Cybercrime | Latest Threats | Microsoft Security Blog http://approjects.co.za/?big=en-us/security/blog/threat-intelligence/cybercrime/ Expert coverage of cybersecurity topics Wed, 15 Apr 2026 13:40:07 +0000 en-US hourly 1 https://wordpress.org/?v=6.8.3 Investigating Storm-2755: “Payroll pirate” attacks targeting Canadian employees http://approjects.co.za/?big=en-us/security/blog/2026/04/09/investigating-storm-2755-payroll-pirate-attacks-targeting-canadian-employees/ Thu, 09 Apr 2026 15:00:00 +0000 Microsoft Incident Response – Detection and Response Team (DART) researchers observed an emerging, financially motivated threat actor, tracked as Storm-2755, compromising Canadian employee accounts to gain unauthorized access to employee profiles and divert salary payments to attacker-controlled accounts.

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Microsoft Incident Response – Detection and Response Team (DART) researchers observed an emerging, financially motivated threat actor that Microsoft tracks as Storm-2755 conducting payroll pirate attacks targeting Canadian users. In this campaign, Storm-2755 compromised user accounts to gain unauthorized access to employee profiles and divert salary payments to attacker-controlled accounts, resulting in direct financial loss for affected individuals and organizations. 

While similar payroll pirate attacks have been observed in other malicious campaigns, Storm-2755’s campaign is distinct in both its delivery and targeting. Rather than focusing on a specific industry or organization, the actor relied exclusively on geographic targeting of Canadian users and used malvertising and search engine optimization (SEO) poisoning on industry agnostic search terms to identify victims. The campaign also leveraged adversary‑in‑the‑middle (AiTM) techniques to hijack authenticated sessions, allowing the threat actor to bypass multifactor authentication (MFA) and blend into legitimate user activity.

Microsoft has been actively engaged with affected organizations and taken multiple disruption efforts to help prevent further compromise, including tenant takedown. Microsoft continues to engage affected customers, providing visibility by sharing observed tactics, techniques, and procedures (TTPs) while supporting mitigation efforts.

In this blog, we present our analysis of Storm-2755’s recent campaign and the TTPs employed across each stage of the attack chain. To support proactive mitigations against this campaign and similar activity, we also provide comprehensive guidance for investigation and remediation, including recommendations such as implementing phishing-resistant MFA to help block these attacks and protect user accounts.

Storm-2755’s attack chain

Analysis of this activity reveals a financially motivated campaign built around session hijacking and abuse of legitimate enterprise workflows. Storm-2755 combined initial credential and token theft with session persistence and targeted discovery to identify payroll and human resources (HR) processes within affected Canadian organizations. By operating through authenticated user sessions and blending into normal business activity, the threat actor was able to minimize detection while pursuing direct financial gain.

The sections below examine each stage of the attack chain—from initial access through impact—detailing the techniques observed.

Initial access

In the observed campaign, Storm-2755 likely gained initial access through SEO poisoning or malvertising that positioned the actor-controlled domain, bluegraintours[.]com, at the top of search results for generic queries like “Office 365” or common misspellings like “Office 265”. Based on data received by DART, unsuspecting users who clicked these links were directed to a malicious Microsoft 365 sign-in page designed to mimic the legitimate experience, resulting in token and credential theft when users entered their credentials.

Once a user entered their credentials into the malicious page, sign-in logs reveal that the victim recorded a 50199 sign-in interrupt error immediately before Storm-2755 successfully compromised the account. When the session shifts from legitimate user activity to threat actor control, the user-agent for the session changes to Axios; typically, version 1.7.9, however the session ID will remain consistent, indicating that the token has been replayed.

This activity aligns with an AiTM attack—an evolution of traditional credential phishing techniques—in which threat actors insert malicious infrastructure between the victim and a legitimate authentication service. Rather than harvesting only usernames and passwords, AiTM frameworks proxy the entire authentication flow in real time, enabling the capture session cookies and OAuth access tokens issued upon successful authentication. Due to these tokens representing a fully authenticated session, threat actors can reuse them to gain access to Microsoft services without being prompted for credentials or MFA, effectively bypassing legacy MFA protections not designed to be phishing-resistant; phishing-resistant methods such as FIDO2/WebAuthN are designed to mitigate this risk.

While Axios is not a malicious tool, this attack path seems to take advantage of known vulnerabilities of the open-source software, namely CVE-2025-27152, which can lead to server-side request forgeries.

Persistence

Storm-2755 leveraged version 1.7.9 of the Axios HTTP client to relay authentication tokens to the customer infrastructure which effectively bypassed non-phishing resistant MFA and preserved access without requiring repeated sign ins. This replay flow allowed Storm-2755 to maintain these active sessions and proxy legitimate user actions, effectively executing an AiTM attack.

Microsoft consistently observed non-interactive sign ins to the OfficeHome application associated with the Axios user-agent occurring approximately every 30 minutes until remediation actions revoked active session tokens, which allowed Storm-2755 to maintain these active sessions and proxy legitimate user actions without detection.

After around 30 days, we observed that the stolen tokens would then become inactive when Storm-2755 did not continue maintaining persistence within the environment. The refresh token became unusable due to expiration, rotation, or policy enforcement, preventing the issuance of new access tokens after the session token had expired. The compromised sessions primarily featured non-interactive sign ins to OfficeHome and recorded sign ins to Microsoft Outlook, My Sign-Ins, and My Profile. For a more limited set of identities, password and MFA changes were observed to maintain more durable persistence within the environment after the token had expired.

A user is lured to an actor-controlled authentication page via SEO poisoning or malvertising and unknowingly submits credentials, enabling the threat actor to replay the stolen session token for impersonation. The actor then maintains persistence through scheduled token replay and conducts follow-on activity such as creating inbox rules or requesting changes in direct deposits until session revocation occurs.
Figure 1. Storm-2755 attack flow

Discovery

Once user accounts have been successfully comprised, discovery actions begin to identify internal processes and mailboxes associated with payroll and HR. Specific intranet searches during compromised sessions focused on keywords such as “payroll”, “HR”, “human”, “resources”, ”support”, “info”, “finance”, ”account”, and “admin” across several customer environments.

Email subject lines were also consistent across all compromised users; “Question about direct deposit”, with the goal of socially engineering HR or finance staff members into performing manual changes to payroll instructions on behalf of Storm-2755, removing the need for further hands-on-keyboard activity.

An example email with several questions regarding direct deposit payments, such as where to send the void cheque, whether the payment can go to a new account, and requesting confirmation of the next payment date.
Figure 2. Example Storm-2755 direct deposit email

While similar recent campaigns have observed email content being tailored to the institution and incorporating elements to reference senior leadership contacts, Storm-2755’s attack seems to be focused on compromising employees in Canada more broadly. 

Where Storm-2755 was unable to successfully achieve changes to payroll information through user impersonation and social engineering of HR personnel, we observed a pivot to direct interaction and manual manipulation of HR software-as-a-service (SaaS) programs such as Workday. While the example below illustrates the attack flow as observed in Workday environments, it’s important to note that similar techniques could be leveraged against any payroll provider or SaaS platform.

Defense evasion

Following discovery activities, but prior to email impersonation, Storm-2755 created email inbox rules to move emails containing the keywords “direct deposit” or “bank” to the compromised user’s conversation history and prevent further rule processing. This rule ensured that the victim would not see the email correspondence from their HR team regarding the malicious request for bank account changes as this correspondence was immediately moved to a hidden folder.

This technique was highly effective in disguising the account compromise to the end user, allowing the threat actor to discreetly continue actions to redirect payments to an actor-controlled bank account undisturbed.

To further avoid potential detection by the account owner, Storm-2755 renewed the stolen session around 5:00 AM in the user’s time zone, operating outside normal business hours to reduce the chance of a legitimate reauthentication that would invalidate their access.

Impact

The compromise led to a direct financial loss for one user. In this case, Storm-2755 was able to gain access to the user’s account and created inbox rules to prevent emails that contained “direct deposit” or “bank”, effectively suppressing alerts from HR. Using the stolen session, the threat actor would email HR to request changes to direct deposit details, HR would then send back the instructions on how to change it. This led Storm-2755 to manually sign in to Workday as the victim to update banking information, resulting in a payroll check being redirected to an attacker-controlled bank account.

Defending against Storm-2755 and AiTM campaigns

Organizations should mitigate AiTM attacks by revoking compromised tokens and sessions immediately, removing malicious inbox rules, and resetting credentials and MFA methods for affected accounts.

To harden defenses, enforce device compliance enforcement through Conditional Access policies, implement phishing-resistant MFA, and block legacy authentication protocols. Organizations storing data in a security information and event management (SIEM) solution enable Defenders to quickly establish a clearer baseline of regular and irregular activity to distinguish compromised sessions from legitimate activity.

Enable Microsoft Defender to automatically disrupt attacks, revoke tokens in real time, monitor for anomalous user-agents like Axios, and audit OAuth applications to prevent persistence. Finally, run phishing simulation campaigns to improve user awareness and reduce susceptibility to credential theft.

