
  • Implement Conditional Access authentication strength to require phishing-resistant authentication for employees and external users for critical apps.
  • Apply Microsoft’s security best practices for Microsoft Teams to safeguard Teams users.
  • Turn on cloud-delivered protection in Microsoft Defender Antivirus or the equivalent for your antivirus product to cover rapidly evolving attacker tools and techniques. Cloud-based machine learning protections block a huge majority of new and unknown variants.
  • Enable network protection to prevent applications or users from accessing malicious domains and other malicious content on the internet.
  • Turn on tamper protection features to prevent attackers from stopping security services.
  • Enable 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.
  • Refer to Microsoft’s human-operated ransomware overview for general hardening recommendations against ransomware attacks.

Microsoft Defender XDR customers can turn on attack surface reduction rules to prevent common attack techniques:

Detection details

Microsoft Defender Antivirus 

Microsoft Defender Antivirus detects Qakbot downloaders, implants, and behavior as the following malware:

Black Basta threat components are detected as the following:

Microsoft Defender Antivirus detects Beacon running on a victim process as the following:

Additional Cobalt Strike components are detected as the following:

SystemBC components are detected as:

Microsoft Defender for Endpoint

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

  • Suspicious activity using Quick Assist

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

  • Suspicious curl behavior
  • Suspicious bitsadmin activity
  • Suspicious file creation by BITSAdmin tool
  • A file or network connection related to a ransomware-linked emerging threat activity group detected —This alert captures Storm-1811 activity
  • Ransomware-linked emerging threat activity group Storm-0303 detected — This alert captures some Qakbot distributor activity
  • Possible Qakbot activity
  • Possible NetSupport Manager activity
  • Possibly malicious use of proxy or tunneling tool
  • Suspicious usage of remote management software
  • Ongoing hands-on-keyboard attacker activity detected (Cobalt Strike)
  • Human-operated attack using Cobalt Strike
  • Human-operated attack implant tool detected
  • Ransomware behavior detected in the file system

Indicators of compromise

Domain names:

  • upd7a[.]com
  • upd7[.]com
  • upd9[.]com
  • upd5[.]pro
  • antispam3[.]com
  • antispam2[.]com

SHA-256:

  • 71d50b74f81d27feefbc2bc0f631b0ed7fcdf88b1abbd6d104e66638993786f8
  • 0f9156f91c387e7781603ed716dcdc3f5342ece96e155115708b1662b0f9b4d0
  • 1ad05a4a849d7ed09e2efb38f5424523651baf3326b5f95e05f6726f564ccc30
  • 93058bd5fe5f046e298e1d3655274ae4c08f07a8b6876e61629ae4a0b510a2f7
  • 1cb1864314262e71de1565e198193877ef83e98823a7da81eb3d59894b5a4cfb

ScreenConnect relay:

  • instance-olqdnn-relay.screenconnect[.]com

NetSupport C2:

  • greekpool[.]com

Cobalt Strike Beacon C2:

  • zziveastnews[.]com
  • realsepnews[.]com

Advanced hunting 

Microsoft Defender XDR

To locate possible malicious activity, run the following query in the Microsoft Defender portal:

This query looks for possible email bombing activity:

EmailEvents
| where EmailDirection == "Inbound"
| make-series Emailcount = count()
              on Timestamp step 1h by RecipientObjectId
| extend (Anomalies, AnomalyScore, ExpectedEmails) = series_decompose_anomalies(Emailcount)
| mv-expand Emailcount, Anomalies, AnomalyScore, ExpectedEmails to typeof(double), Timestamp
| where Anomalies != 0
| where AnomalyScore >= 10

This query looks for possible Teams phishing activity.

let suspiciousUpns = DeviceProcessEvents
| where DeviceId == "alertedMachine"
| where isnotempty(InitiatingProcessAccountUpn)
| project InitiatingProcessAccountUpn;
CloudAppEvents
| where Application == "Microsoft Teams"
| where ActionType == "ChatCreated"
| where isempty(AccountObjectId)
| where RawEventData.ParticipantInfo.HasForeignTenantUsers == true
| where RawEventData.CommunicationType == "OneonOne"
| where RawEventData.ParticipantInfo.HasGuestUsers == false
| where RawEventData.ParticipantInfo.HasOtherGuestUsers == false
| where RawEventData.Members[0].DisplayName in ("Microsoft  Security", "Help Desk", "Help Desk Team", "Help Desk IT", "Microsoft Security", "office")
| where AccountId has "@"
| extend TargetUPN = tolower(tostring(RawEventData.Members[1].UPN))
| where TargetUPN in (suspiciousUpns)

Microsoft Sentinel

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

Microsoft Sentinel also has a range of hunting queries available in Sentinel GitHub repo or as part of Sentinel solutions that customers can use to detect the activity detailed in this blog in addition to Microsoft Defender detections. These hunting queries include the following:

Qakbot:

Cobalt Strike:

References

Learn more

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

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

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

The post Threat actors misusing Quick Assist in social engineering attacks leading to ransomware appeared first on Microsoft Security Blog.