To proactively protect against this attack pattern and similar patterns of compromise Microsoft recommends:

  1. Implement phishing resistant MFA where possible: Traditional MFA methods such as SMS codes, email-based one-time passwords (OTPs), and push notifications are becoming less effective against today’s attackers. Sophisticated phishing campaigns have demonstrated that second factors can be intercepted or spoofed.
  2. Use Conditional Access Policies to configure adaptive session lifetime policies: Session lifetime and persistence can be managed in several different ways based on organizational needs. These policies are designed to restrict extended session lifetime by prompting the user for reauthentication. This reauthentication might involve only one first factor, such as password, FIDO2 security keys, or passwordless Microsoft Authenticator, or it might require MFA.
  3. Leverage continuous access evaluation (CAE): For supporting applications to ensure access tokens are re-evaluated in near real time when risk conditions change. CAE reduces the effectiveness of stolen access and fresh tokens by allowing access to be promptly revoked following user risk changes, credential resets, or policy enforcement events limiting attacker persistence.
    1. Consider Global Secure Access (GSA) as a complementary network control path: Microsoft’s Global Secure Access (Entra Internet Access + Entra Private Access) extends Zero Trust enforcement to the network layer, providing an identity-aware secure network edge that strengthens CAE signal fidelity, enables Compliant Network Conditional Access conditions, and ensures consistent policy enforcement across identity, device, and network—forming a complete third managed path alongside identity and device controls.
  4. Create alerting of suspicious inbox-rule creation: This alerting is essential to quickly identify and triage evidence of business email compromise (BEC) and phishing campaigns. This playbook helps defenders investigate any incident related to suspicious inbox manipulation rules configured by threat actors and take recommended actions to remediate the attack and protect networks.
  5. Secure organizational resources through Microsoft Intune compliance policies: When integrated with Microsoft Entra Conditional Access policies, Intune offers an added layer of protection based on a devices current compliance status to help ensure that only devices that are compliant are permitted to access corporate resources.

Microsoft Defender detection and hunting guidance

Microsoft Defender 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.

Tactic Observed activity Microsoft Defender coverage 
Credential accessAn OAuth device code authentication was detected in an unusual context based on user behavior and sign-in patterns.Microsoft Defender XDR
– Anomalous OAuth device code authentication activity
Credential accessA possible token theft has been detected. Threat actor tricked a user into granting consent or sharing an authorization code through social engineering or AiTM techniques. Microsoft Defender XDR
– Possible adversary-in-the-middle (AiTM) attack detected (ConsentFix)
Initial accessToken replay often result in sign ins from geographically distant IP addresses. The presence of sign ins from non-standard locations should be investigated further to validate suspected token replay.  Microsoft Entra ID Protection
– Atypical Travel
– Impossible Travel
– Unfamiliar sign-in properties (lower confidence)
Initial accessAn authentication attempt was detected that aligns with patterns commonly associated with credential abuse or identity attacks.Microsoft Defender XDR
– Potential Credential Abuse in Entra ID Authentication  
Initial accessA successful sign in using an uncommon user-agent and a potentially malicious IP address was detected in Microsoft Entra.Microsoft Defender XDR
– Suspicious Sign-In from Unusual User Agent and IP Address
PersistenceA user was suspiciously registered or joined into a new device to Entra, originating from an IP address identified by Microsoft Threat Intelligence.Microsoft Defender XDR
– Suspicious Entra device join or registration

Microsoft Security Copilot

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

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

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

Threat intelligence reports

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

Microsoft Defender XDR threat analytics

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 queries to find related activity in their networks:

Review inbox rules created to hide or delete incoming emails from Workday

Results of the following query may indicate an attacker is trying to delete evidence of Workday activity.

CloudAppEvents 
| where Timestamp >= ago(1d)
| where Application == "Microsoft Exchange Online" and ActionType in ("New-InboxRule", "Set-InboxRule")  
| extend Parameters = RawEventData.Parameters // extract inbox rule parameters
| where Parameters has "From" and Parameters has "@myworkday.com" // filter for inbox rule with From field and @MyWorkday.com in the parameters
| where Parameters has "DeleteMessage" or Parameters has ("MoveToFolder") // email deletion or move to folder (hiding)
| mv-apply Parameters on (where Parameters.Name == "From"
| extend RuleFrom = tostring(Parameters.Value))
| mv-apply Parameters on (where Parameters.Name == "Name" 
| extend RuleName = tostring(Parameters.Value))

Review updates to payment election or bank account information in Workday

The following query surfaces changes to payment accounts in Workday.

CloudAppEvents 
| where Timestamp >= ago(1d)
| where Application == "Workday"
| where ActionType == "Change My Account" or ActionType == "Manage Payment Elections"
| extend Descriptor = tostring(RawEventData.target.descriptor)

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.

Malicious inbox rule

The query includes filters specific to inbox rule creation, operations for messages with DeleteMessage, and suspicious keywords.

let Keywords = dynamic(["direct deposit", “hr”, “bank”]);
OfficeActivity
| where OfficeWorkload =~ "Exchange" 
| where Operation =~ "New-InboxRule" and (ResultStatus =~ "True" or ResultStatus =~ "Succeeded")
| where Parameters has "Deleted Items" or Parameters has "Junk Email"  or Parameters has "DeleteMessage"
| extend Events=todynamic(Parameters)
| parse Events  with * "SubjectContainsWords" SubjectContainsWords '}'*
| parse Events  with * "BodyContainsWords" BodyContainsWords '}'*
| parse Events  with * "SubjectOrBodyContainsWords" SubjectOrBodyContainsWords '}'*
| where SubjectContainsWords has_any (Keywords)
 or BodyContainsWords has_any (Keywords)
 or SubjectOrBodyContainsWords has_any (Keywords)
| extend ClientIPAddress = case( ClientIP has ".", tostring(split(ClientIP,":")[0]), ClientIP has "[", tostring(trim_start(@'[[]',tostring(split(ClientIP,"]")[0]))), ClientIP )
| extend Keyword = iff(isnotempty(SubjectContainsWords), SubjectContainsWords, (iff(isnotempty(BodyContainsWords),BodyContainsWords,SubjectOrBodyContainsWords )))
| extend RuleDetail = case(OfficeObjectId contains '/' , tostring(split(OfficeObjectId, '/')[-1]) , tostring(split(OfficeObjectId, '\\')[-1]))
| summarize count(), StartTimeUtc = min(TimeGenerated), EndTimeUtc = max(TimeGenerated) by  Operation, UserId, ClientIPAddress, ResultStatus, Keyword, OriginatingServer, OfficeObjectId, RuleDetail
| extend AccountName = tostring(split(UserId, "@")[0]), AccountUPNSuffix = tostring(split(UserId, "@")[1])
| extend OriginatingServerName = tostring(split(OriginatingServer, " ")[0])

Detect network IP and domain indicators of compromise using ASIM

The following query checks IP addresses and domain IOCs across data sources supported by ASIM network session parser.

//IP list and domain list- _Im_NetworkSession
let lookback = 30d;
let ioc_domains = dynamic(["http://bluegraintours.com"]);
_Im_NetworkSession(starttime=todatetime(ago(lookback)), endtime=now())
| where DstDomain has_any (ioc_domains)
| summarize imNWS_mintime=min(TimeGenerated), imNWS_maxtime=max(TimeGenerated),
  EventCount=count() by SrcIpAddr, DstIpAddr, DstDomain, Dvc, EventProduct, EventVendor

Detect domain and URL indicators of compromise using ASIM

The following query checks domain and URL IOCs across data sources supported by ASIM web session parser.

// file hash list - imFileEvent
// Domain list - _Im_WebSession
let ioc_domains = dynamic(["http://bluegraintours.com"]);
_Im_WebSession (url_has_any = ioc_domains)

Indicators of compromise

In observed compromises associated with hxxp://bluegraintours[.]com, sign-in logs consistently showed a distinctive authentication pattern. This pattern included multiple failed sign‑in attempts with various causes followed by a failure citing Microsoft Entra error code 50199, immediately preceding a successful authentication. Upon successful sign in, the user-agent shifted to Axios, while the session ID remained unchanged—an indication that an authenticated session token had been replayed rather than a new session established. This combination of error sequencing, user‑agent transition, and session continuity is characteristic of AiTM activity and should be evaluated together when assessing potential compromise tied to this domain

IndicatorTypeDescription
hxxp://bluegraintours[.]comURLMalicious website created to steal user tokens
axios/1.7.9User-agent stringUser agent string utilized during AiTM attack

Acknowledgments

Learn more

For the latest security research from the Microsoft Threat Intelligence community, check out the Microsoft Threat Intelligence Blog.

To get notified about new publications and to join discussions on social media, follow us on LinkedIn, X (formerly Twitter), and Bluesky.

To hear stories and insights from the Microsoft Threat Intelligence community about the ever-evolving threat landscape, listen to the Microsoft Threat Intelligence podcast.

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Storm-1175 focuses gaze on vulnerable web-facing assets in high-tempo Medusa ransomware operations http://approjects.co.za/?big=en-us/security/blog/2026/04/06/storm-1175-focuses-gaze-on-vulnerable-web-facing-assets-in-high-tempo-medusa-ransomware-operations/ Mon, 06 Apr 2026 16:00:00 +0000 The financially motivated cybercriminal threat actor Storm-1175 operates high-velocity ransomware campaigns that weaponize recently disclosed vulnerabilities to obtain initial access, exfiltrate data, and deploy Medusa ransomware.

The post Storm-1175 focuses gaze on vulnerable web-facing assets in high-tempo Medusa ransomware operations appeared first on Microsoft Security Blog.

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The financially motivated cybercriminal actor tracked by Microsoft Threat Intelligence as Storm-1175 operates high-velocity ransomware campaigns that weaponize N-days, targeting vulnerable, web-facing systems during the window between vulnerability disclosure and widespread patch adoption. Following successful exploitation, Storm-1175 rapidly moves from initial access to data exfiltration and deployment of Medusa ransomware, often within a few days and, in some cases, within 24 hours. The threat actor’s high operational tempo and proficiency in identifying exposed perimeter assets have proven successful, with recent intrusions heavily impacting healthcare organizations, as well as those in the education, professional services, and finance sectors in Australia, United Kingdom, and United States.

The pace of Storm-1175’s campaigns is enabled by the threat actor’s consistent use of recently disclosed vulnerabilities to obtain initial access. While the threat actor typically uses N-day vulnerabilities, we have also observed Storm-1175 leveraging zero-day exploits, in some cases a full week before public vulnerability disclosure. The threat actor has also been observed chaining together multiple exploits to enable post-compromise activity. After initial access, Storm-1175 establishes persistence by creating new user accounts, deploys various tools including remote monitoring and management software for lateral movement, conducts credential theft, and tampers with security solutions before deploying ransomware throughout the compromised environment.

In this blog post, we delve into the attack techniques attributed to Storm-1175 over several years. While Storm-1175’s methodology aligns with the tactics, techniques, and procedures (TTPs) of many tracked ransomware actors, analysis of their post-compromise tactics provides essential insights into how organizations can harden and defend against attackers like Storm-1175, informing opportunities to disrupt attackers even if they have gained initial access to a network.

Storm-1175’s rapid attack chain: From initial access to impact

Exploitation of vulnerable web-facing assets

Storm-1175 rapidly weaponizes recently disclosed vulnerabilities to obtain initial access. Since 2023, Microsoft Threat Intelligence has observed exploitation of over 16 vulnerabilities, including:

Storm-1175 rotates exploits quickly during the time between disclosure and patch availability or adoption, taking advantage of the period where many organizations remain unprotected. In some cases, Storm-1175 has weaponized exploits for disclosed vulnerabilities in as little as one day, as was the case for CVE-2025-31324 impacting SAP NetWeaver: the security issue was disclosed on April 24, 2025, and we observed Storm-1175 exploitation soon after on April 25.

Diagram showing timeline of Storm-1175 exploitation, of various vulnerabilities over the years, including date of disclosure and date of weaponization
Figure 1. Timeline of disclosure and exploitation of vulnerabilities used by Storm-1175 in campaigns

In multiple intrusions, Storm-1175 has chained together exploits to enable post-compromise activities like remote code execution (RCE). For example, in July 2023, Storm-1175 exploited two vulnerabilities affecting on-premises Microsoft Exchange Servers, dubbed “OWASSRF” by public researchers: exploitation of CVE‑2022‑41080 provided initial access by exposing Exchange PowerShell via Outlook Web Access (OWA), and Storm-1175 subsequently exploited CVE‑2022‑41082 to achieve remote code execution.

Storm-1175 has also demonstrated a capability for targeting Linux systems as well: in late 2024, Microsoft Threat Intelligence identified the exploitation of vulnerable Oracle WebLogic instances across multiple organizations, though we were unable to identify the exact vulnerability being exploited in these attacks.

Finally, we have also observed the use of at least three zero-day vulnerabilities including, most recently, CVE-2026-23760 in SmarterMail, which was exploited by Storm-1175 the week prior to public disclosure, and CVE-2025-10035 in GoAnywhere Managed File Transfer, also exploited one week before public disclosure. While these more recent attacks demonstrate an evolved development capability or new access to resources like exploit brokers for Storm-1175, it is worth noting that GoAnywhere MFT has previously been targeted by ransomware attackers, and that the SmarterMail vulnerability was reportedly similar to a previously disclosed flaw; these factors may have helped to facilitate subsequent zero-day exploitation activity by Storm-1175, who still primarily leverages N-day vulnerabilities. Regardless, as attackers increasingly become more adept at identifying new vulnerabilities, understanding your digital footprint—such as through the use of public scanning interfaces like Microsoft Defender External Attack Surface Management—is essential to defending against perimeter network attacks.

Covert persistence and lateral movement

During exploitation, Storm-1175 typically creates a web shell or drops a remote access payload to establish their initial hold in the environment. From this point, Microsoft Threat Intelligence has observed Storm-1175 moving from initial access to ransomware deployment in as little as one day, though many of the actor’s attacks have occurred over a period of five to six days.

Diagram showing the Storm-1175 attack chain from Exploitation to Impact
Figure 2. Storm-1175 attack chain

On the initially compromised device, the threat actor often establishes persistence by creating a new user and adding that user to the administrators group:

Screenshot of code for creating new user account and adding as administrator
Figure 3. Storm-1175 creates a new user account and adds it as an administrator

From this account, Storm-1175 begins their reconnaissance and lateral movement activity. Storm-1175 has a rotation of tools to accomplish these subsequent attack stages. Most commonly, we observe the use of living-off-the-land binaries (LOLBins), including PowerShell and PsExec, followed by the use of Cloudflare tunnels (renamed to mimic legitimate binaries like conhost.exe) to move laterally over Remote Desktop Protocol (RDP) and deliver payloads to new devices. If RDP is not allowed in the environment, Storm-1175 has been observed using administrator privileges to modify the Windows Firewall policy to enable Remote Desktop.

Screenshot of code for modifying the firewall and enabling RDP
Figure 4. From an initial foothold after the compromise of a SmarterMail application, Storm-1175 modifies the firewall and enables remote desktop access for lateral movement, writing the results of the command to a TXT file

Storm-1175 has also demonstrated a heavy reliance on remote monitoring and management (RMM) tools during post-compromise activity. Since 2023, Storm-1175 has used multiple RMMs, including:

  • Atera RMM
  • Level RMM
  • N-able
  • DWAgent
  • MeshAgent
  • ConnectWise ScreenConnect
  • AnyDesk
  • SimpleHelp

While often used by enterprise IT teams, these RMM tools have multi-pronged functionality that could also allow adversaries to maintain persistence in a compromised network, create new user accounts, enable an alternative command-and-control (C2) method, deliver additional payloads, or use as an interactive remote desktop session.

In many attacks, Storm-1175 relies on PDQ Deployer, a legitimate software deployment tool that lets system administrators silently install applications, for both lateral movement and payload delivery, including ransomware deployment throughout the network.

Additionally, Storm-1175 has leveraged Impacket for lateral movement. Impacket is a collection of open-source Python classes designed for working with network protocols, and it is popular with adversaries due to ease of use and wide range of capabilities. Microsoft Defender for Endpoint has a dedicated attack surface reduction rule to defend against lateral movement techniques used by Impacket: Block process creations originating from PSExec and WMI commands); protecting lateral movement pathways can also mitigate Impacket.

Credential theft

Impacket is further used to facilitate credential dumping through LSASS; the threat actor also leveraged the commodity credential theft tool Mimikatz in identified intrusions in 2025. Additionally, Storm-1175 has relied on known living-off-the-land techniques for stealing credentials, such as by modifying the registry entry UseLogonCredential to turn on WDigest credential caching, or using Task Manager to dump LSASS credentials; for both of these attack techniques, the threat actor must obtain local administrative privileges to modify these resources. The attack surface reduction rule block credential stealing from LSASS can limit the effectiveness of this type of attack, and—more broadly—limiting the use of local administrator rights by end users. Ensuring that local administrator passwords are not shared through the environment can also reduce the risk of these LSASS dumping techniques.

We have also observed that after gaining administrator credentials, Storm-1175 has used a script to recover passwords from Veeam backup software, which is used to connect to remote hosts, therefore enabling ransomware deployment to additional connected systems.

With sufficient privileges, Storm-1175 can then use tools like PsExec to pivot to a Domain Controller, where they have accessed the NTDS.dit dump, a copy of the Active Directory database which contains user data and passwords that can be cracked offline. This privileged position has also granted Storm-1175 access to the security account manager (SAM), which provides detailed configuration and security settings, enabling an attacker to understand and manipulate the system environment on a much wider scale.

Security tampering for ransomware delivery

Storm-1175 modifies the Microsoft Defender Antivirus settings stored in the registry to tamper with the antivirus software and prevent it from blocking ransomware payloads; in order to accomplish this, an attacker must have access to highly privileged accounts that can modify the registry directly. For this reason, prioritizing alerts related to credential theft activity, which typically indicate an active attacker in the environment, is essential to responding to ransomware signals and preventing attackers from gaining privileged account access.