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Staying ahead of threat actors in the age of AI http://approjects.co.za/?big=en-us/security/blog/2024/02/14/staying-ahead-of-threat-actors-in-the-age-of-ai/ Wed, 14 Feb 2024 12:00:00 +0000 Microsoft, in collaboration with OpenAI, is publishing research on emerging threats in the age of AI, focusing on identified activity associated with known threat actors Forest Blizzard, Emerald Sleet, Crimson Sandstorm, and others. The observed activity includes prompt-injections, attempted misuse of large language models (LLM), and fraud.

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

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

A principled approach to detecting and blocking threat actors

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

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

These principles include:   

  • Identification and action against malicious threat actors’ use: Upon detection of the use of any Microsoft AI application programming interfaces (APIs), services, or systems by an identified malicious threat actor, including nation-state APT or APM, or the cybercrime syndicates we track, Microsoft will take appropriate action to disrupt their activities, such as disabling the accounts used, terminating services, or limiting access to resources.           
  • Notification to other AI service providers: When we detect a threat actor’s use of another service provider’s AI, AI APIs, services, and/or systems, Microsoft will promptly notify the service provider and share relevant data. This enables the service provider to independently verify our findings and take action in accordance with their own policies.
  • Collaboration with other stakeholders: Microsoft will collaborate with other stakeholders to regularly exchange information about detected threat actors’ use of AI. This collaboration aims to promote collective, consistent, and effective responses to ecosystem-wide risks.
  • Transparency: As part of our ongoing efforts to advance responsible use of AI, Microsoft will inform the public and stakeholders about actions taken under these threat actor principles, including the nature and extent of threat actors’ use of AI detected within our systems and the measures taken against them, as appropriate.

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

Microsoft and OpenAI’s complementary defenses protect AI platforms

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

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

Summary of Microsoft and OpenAI’s findings and threat intelligence

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

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

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

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

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

Forest Blizzard 

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

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

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

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

Emerald Sleet

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

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

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

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

Crimson Sandstorm

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

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

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

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

Charcoal Typhoon

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

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

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

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

Salmon Typhoon

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

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

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

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

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

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

Appendix: LLM-themed TTPs

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

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

Learn more

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

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

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

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

The post Staying ahead of threat actors in the age of AI appeared first on Microsoft Security Blog.

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New TTPs observed in Mint Sandstorm campaign targeting high-profile individuals at universities and research orgs http://approjects.co.za/?big=en-us/security/blog/2024/01/17/new-ttps-observed-in-mint-sandstorm-campaign-targeting-high-profile-individuals-at-universities-and-research-orgs/ Wed, 17 Jan 2024 17:00:00 +0000 Since November 2023, Microsoft has observed a distinct subset of Mint Sandstorm (PHOSPHORUS) targeting high-profile individuals working on Middle Eastern affairs at universities and research organizations in Belgium, France, Gaza, Israel, the United Kingdom, and the United States. In this campaign, the threat actor used bespoke phishing lures in an attempt to socially engineer targets into downloading malicious files.

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Since November 2023, Microsoft has observed a distinct subset of Mint Sandstorm (PHOSPHORUS) targeting high-profile individuals working on Middle Eastern affairs at universities and research organizations in Belgium, France, Gaza, Israel, the United Kingdom, and the United States. In this campaign, Mint Sandstorm used bespoke phishing lures in an attempt to socially engineer targets into downloading malicious files. In a handful of cases, Microsoft observed new post-intrusion tradecraft including the use of a new, custom backdoor called MediaPl.

Operators associated with this subgroup of Mint Sandstorm are patient and highly skilled social engineers whose tradecraft lacks many of the hallmarks that allow users to quickly identify phishing emails. In some instances of this campaign, this subgroup also used legitimate but compromised accounts to send phishing lures. Additionally, Mint Sandstorm continues to improve and modify the tooling used in targets’ environments, activity that might help the group persist in a compromised environment and better evade detection.

Mint Sandstorm (which overlaps with the threat actor tracked by other researchers as APT35 and Charming Kitten) is a composite name used to describe several subgroups of activity with ties to the Islamic Revolutionary Guard Corps (IRGC), an intelligence arm of Iran’s military. Microsoft attributes the activity detailed in this blog to a technically and operationally mature subgroup of Mint Sandstorm that specializes in gaining access to and stealing sensitive information from high-value targets. This group is known to conduct resource-intensive social engineering campaigns that target journalists, researchers, professors, or other individuals with insights or perspective on security and policy issues of interest to Tehran.