Storm-1175 has also used encoded PowerShell commands to add the C:\ drive to the antivirus exclusion path, preventing the security solution from scanning the drive and allowing payloads to run without any alerts. Defenders can harden against these tampering techniques by combining tamper protection with the DisableLocalAdminMerge setting, which prevents attackers from using local administrator privileges to set antivirus exclusions.

Data exfiltration and ransomware deployment

Like other ransomware as a service (RaaS) offerings, Medusa offers a leak site to facilitate double extortion operations for its affiliates: attackers not only encrypt data, but steal the data and hold it for ransom, threatening to leak the files publicly if a ransom is not paid. To that aim, Storm-1175 often uses Bandizip to collect files and Rclone for data exfiltration. Data synchronization tools like Rclone allow threat actors to easily transfer large volumes of data to a remote attacker-owned cloud resource. These tools also provide data synchronization capabilities, moving newly created or updated files to cloud resources in real-time to enable continuous exfiltration throughout all stages of the attack without needing attacker interaction.

Finally, having gained sufficient access throughout the network, Storm-1175 frequently leverages PDQ Deployer to launch a script (RunFileCopy.cmd) and deliver Medusa ransomware payloads. In some cases, Storm-1175 has alternatively used highly privileged access to create a Group Policy update to broadly deploy ransomware.

Mitigation and protection guidance

To defend against Storm-1175 TTPs and similar activity, Microsoft recommends the following mitigation measures:

Microsoft Defender detections

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

Tactic Observed activity Microsoft Defender coverage 
Initial AccessStorm-1175 exploits vulnerable web-facing applicationsMicrosoft Defender for Endpoint
– Ransomware-linked threat actor detected
– Possible Beyond Trust software vulnerability exploitation
– Possible exploitation of GoAnywhere MFT vulnerability
– Possible SAP NetWeaver vulnerability exploitation Possible exploitation of JetBrains TeamCity vulnerability
– Suspicious command execution via ScreenConnect
– Suspicious service launched
Persistence and privilege escalationStorm-1175 creates new user accounts under administrative groups using the net commandMicrosoft Defender for Endpoint
– User account created under suspicious circumstances
– New local admin added using Net commands
– New group added suspiciously
– Suspicious account creation
– Suspicious Windows account manipulation
– Anomalous account lookups
Credential theftStorm-1175 dumps credentials from LSASS, or uses a privileged position from the Domain Controller to access NTDS.dit and SAM hiveMicrosoft Defender Antivirus
– Behavior:Win32/SAMDumpz

Microsoft Defender for Endpoint
– Exposed credentials at risk of compromise
– Compromised account credentials
– Process memory dump
Persistence, lateral movementStorm-1175 uses RMM tools for persistence, payload delivery, and lateral movementMicrosoft Defender for Endpoint
– Suspicious Atera activity
– File dropped and launched from remote location
ExecutionStorm-1175 delivers tools such as PsExec or leverages LOLbins like PowerShell to carry out post-compromise activityMicrosoft Defender Antivirus
– Behavior:Win32/PsexecRemote

Microsoft Defender for Endpoint
– Hands-on-keyboard attack involving multiple devices
– Remote access software
– Suspicious PowerShell command line
– Suspicious PowerShell download or encoded command execution
– Ransomware-linked threat actor detected
ExfiltrationStorm-1175 uses the synch tool Rclone to steal documentsMicrosoft Defender for Endpoint
– Potential human-operated malicious activity
– Renaming of legitimate tools for possible data exfiltration
– Possible data exfiltration
– Hidden dual-use tool launch attempt
Defense evasionStorm-1175 disables Windows DefenderMicrosoft Defender for Endpoint
– Defender detection bypass
– Attempt to turn off Microsoft Defender Antivirus protection
ImpactStorm-1175 deploys Medusa ransomwareMicrosoft Defender Antivirus
– Ransom:Win32/Medusa

Microsoft Defender for Endpoint
– Possible ransomware activity based on a known malicious extension
– Possible compromised user account delivering ransomware-related files
– Potentially compromised assets exhibiting ransomware-like behavior
– Ransomware behavior detected in the file system
– File dropped and launched from remote location

Microsoft Security Copilot

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

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

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

Threat intelligence reports

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

Indicators of compromise

The following indicators are gathered from identified Storm-1175 attacks during 2026.

IndicatorTypeDescriptionFirst seenLast seen
0cefeb6210b7103fd32b996beff518c9b6e1691a97bb1cda7f5fb57905c4be96SHA-256Gaze.exe (Medusa Ransomware)2026-03-012026-03-01
9632d7e4a87ec12fdd05ed3532f7564526016b78972b2cd49a610354d672523c *Note that we have seen this hash in ransomware intrusions by other threat actors since 2024 as wellSHA-256lsp.exe (Rclone)2024-04-01  2026-02-18
e57ba1a4e323094ca9d747bfb3304bd12f3ea3be5e2ee785a3e656c3ab1e8086SHA-256main.exe (SimpleHelp)2026-01-152026-01-15
5ba7de7d5115789b952d9b1c6cff440c9128f438de933ff9044a68fff8496d19SHA-256moon.exe (SimpleHelp)2025-09-152025-09-22
185.135.86[.]149IPSimpleHelp C22024-02-232026-03-15
134.195.91[.]224IPSimpleHelp C22024-02-232026-02-26
85.155.186[.]121IPSimpleHelp C22024-02-232026-02-12

References

Learn more

For the latest security research from the Microsoft Threat Intelligence community, check out the Microsoft Threat Intelligence Blog.

To get notified about new publications and to join discussions on social media, follow us on LinkedIn, X (formerly Twitter), and Bluesky.

To hear stories and insights from the Microsoft Threat Intelligence community about the ever-evolving threat landscape, listen to the Microsoft Threat Intelligence podcast.

The post Storm-1175 focuses gaze on vulnerable web-facing assets in high-tempo Medusa ransomware operations appeared first on Microsoft Security Blog.

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Storm-2561 uses SEO poisoning to distribute fake VPN clients for credential theft http://approjects.co.za/?big=en-us/security/blog/2026/03/12/storm-2561-uses-seo-poisoning-to-distribute-fake-vpn-clients-for-credential-theft/ Thu, 12 Mar 2026 17:00:00 +0000 http://approjects.co.za/?big=en-us/security/blog/?p=145731 Storm-2561 uses SEO poisoning to push fake VPN downloads that install signed trojans and steal VPN credentials. Active since 2025, Storm-2561 mimics trusted brands and abuses legitimate services. This post reviews TTPs, IOCs, and mitigation guidance.

The post Storm-2561 uses SEO poisoning to distribute fake VPN clients for credential theft appeared first on Microsoft Security Blog.

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In mid-January 2026, Microsoft Defender Experts identified a credential theft campaign that uses fake virtual private network (VPN) clients distributed through search engine optimization (SEO) poisoning. The campaign redirects users searching for legitimate enterprise software to malicious ZIP files on attacker-controlled websites to deploy digitally signed trojans that masquerade as trusted VPN clients while harvesting VPN credentials. Microsoft Threat Intelligence attributes this activity to the cybercriminal threat actor Storm-2561.

Active since May 2025, Storm-2561 is known for distributing malware through SEO poisoning and impersonating popular software vendors. The techniques they used in this campaign highlight how threat actors continue to exploit trusted platforms and software branding to avoid user suspicion and steal sensitive information. By targeting users who are actively searching for enterprise VPN software, attackers take advantage of both user urgency and implicit trust in search engine rankings. The malicious ZIP files that contain fake installer files are hosted on GitHub repositories, which have since been taken down. Additionally, the trojans are digitally signed by a legitimate certificate that has since been revoked.

In this blog, we share our in-depth analysis of the tactics, techniques, and procedures (TTPs) and indicators of compromise in this Storm-2561 campaign, highlighting the social engineering techniques that the threat actor used to improve perceived legitimacy, avoid suspicion, and evade detection. We also share protection and mitigation recommendations, as well as Microsoft Defender detection and hunting guidance.

MICROSOFT DEFENDER EXPERTS

Around the clock, expert-led defense ↗

From search to stolen credentials: Storm-2561 attack chain

In this campaign, users searching for legitimate VPN software are redirected from search results to spoofed websites that closely mimic trusted VPN products but instead deploy malware designed to harvest credentials and VPN data. When users click to download the software, they are redirected to a malicious GitHub repository (no longer available) that hosts the fake VPN client for direct download.

The GitHub repo hosts a ZIP file containing a Microsoft Windows Installer (MSI) installer file that mimics a legitimate VPN software and side-loads malicious dynamic link library (DLL) files during installation. The fake VPN software enables credential collection and exfiltration while appearing like a benign VPN client application.

This campaign exhibits characteristics consistent with financially motivated cybercrime operations employed by Storm-2561. The malicious components are digitally signed by “Taiyuan Lihua Near Information Technology Co., Ltd.”

Diagram showing the attack chain of the Storm-2561 campaign
Figure 1. Storm-2561 campaign attack chain

Initial access and execution

The initial access vector relies on abusing SEO to push malicious websites to the top of search results for queries such as “Pulse VPN download” or “Pulse Secure client,” but Microsoft has observed spoofing of various VPN software brands and has observed the GitHub link at the following two domains: vpn-fortinet[.]com and ivanti-vpn[.]org.

Once the user lands on the malicious website and clicks to download the software, the malware is delivered through a ZIP download hosted at hxxps[:]//github[.]com/latestver/vpn/releases/download/vpn-client2/VPN-CLIENT.zip. At the time of this report, this repository is no longer active.

Screenshot of fake website posting as Fortinet
Figure 2. Screenshot from actor-controlled website vpn-fortinet[.]com masquerading as Fortinet
Code snippet for downloading the fake VPN installer
Figure 3. Code snippet from vpn-fortinet[.]com showing download of VPN-CLIENT.zip hosted on GitHub

When the user launches the malicious MSI masquerading as a legitimate Pulse Secure VPN installer embedded within the downloaded ZIP file, the MSI file installs Pulse.exe along with malicious DLL files to a directory structure that closely resembles a real Pulse Secure installation path: %CommonFiles%\Pulse Secure. This installation path blends in with legitimate VPN software to appear trustworthy and avoid raising user suspicion.

Alongside the primary application, the installer drops malicious DLLs, dwmapi.dll and inspector.dll, into the Pulse Secure directory. The dwmapi.dll file is an in-memory loader that drops and launches an embedded shellcode payload that loads and launches the inspector.dll file, a variant of the infostealer Hyrax. The Hyrax infostealer extracts URI and VPN sign-in credentials before exfiltrating them to attacker-controlled command-and-control (C2) infrastructure.

Code signing abuse

The MSI file and the malicious DLLs are signed with a valid digital certificate, which is now revoked, from Taiyuan Lihua Near Information Technology Co., Ltd. This abuse of code signing serves multiple purposes:

  • Bypasses default Windows security warnings for unsigned code
  • Might bypass application whitelisting policies that trust signed binaries
  • Reduces security tool alerts focused on unsigned malware
  • Provides false legitimacy to the installation process

Microsoft identified several other files signed with the same certificates. These files also masqueraded as VPN software. These IOCs are included in the below.

Credential theft

The fake VPN client presents a graphical user interface that closely mimics the legitimate VPN client, prompting the user to enter their credentials. Rather than establishing a VPN connection, the application captures the credentials entered and exfiltrates them to attacker-controlled C2 infrastructure (194.76.226[.]93:8080). This approach relies on visual deception and immediate user interaction, allowing attackers to harvest credentials as soon as the target attempts to sign in. The credential theft operation follows the below structured sequence:

  • UI presentation: A fake VPN sign-in dialog is displayed to the user, closely resembling the legitimate Pulse Secure client.
  • Error display: After credentials are submitted, a fake error message is shown to the user.
  • Redirection: The user is instructed to download and install the legitimate Pulse Secure VPN client.
  • Access to stored VPN data: The inspector.dll component accesses stored VPN configuration data from C:\ProgramData\Pulse Secure\ConnectionStore\connectionstore.dat.
  • Data exfiltration: Stolen credentials and VPN configuration data are transmitted to attacker-controlled infrastructure.

Persistence

To maintain access, the MSI malware establishes persistence during installation through the Windows RunOnce registry key, adding the Pulse.exe malware to run when the device reboots.

Defense evasion

One of the most sophisticated aspects of this campaign is the post-credential theft redirection strategy. After successfully capturing user credentials, the malicious application conducts the following actions:

  • Displays a convincing error message indicating installation failure
  • Provides instructions to download the legitimate Pulse VPN client from official sources
  • In certain instances, opens the user’s browser to the legitimate VPN website

If users successfully install and use legitimate VPN software afterward, and the VPN connection works as expected, there are no indications of compromise to the end user. Users are likely to attribute the initial installation failure to technical issues, not malware.

Defending against credential theft campaigns

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

  • Turn on cloud-delivered protection in Microsoft Defender Antivirus or the equivalent for your antivirus product to cover rapidly evolving attacker tools and techniques. Cloud-based machine learning protections block a huge majority of new and unknown variants. 
  • 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. 
  • Enable network protection in Microsoft Defender for Endpoint. 
  • Turn on web protection in Microsoft Defender for Endpoint. 
  • 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. 
  • Enforce multifactor authentication (MFA) on all accounts, remove users excluded from MFA, and strictly require MFA from all devices, in all locations, at all times. 
  • Remind employees that enterprise or workplace credentials should not be stored in browsers or password vaults secured with personal credentials. Organizations can turn off password syncing in browser on managed devices using Group Policy
  • Turn on the following attack surface reduction rule to block or audit activity associated with this threat:

Microsoft Defender detection and hunting guidance

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

Tactic Observed activity Microsoft Defender coverage 
ExecutionPayloads deployed on the device.Microsoft Defender Antivirus
Trojan:Win32/Malgent
TrojanSpy:Win64/Hyrax  

Microsoft Defender for Endpoint (set to block mode)
– An active ‘Malagent’ malware was blocked
– An active ‘Hyrax’ credential theft malware was blocked  
– Microsoft Defender for Endpoint VPN launched from unusual location
Defense evasionThe fake VPN software side-loads malicious DLL files during installation.Microsoft Defender for Endpoint
– An executable file loaded an unexpected DLL file
PersistenceThe Pulse.exe malware runs when the device reboots.Microsoft Defender for Endpoint
– Anomaly detected in ASEP registry

Microsoft Security Copilot

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

MICROSOFT SECURITY COPILOT

Protect at the speed and scale of AI ↗

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

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

Threat intelligence reports

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

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

Hunting queries

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

Files signed by Taiyuan Lihua Near Information Technology Co., Ltd.

Look for files signed with Taiyuan Lihua Near Information Technology Co., Ltd. signer.

let a = DeviceFileCertificateInfo
| where Signer == "Taiyuan Lihua Near Information Technology Co., Ltd."
| distinct SHA1;
DeviceProcessEvents
| where SHA1 in(a)

Identify suspicious DLLs in Pulse Secure folder

Identify launching of malicious DLL files in folders masquerading as Pulse Secure.

DeviceImageLoadEvents
| where FolderPath contains "Pulse Secure" and FolderPath contains "Program Files" and (FolderPath contains "\\JUNS\\" or FolderPath contains "\\JAMUI\\")
| where FileName has_any("inspector.dll","dwmapi.dll")

Indicators of compromise

IndicatorTypeDescription
57a50a1c04254df3db638e75a64d5dd3b0d6a460829192277e252dc0c157a62fSHA-256ZIP file retrieved from GitHub (VPN-Client.zip)
862f004679d3b142d9d2c729e78df716aeeda0c7a87a11324742a5a8eda9b557SHA-256Suspicious MSI file downloaded from the masqueraded Ivanti pulse VPN client domain (VPN-Client.msi)
6c9ab17a4aff2cdf408815ec120718f19f1a31c13fc5889167065d448a40dfe6SHA-256Suspicious DLL file loaded by the above executables; also signed by Taiyuan Lihua Near Information Technology Co., Ltd. (dwmapi.dll)
6129d717e4e3a6fb4681463e421a5603b640bc6173fb7ba45a41a881c79415caSHA-256Malicious DLL that steals data from C:\ProgramData\Pulse Secure\ConnectionStore\connstore.dat and exfiltrating it (inspector.dll)
44906752f500b61d436411a121cab8d88edf614e1140a2d01474bd587a8d7ba832397697c209953ef0252b95b904893cb07fa975SHA-256Malware signed by Taiyuan Lihua Near Information Technology Co., Ltd. (Pulse.exe)
85c4837e3337165d24c6690ca63a3274dfaaa03b2ddaca7f1d18b3b169c6aac1SHA-256Malware signed by Taiyuan Lihua Near Information Technology Co., Ltd. (Sophos-Connect-Client.exe)
98f21b8fa426fc79aa82e28669faac9a9c7fce9b49d75bbec7b60167e21963c9SHA-256Malware signed by Taiyuan Lihua Near Information Technology Co., Ltd. (GlobalProtect-VPN.exe)
cfa4781ebfa5a8d68b233efb723dbde434ca70b2f76ff28127ecf13753bfe011SHA-256Malware signed by Taiyuan Lihua Near Information Technology Co., Ltd. (VPN-Client.exe)
26db3fd959f12a61d19d102c1a0fb5ee7ae3661fa2b301135cdb686298989179SHA-256Malware signed by Taiyuan Lihua Near Information Technology Co., Ltd. (vpn.exe)
44906752f500b61d436411a121cab8d88edf614e1140a2d01474bd587a8d7ba8SHA-256Malware signed by Taiyuan Lihua Near Information Technology Co., Ltd. (Pulse.exe)
eb8b81277c80eeb3c094d0a168533b07366e759a8671af8bfbe12d8bc87650c9SHA-256Malware signed by Taiyuan Lihua Near Information Technology Co., Ltd. (WiredAccessMethod.dll)
8ebe082a4b52ad737f7ed33ccc61024c9f020fd085c7985e9c90dc2008a15adcSHA-256Malware signed by Taiyuan Lihua Near Information Technology Co., Ltd.(PulseSecureService.exe)
194.76.226[.]93IP addressIP address where stolen data is sent
checkpoint-vpn[.]comDomainSuspect initial access domain
cisco-secure-client[.]esDomainSuspect initial access domain
forticlient-for-mac[.]comDomainSuspect initial access domain
forticlient-vpn[.]deDomainSuspect initial access domain
forticlient-vpn[.]frDomainSuspect initial access domain
forticlient-vpn[.]itDomainSuspect initial access domain
forticlient[.]caDomainSuspect initial access domain
forticlient.co[.]ukDomainSuspect initial access domain
forticlient[.]noDomainSuspect initial access domain
fortinet-vpn[.]comDomainSuspect initial access domain
ivanti-vpn[.]orgDomainInitial access domain (GitHub ZIP)
ivanti-secure-access[.]deDomainSuspect initial access domain
ivanti-pulsesecure[.]comDomainSuspect initial access domain
sonicwall-netextender[.]nlDomainSuspect initial access domain
sophos-connect[.]orgDomainSuspect initial access domain
vpn-fortinet[.]comDomainInitial access domain (GitHub ZIP)
watchguard-vpn[.]comDomainSuspect initial access domain
vpn-connection[.]proDomainC2 where stolen credentials are sent
myconnection[.]proDomainC2 where stolen credentials are sent
hxxps://github[.]com/latestver/vpn/releases/download/vpn-client2/VPN-CLIENT.zipURLGitHub URL hosting VPN-CLIENT.zip file (no longer available)