These individuals, who work with or who have the potential to influence the intelligence and policy communities, are attractive targets for adversaries seeking to collect intelligence for the states that sponsor their activity, such as the Islamic Republic of Iran. Based on the identities of the targets observed in this campaign and the use of lures related to the Israel-Hamas war, it’s possible this campaign is an attempt to gather perspectives on events related to the war from individuals across the ideological spectrum.

In this blog, we share our analysis of the new Mint Sandstorm tradecraft and provide detection, hunting, and protection information. Organizations can also use the mitigations included in this blog to harden their attack surfaces against the tradecraft observed in this and other Mint Sandstorm campaigns. These mitigations are high-value measures that are effective ways to defend organizations from multiple threats, including Mint Sandstorm, and are useful to any organization regardless of their threat model.

New Mint Sandstorm tradecraft

Microsoft observed new tactics, techniques, and procedures (TTPs) in this Mint Sandstorm campaign, notably the use of legitimate but compromised email accounts to send phishing lures, use of the Client for URL (curl) command to connect to Mint Sandstorm’s command-and-control (C2) server and download malicious files, and delivery of a new custom backdoor, MediaPl.

Social engineering

In this campaign, Mint Sandstorm masqueraded as high-profile individuals including as a journalist at a reputable news outlet. In some cases, the threat actor used an email address spoofed to resemble a personal email account belonging to the journalist they sought to impersonate and sent benign emails to targets requesting their input on an article about the Israel-Hamas war. In other cases, Mint Sandstorm used legitimate but compromised email accounts belonging to the individuals they sought to impersonate. Initial email messages did not contain any malicious content.

This tradecraft, namely the impersonation of a known individual, the use of highly bespoke phishing lures, and the use of wholly benign messages in the initial stages of the campaign, is likely an attempt to build rapport with targets and establish a level of trust before attempting to deliver malicious content to targets. Additionally, it’s likely that the use of legitimate but compromised email accounts, observed in a subset of this campaign, further bolstered Mint Sandstorm’s credibility, and might have played a role in the success of this campaign.

Delivery

If targets agreed to review the article or document referenced in the initial email, Mint Sandstorm followed up with an email containing a link to a malicious domain. In this campaign, follow up messages directed targets to sites such as cloud-document-edit[.]onrender[.]com, a domain hosting a RAR archive (.rar) file that purported to contain the draft document targets were asked to review. If opened, this .rar file decompressed into a double extension file (.pdf.lnk) with the same name. When launched, the .pdf.lnk file ran a curl command to retrieve a series of malicious files from attacker-controlled subdomains of glitch[.]me and supabase[.]co.

Microsoft observed multiple files downloaded to targets’ devices in this campaign, notably several .vbs scripts. In several instances, Microsoft observed a renamed version of NirCmd, a legitimate command line tool that allows a user to carry out a number of actions on a device without displaying a user interface, on a target’s device.

Persistence

In some cases, the threat actor used a malicious file, Persistence.vbs, to persist in targets’ environments. When run, Persistence.vbs added a file, typically named a.vbs, to the CurrentVersion\Run registry key. In other cases, Mint Sandstorm created a scheduled task to reach out to an attacker-controlled supabase[.]co domain and download a .txt file.

Intrusion chain leading to backdoors observed in the ongoing Mint Sandstorm campaign
Figure 1. Intrusion chain leading to backdoors observed in the ongoing Mint Sandstorm campaign

Collection

Activity observed in this campaign suggests that Mint Sandstorm wrote activity from targets’ devices to a series of text files, notably one named documentLoger.txt.

In addition to the activity detailed above, in some cases, Mint Sandstorm dropped MischiefTut or MediaPl, custom backdoors.

MediaPl backdoor

MediaPl is a custom backdoor capable of sending encrypted communications to its C2 server. MediaPl is configured to masquerade as Windows Media Player, an application used to store and play audio and video files. To this end, Mint Sandstorm typically drops this file in C:\\Users\\[REDACTED] \\AppData\\Local\\Microsoft\\Media Player\\MediaPl.dll. When MediaPl.dll is run with the path of an image file provided as an argument, it launches the image in Windows Photo application and also parses the image for C2 information. Communications to and from MediaPl’s C2 server are AES CBC encrypted and Base64 encoded. As of this writing, MediaPl can terminate itself, can pause and retry communications with its C2 server, and launch command(s) it has received from the C2 using the _popen function.

MischiefTut

MischiefTut is a custom backdoor implemented in PowerShell with a set of basic capabilities. MischiefTut can run reconnaissance commands, write outputs to a text file and, ostensibly, send outputs back to adversary-controlled infrastructure. MischiefTut can also be used to download additional tools on a compromised system.