References

Learn more

For the latest security research from the Microsoft Threat Intelligence community, check out the Microsoft Threat Intelligence Blog.

To get notified about new publications and to join discussions on social media, follow us on LinkedIn, X (formerly Twitter), and Bluesky.

To hear stories and insights from the Microsoft Threat Intelligence community about the ever-evolving threat landscape, listen to the Microsoft Threat Intelligence podcast.

The post Storm-2561 uses SEO poisoning to distribute fake VPN clients for credential theft appeared first on Microsoft Security Blog.

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Investigating targeted “payroll pirate” attacks affecting US universities http://approjects.co.za/?big=en-us/security/blog/2025/10/09/investigating-targeted-payroll-pirate-attacks-affecting-us-universities/ Thu, 09 Oct 2025 15:00:00 +0000 Microsoft Threat Intelligence has identified a financially motivated threat actor that we track as Storm-2657 compromising employee accounts to gain unauthorized access to employee profiles and divert salary payments to attacker-controlled accounts, attacks that have been dubbed “payroll pirate”.

The post Investigating targeted “payroll pirate” attacks affecting US universities appeared first on Microsoft Security Blog.

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Microsoft Threat Intelligence has observed a financially motivated threat actor that we track as Storm-2657 compromising employee accounts to gain unauthorized access to employee profiles and divert salary payments to attacker-controlled accounts. These types of attacks have been dubbed “payroll pirate” by the industry. Storm-2657 is actively targeting a range of US-based organizations, particularly employees in sectors like higher education, to gain access to third-party human resources (HR) software as a service (SaaS) platforms like Workday.  

In a campaign observed in the first half of 2025, we identified the actor specifically targeting Workday profiles. However, it’s important to note that any SaaS systems storing HR or payment and bank account information could be easily targeted with the same technique. These attacks don’t represent any vulnerability in the Workday platform or products, but rather financially motivated threat actors using sophisticated social engineering tactics and taking advantage of the complete lack of multifactor authentication (MFA) or lack of phishing-resistant MFA to compromise accounts. Workday has published guidance for their customers in their community, and we thank Workday for their partnership and support in helping to raise awareness on how to mitigate this threat.

Microsoft has identified and reached out to some of the affected customers to share tactics, techniques, and procedures (TTPs) and assist with mitigation efforts. In this blog, we present our analysis of Storm-2657’s recent campaign and the TTPs employed in attacks. We offer comprehensive guidance for investigation and remediation, including implementing phishing-resistant MFA to help block these attacks and protect user accounts. Additionally, we provide comprehensive detections and hunting queries to enable organizations to defend against this attack and disrupt threat actor activity.

Analysis of the campaign

In the observed campaign, the threat actor gained initial access through phishing emails crafted to steal MFA codes using adversary-in-the-middle (AITM) phishing links. After obtaining MFA codes, the threat actor was able to gain unauthorized access to the victims’ Exchange Online and later hijacked and modified their Workday profiles.

After gaining access to compromised employee accounts, the threat actor created inbox rules to delete incoming warning notification emails from Workday, hiding the actor’s changes to the HR profiles. Storm-2657 then stealthily moved on to modify the employee’s salary payment configuration in their HR profile, thereby redirecting future salary payments to accounts under the actor’s control, causing financial harm to their victims. While the following example illustrates the attack flow as observed in Workday environments, it’s important to note that similar techniques could be leveraged against any payroll provider or SaaS platform.

Diagram depicting Storm-2657 phishing a Entra user account for MFA Duo to access the employee mailbox and HR SaaS system. In the mailbox, the attacker accesses various folders and messages in addition to creating an inbox rule to delete emails from Workday. In the HR system, the attacker accesses the employee's Workday through SSO before updating the employee's MFA settings and payroll information to redirect payments to the attacker-controlled bank account.
Figure 1. Attack flow of threat actor activity in a real incident

Initial access

The threat actor used realistic phishing emails, targeting accounts at multiple universities, to harvest credentials. Since March 2025, we’ve observed 11 successfully compromised accounts at three universities that were used to send phishing emails to nearly 6,000 email accounts across 25 universities.

Some phishing emails contained Google Docs links, making detection challenging, as these are common in academic environments. In multiple instances, compromised accounts did not have MFA enabled. In other cases, users were tricked into disclosing MFA codes via AiTM phishing links distributed through email. Following the compromise of email accounts and the payroll modifications in Workday, the threat actor leveraged newly accessed accounts to distribute further phishing emails, both within the organization and externally to other universities.

The threat actor used several themes in their phishing emails. One common theme involved messages about illnesses or outbreaks on campus, suggesting that recipients might have been exposed. These emails included a link to a Google Docs page that then redirected to an attacker-controlled domain.

Some examples of the email subject lines are:

  • COVID-Like Case Reported — Check Your Contact Status
  • Confirmed Case of Communicable Illness
  • Confirmed Illness

In one instance, a phishing email was sent to 500 individuals within a single organization, encouraging targets to check their illness exposure status. Approximately 10% of recipients reported the email as a suspected phishing attempt.

Figure 2. Sample of a phishing email sent by the threat actor with illness exposure related theme

The second theme involved reports of misconduct or actions by individuals within the faculty, with the goal of tricking recipients into checking the link to determine if they are mentioned in the report.

Some examples of the subject lines are:

  • Faculty Compliance Notice – Classroom Misconduct Report
  • Review Acknowledgment Requested – Faculty Misconduct Mention

The most recently identified theme involved phishing emails impersonating a legitimate university or an entity associated with a university. To make their messages appear convincing, Storm-2657 tailored the content based on the recipient’s institution. Examples included messages that appear to be official communications from the university president, information about compensation and benefits, or documents shared by HR with recipients. Most of the time the subject line contained either the university name or the university’s president name, further enhancing the email’s legitimacy and appeal to the intended target.

Some examples of the subject lines are:

  • Please find the document forwarded by the HR Department for your review
  • [UNIVERSITY NAME] 2025 Compensation and Benefits Update
  • A document authored by [UNIVERSITY PRESIDENT NAME] has been shared for your examination.
Screenshot of a sample phishing email claiming to be about 2025 compensation and benefits with a link for the recipient to access their benefits.
Figure 3. Sample of a phishing email sent by the threat actor with HR related theme

Defense evasion

Following account compromise, the threat actor created a generic inbox rule to hide or delete any incoming warning notification emails from the organization’s Workday email service. This rule ensured that the victim would not see the notification emails from Workday about the payroll changes made by the threat actor, thereby minimizing the likelihood of detection by the victim. In some cases, the threat actor might have attempted to stay under the radar and hide their traces from potential reviews by creating rule names solely using special characters or non-alphabetic symbols like “….” or “\’\’\’\’”.

Figure 4. An example of inbox rule creation to delete all incoming emails from Workday portal captured through Microsoft Defender for Cloud Apps

Persistence

In observed cases, the threat actor established persistence by enrolling their own phone numbers as MFA devices for victim accounts, either through Workday profiles or Duo MFA settings. By doing so, they bypassed the need for further MFA approval from the legitimate user, enabling continued access without detection.

Impact

The threat actor subsequently accessed Workday through single sign-on (SSO) and changed the victim’s payroll/bank account information.