Implications

The ability to obtain and maintain remote access to a target’s system can enable Mint Sandstorm to conduct a range of activities that can adversely impact the confidentiality of a system. Compromise of a targeted system can also create legal and reputational risks for organizations affected by this campaign. In light of the patience, resources, and skills observed in campaigns attributed to this subgroup of Mint Sandstorm, Microsoft continues to update and augment our detection capabilities to help customers defend against this threat.

Recommendations

Microsoft recommends the following mitigations to reduce the impact of activity associated with recent Mint Sandstorm campaigns.

  • Use the Attack Simulator in Microsoft Defender for Office 365 to organize realistic, yet safe, simulated phishing and password attack campaigns in your organization by training end-users against clicking URLs in unsolicited messages and disclosing their credentials. Training should include checking for poor spelling and grammar in phishing emails or the application’s consent screen as well as spoofed app names, logos and domain URLs appearing to originate from legitimate applications or companies. Note that Attack Simulator testing only supports phishing emails containing links at this time.
  • Encourage users to use Microsoft Edge and other web browsers that support SmartScreen, which identifies and blocks malicious websites, including phishing sites, scam sites, and sites that contain exploits and host malware. Turn on network protection to block connections to malicious domains and IP addresses.
  • Turn on cloud-delivered protection in Microsoft Defender Antivirus or the equivalent for your antivirus product to cover rapidly evolving attacker tools and techniques. Cloud-based machine learning protections block a majority of new and unknown variants.

Microsoft Defender XDR customers can also turn on attack surface reduction rules to harden their environments against techniques used by this Mint Sandstorm subgroup. These rules, which can be configured by all Microsoft Defender Antivirus customers and not just those using the EDR solution, offer significant protection against the tradecraft discussed in this report.

Detection details

Microsoft Defender Antivirus

Microsoft Defender Antivirus detects activity associated with the MediaPl backdoor as the following malware:

Microsoft Defender Antivirus detects activity associated with the MischiefTut backdoor as the following malware:

Microsoft Defender for Endpoint

Microsoft Defender for Endpoint provides customers with detections and alerts. Alerts with the following titles in the Security Center can indicate threat activity related to Mint Sandstorm.

  • Possible Mint Sandstorm activity
  • Anomaly detected in ASEP registry

Threat intelligence reports

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

Microsoft Defender Threat Intelligence

Microsoft Defender XDR Threat analytics 

Indicators of compromise

Organizations who fit the targeting model discussed in this report can hunt for the following indicators of compromise in their environments.

Domains

  • east-healthy-dress[.]glitch[.]me
  • coral-polydactyl-dragonfruit[.]glitch[.]me
  • kwhfibejjyxregxmnpcs[.]supabase[.]co
  • epibvgvoszemkwjnplyc[.]supabase[.]co
  • ndrrftqrlblfecpupppp[.]supabase[.]co
  • cloud-document-edit[.]onrender[.]com

Files

  • MediaPl.dll (SHA-256: f2dec56acef275a0e987844e98afcc44bf8b83b4661e83f89c6a2a72c5811d5f)

Advanced hunting

Microsoft Defender XDR

Curl command used to retrieve malicious files

Use this query to locate the curl command Mint Sandstorm used to pull down malicious files in this campaign.

DeviceProcessEvents
| where InitiatingProcessCommandLine has_all('id=',
'&Prog') and InitiatingProcessCommandLine has_any('vbs', '--ssl')

Creation of log files

Use this query to identify files created by Mint Sandstorm, ostensibly for exfiltration.

DeviceProcessEvents
| where InitiatingProcessCommandLine has_all('powershell', '$pnt', 'Get-Content', 'gcm') and InitiatingProcessCommandLine has_any('documentLog', 'documentLoger', 'Logdocument')

Files with double file name extensions

Use this query to find files with double extension, e.g., .pdf.lnk.

DeviceFileEvents
| where FileName endswith ".pdf.lnk"

Registry keys with VBScript

Use this query to find registry run keys entry with VBScript in value

DeviceRegistryEvents
| where ActionType == "RegistryValueSet" or ActionType == "RegistryKeyCreated"
| where RegistryKey endswith @"\Software\Microsoft\Windows\CurrentVersion\Run" or 
RegistryKey endswith @"\Software\Microsoft\Windows\CurrentVersion\RunOnce" or
RegistryKey endswith @"\Software\Microsoft\Windows\CurrentVersion\Policies\Explorer\Run"
| where RegistryValueData has_any ("vbscript",".vbs")

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.

Learn more

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

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

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

The post New TTPs observed in Mint Sandstorm campaign targeting high-profile individuals at universities and research orgs appeared first on Microsoft Security Blog.

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