With the Workday connector enabled in Microsoft Defender for Cloud Apps, analysts can efficiently investigate and identify attack traces by examining Workday logs and Defender-recorded actions. There are multiple indicators available to help pinpoint these changes. For example, one indicator from the Workday logs generated by such threat actor changes is an event called “Change My Account” or “Manage Payment Elections”, depending on the type of modifications performed in the Workday application audit logs:

Figure 5. Example of payment modification audit log as captured through Microsoft Defender for Cloud Apps

These payroll modifications are frequently accompanied by notification emails informing users that payroll or bank details have been changed or updated. As previously discussed, threat actors might attempt to eliminate these messages either through manual deletion or by establishing inbox rules. These deletions can be identified by monitoring Exchange Online events such as SoftDelete, HardDelete, and MoveToDeletedItems. The subjects of these emails typically contain the following terms:

  • “Payment Elections”
  • “Payment Election”
  • “Direct Deposit”

Microsoft Defender for Cloud Apps correlates signals from both Microsoft Exchange Online (first-party SaaS application) and Workday (third-party SaaS application), enabling thorough detection of suspicious activities that span multiple systems, as seen in the image below. Only by correlating first party and third-party signals is it possible to detect this activity spawning across multiple systems.

Screenshot of an audit log depicting an inbox rule creation in Exchange Online on August 14, 2025, followed by payroll account modifications in Workday on the same day.
Figure 6. Example of audit logs captured through Microsoft Defender for Cloud Apps showcasing an inbox rule creation in Microsoft Exchange Online followed by payroll account modification in Workday

Mitigation and protection guidance

Mitigating threats from actors like Storm-2657 begins with securing user identity by eliminating traditional credentials and adopting passwordless, phishing-resistant MFA methods such as FIDO2 security keys, Windows Hello for Business, and Microsoft Authenticator passkeys.

Microsoft recommends enforcing phishing-resistant MFA for privileged roles in Microsoft Entra ID to significantly reduce the risk of account compromise. Learn how to require phishing-resistant MFA for admin roles and plan a passwordless deployment.

Passwordless authentication improves security as well as enhances user experience and reduces IT overhead. Explore Microsoft’s overview of passwordless authentication and authentication strength guidance to understand how to align your organization’s policies with best practices. For broader strategies on defending against identity-based attacks, refer to Microsoft’s blog on evolving identity attack techniques.

If Microsoft Defender alerts indicate suspicious activity or confirmed compromised account or a system, it’s essential to act quickly and thoroughly. Below are recommended remediation steps for each affected identity:

  1. Reset credentials – Immediately reset the account’s password and revoke any active sessions or tokens. This ensures that any stolen credentials can no longer be used.
  2. Re-register or remove MFA devices – Review users MFA devices, specifically those recently added or updated.
  3. Revert unauthorized payroll or financial changes – If the attacker modified payroll or financial configurations, such as direct deposit details, revert them to their original state and notify the appropriate internal teams.
  4. Remove malicious inbox rules – Attackers often create inbox rules to hide their activity or forward sensitive data. Review and delete any suspicious or unauthorized rules.
  5. Verify MFA reconfiguration – Confirm that the user has successfully reconfigured MFA and that the new setup uses secure, phishing-resistant methods.

Microsoft Defender XDR detections

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.

TacticObserved activityMicrosoft Defender coverage
Initial accessThreat actor gains access to account through phishingMicrosoft Defender for Office 365
– Email messages removed after delivery
– Email reported by user as malware or phish

Microsoft Defender XDR
– Compromised user account in a recognized attack pattern
– Anonymous IP address
Defense EvasionThreat actor creates an inbox rule to delete incoming emails from WorkdayMicrosoft Defender for Cloud apps
– Possible BEC-related inbox rule
– Suspicious inbox manipulation rule
– Suspicious Workday inbox rule creation followed by a Workday session
– Malicious inbox rule manipulation possibly related to BEC payroll fraud attempt
ImpactThreat actor gains access to victim’s Workday profile and modifies payroll electionsMicrosoft Defender for Cloud apps
– Suspicious payroll configuration user activity in Workday

Hunting queries

Microsoft Defender XDR

The Microsoft Defender for Cloud Apps connector for Workday includes write events such as Workday account updates, payroll configuration changes, etc. These are available in the Defender XDR CloudAppEvents hunting tables for further investigation. Important events related to this attack include but are not limited:

  • Add iOS Device
  • Add Android Device
  • Change My Account
  • Manage Payment Elections

Install the Microsoft Defender for Cloud Apps connector for Workday to take advantage of these logging, investigation, and detection capabilities.

Review inbox rules created to hide or delete incoming emails from Workday

Results of the following query may indicate an attacker is trying to delete evidence of Workday activity.

CloudAppEvents 
| where Timestamp >= ago(1d)
| where Application == "Microsoft Exchange Online" and ActionType in ("New-InboxRule", "Set-InboxRule")  
| extend Parameters = RawEventData.Parameters // extract inbox rule parameters
| where Parameters has "From" and Parameters has "@myworkday.com" // filter for inbox rule with From field and @MyWorkday.com in the parameters
| where Parameters has "DeleteMessage" or Parameters has ("MoveToFolder") // email deletion or move to folder (hiding)
| mv-apply Parameters on (where Parameters.Name == "From"
| extend RuleFrom = tostring(Parameters.Value))
| mv-apply Parameters on (where Parameters.Name == "Name" 
| extend RuleName = tostring(Parameters.Value))

Review updates to payment election or bank account information in Workday

The following query surfaces changes to payment accounts in Workday.

CloudAppEvents 
| where Timestamp >= ago(1d)
| where Application == "Workday"
| where ActionType == "Change My Account" or ActionType == "Manage Payment Elections"
| extend Descriptor = tostring(RawEventData.target.descriptor)

Review device additions in Workday

The following query looks for recent device additions in Workday. If the device is unknown, it may indicate an attacker joined their own device for persistence and MFA evasion.

CloudAppEvents 
| where Timestamp >= ago(1d)
| where Application == "Workday"
| where ActionType has "Add iOS Device" or ActionType has "Add Android Device"
| extend Descriptor = tostring(RawEventData.target.descriptor) // will contain information of the device

Hunt for bulk suspicious emails from .edu sender

The following query identifies email from .edu senders sent to a high number of users.

EmailEvents
| where Timestamp >= ago(7d)
| where SenderFromDomain has "edu" or SenderMailFromDomain has "edu"
| where EmailDirection == "Inbound"
| summarize dcount(RecipientEmailAddress), dcount(InternetMessageId), make_set(InternetMessageId), dcount(Subject), dcount(NetworkMessageId), take_any(NetworkMessageId) by bin(Timestamp,1d), SenderFromAddress
| where dcount_RecipientEmailAddress > 100 // number can be adjusted, usually the sender will send emails to around 100-600 recipients per day

Hunt for phishing URL from identified .edu phish sender

If a suspicious .edu sender has been identified, use the following query to surface email events from this sender address.

EmailEvents
| where Timestamp >= ago(1d)
| where SenderFromAddress == ""
| where EmailDirection == "Inbound"
| project NetworkMessageId, Subject, InternetMessageId
| join EmailUrlInfo on NetworkMessageId
| where Timestamp >= ago(1d)
| project Url, NetworkMessageId, Subject, InternetMessageId

Hunt for user clicks to suspicious URL from the identified .edu phish sender (previous query)

If a suspicious .edu sender has been identified, use the below query to surface user clicks that may indicate a malicious link was accessed.

EmailEvents
| where Timestamp >= ago(1d)
| where SenderFromAddress == ""
| where EmailDirection == "Inbound"
| project NetworkMessageId, Subject, InternetMessageId
| join UrlClickEvents on NetworkMessageId
| where Timestamp >= ago(1d)
| project AccountUpn, Subject, InternetMessageId, DetectionMethods, ThreatTypes, IsClickedThrough // these users very likely fall into the phishing attack

Microsoft Sentinel

Install the Workday connector for Microsoft Sentinel. Microsoft Sentinel has a range of detection and threat hunting content that customers can use to detect the post exploitation activity detailed in this blog.

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.

Malicious inbox rule

The query includes filters specific to inbox rule creation, operations for messages with ‘DeleteMessage’, and suspicious keywords.

let Keywords = dynamic(["helpdesk", " alert", " suspicious", "fake", "malicious", "phishing", "spam", "do not click", "do not open", "hijacked", "Fatal"]);
OfficeActivity
| where OfficeWorkload =~ "Exchange" 
| where Operation =~ "New-InboxRule" and (ResultStatus =~ "True" or ResultStatus =~ "Succeeded")
| where Parameters has "Deleted Items" or Parameters has "Junk Email"  or Parameters has "DeleteMessage"
| extend Events=todynamic(Parameters)
| parse Events  with * "SubjectContainsWords" SubjectContainsWords '}'*
| parse Events  with * "BodyContainsWords" BodyContainsWords '}'*
| parse Events  with * "SubjectOrBodyContainsWords" SubjectOrBodyContainsWords '}'*
| where SubjectContainsWords has_any (Keywords)
 or BodyContainsWords has_any (Keywords)
 or SubjectOrBodyContainsWords has_any (Keywords)
| extend ClientIPAddress = case( ClientIP has ".", tostring(split(ClientIP,":")[0]), ClientIP has "[", tostring(trim_start(@'[[]',tostring(split(ClientIP,"]")[0]))), ClientIP )
| extend Keyword = iff(isnotempty(SubjectContainsWords), SubjectContainsWords, (iff(isnotempty(BodyContainsWords),BodyContainsWords,SubjectOrBodyContainsWords )))
| extend RuleDetail = case(OfficeObjectId contains '/' , tostring(split(OfficeObjectId, '/')[-1]) , tostring(split(OfficeObjectId, '\\')[-1]))
| summarize count(), StartTimeUtc = min(TimeGenerated), EndTimeUtc = max(TimeGenerated) by  Operation, UserId, ClientIPAddress, ResultStatus, Keyword, OriginatingServer, OfficeObjectId, RuleDetail
| extend AccountName = tostring(split(UserId, "@")[0]), AccountUPNSuffix = tostring(split(UserId, "@")[1])
| extend OriginatingServerName = tostring(split(OriginatingServer, " ")[0])

Risky sign-in with new MFA method

This query identifies scenarios of risky sign-ins tied to new MFA methods being added.

let mfaMethodAdded=CloudAppEvents
    | where ActionType =~ "Update user." 
    | where RawEventData has "StrongAuthenticationPhoneAppDetail"
    | where isnotempty(RawEventData.ObjectId) and isnotempty(RawEventData.Target[1].ID)
    | extend AccountUpn = tostring(RawEventData.ObjectId)
    | extend AccountObjectId = tostring(RawEventData.Target[1].ID)
    | project MfaAddedTimestamp=Timestamp,AccountUpn,AccountObjectId;
    let usersWithNewMFAMethod=mfaMethodAdded
    | distinct AccountObjectId;
    let hasusersWithNewMFAMethod = isnotempty(toscalar(usersWithNewMFAMethod));
    let riskySignins=AADSignInEventsBeta
    | where hasusersWithNewMFAMethod
    | where AccountObjectId in (usersWithNewMFAMethod)
    | where RiskLevelDuringSignIn in ("50","100") //Medium and High sign-in risk level.
    | where Application in ("Office 365 Exchange Online", "OfficeHome")
    | where isnotempty(SessionId)
    | project SignInTimestamp=Timestamp, Application, SessionId, AccountObjectId, IPAddress,RiskLevelDuringSignIn
    | summarize SignInTimestamp=argmin(SignInTimestamp,*) by Application,SessionId, AccountObjectId, IPAddress,RiskLevelDuringSignIn;
    mfaMethodAdded
    | join riskySignins on AccountObjectId
    | where MfaAddedTimestamp - SignInTimestamp < 6h //Time delta between risky sign-in and device registration less than 6h
    | project-away AccountObjectId1

Microsoft Security Copilot

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

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

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

Acknowledgments

We would like to thank Workday for their collaboration and assistance in responding to this threat.

Workday customers can refer to the guidance published by Workday on their community: https://community.workday.com/alerts/customer/1229867.

Learn more

For the latest security research from the Microsoft Threat Intelligence community, check out the Microsoft Threat Intelligence Blog.

To get notified about new publications and to join discussions on social media, follow us on LinkedIn, X (formerly Twitter), and Bluesky.

To hear stories and insights from the Microsoft Threat Intelligence community about the ever-evolving threat landscape, listen to the Microsoft Threat Intelligence podcast.

The post Investigating targeted “payroll pirate” attacks affecting US universities appeared first on Microsoft Security Blog.

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Jasper Sleet: North Korean remote IT workers’ evolving tactics to infiltrate organizations http://approjects.co.za/?big=en-us/security/blog/2025/06/30/jasper-sleet-north-korean-remote-it-workers-evolving-tactics-to-infiltrate-organizations/ Mon, 30 Jun 2025 19:17:49 +0000 Since 2024, Microsoft Threat Intelligence has observed remote IT workers deployed by North Korea leveraging AI to improve the scale and sophistication of their operations, steal data, and generate revenue for the North Korean government.

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

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Since 2024, Microsoft Threat Intelligence has observed remote information technology (IT) workers deployed by North Korea leveraging AI to improve the scale and sophistication of their operations, steal data, and generate revenue for the Democratic People’s Republic of Korea (DPRK). Among the changes noted in the North Korean remote IT worker tactics, techniques, and procedures (TTPs) include the use of AI tools to replace images in stolen employment and identity documents and enhance North Korean IT worker photos to make them appear more professional. We’ve also observed that they’ve been utilizing voice-changing software.

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

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

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

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

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

From North Korea to the world: The remote IT workforce

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

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

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

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

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

Tactics and techniques

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

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

Diagram of the North Korean IT workers ecosystem depicting the flow of how the workers set up profiles and accounts to apply for remote positions at a victim organization, complete interviews, and perform remote work using applications and laptop farms. The victim organization then pays the workers, who use a facilitator to transfer and launder the money back to North Korea.
Figure 1. The North Korean IT worker ecosystem

Crafting fake personas and profiles

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

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

Screenshot of a fake LinkedIn profile from a North Korean IT worker, claiming to be Joshua Desire from California as a Senior Software Engineer.
Figure 2. An example of a North Korean IT worker LinkedIn profile that has since been taken down.

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

Establishing digital footprint

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

Screenshot of a GitHub profile from a North Korean IT worker using the username codegod2222 and claiming to be a full stack engineer with 13 years of experience.
Figure 3. Example profile used by a North Korean IT worker that has since been taken down.

Using AI to improve operations

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

Photos of potential North Korean IT workers
Figure 4. Photos of potential North Korean IT workers

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

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

Image creation

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

Blurred screenshots of North Korean IT workers' resume and profile photos that used AI to modify the images. The individual appears the same in both images though the backgrounds vary as the left depicts an outdoors setting while the right image depicts the individual in an office building.
Figure 5. Use of AI apps to modify photos used for North Korean IT workers’ resumes and profiles
Two screenshots of North Korean IT worker resumes, which use different versions of the same photographed individual seen in Figure 5.
Figure 6. Examples of resumes for North Korean IT workers. These two resumes use different versions of the same photo.

Communications

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

Facilitators for initial access

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

Screenshot of an example job opportunity for a facilitator role, with the headline reading Exciting Job Opportunity A Simple, Secure Way to Land a Tech Job with details regarding the process to interview, provided benefits, and job functions.
Figure 7. Example of a job opportunity for a facilitator role

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

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

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

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

Defense evasion and persistence

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

Attribution

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

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

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

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

Defending against North Korean remote IT worker infiltration

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

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

Investigate

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

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

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

Monitor

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

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

Monitor for identifiable characteristics of North Korean remote workers

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

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

Monitor for activity associated with Jasper Sleet access

  • If RMM tools are used in your environment, enforce security settings where possible, to implement MFA:
    • If an unapproved installation is discovered, reset passwords for accounts used to install the RMM services. If a system-level account was used to install the software, further investigation may be warranted.
  • Monitor for impossible travel—for example, a supposedly US-based employee signing in from China or Russia.
  • Monitor for use of public VPNs such as Astrill. For example, IP addresses associated with VPNs known to be used by Jasper Sleet can be added to Sentinel watchlists. Or, Microsoft Defender for Identity can integrate with your VPN solution to provide more information about user activity, such as extra detection for abnormal VPN connections.
  • Monitor for signals of insider threats in your environment. Microsoft Purview Insider Risk Management can help identify potentially malicious or inadvertent insider risks.
  • Monitor for consistent user activity outside of typical working hours.

Remediate

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

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

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

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

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

Microsoft Defender XDR detections

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

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

Microsoft Defender XDR

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

  • Sign-in activity by a suspected North Korean entity

Microsoft Defender for Endpoint

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

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

Microsoft Defender for Identity

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

  • Atypical travel
  • Suspicious behavior: Impossible travel activity

Microsoft Entra ID Protection

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

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

Microsoft Defender for Cloud Apps

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

  • Impossible travel activity

Microsoft Security Copilot

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

  • Incident investigation
  • Microsoft User analysis
  • Threat actor profile

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

Hunting queries

Microsoft Defender XDR

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

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

Microsoft Sentinel

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

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

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

References

Acknowledgments

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

Learn more

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

For the latest security research from the Microsoft Threat Intelligence community, check out the Microsoft Threat Intelligence Blog

To get notified about new publications and to join discussions on social media, follow us on LinkedInX (formerly Twitter), and Bluesky

To hear stories and insights from the Microsoft Threat Intelligence community about the ever-evolving threat landscape, listen to the Microsoft Threat Intelligence podcast

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

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Unveiling RIFT: Enhancing Rust malware analysis through pattern matching http://approjects.co.za/?big=en-us/security/blog/2025/06/27/unveiling-rift-enhancing-rust-malware-analysis-through-pattern-matching/ Fri, 27 Jun 2025 18:30:00 +0000 As threat actors are adopting Rust for malware development, RIFT, an open-source tool, helps reverse engineers analyze Rust malware, solving challenges in the security industry.

The post Unveiling RIFT: Enhancing Rust malware analysis through pattern matching appeared first on Microsoft Security Blog.

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Today, Microsoft Threat Intelligence Center is excited to announce the release of RIFT, a tool designed to assist malware analysts automate the identification of attacker-written code within Rust binaries. Known for its efficiency, type safety, and robust memory safety, Rust has increasingly become a tool for creating malware, especially among financially motivated groups and nation-state entities. This shift has introduced new challenges for malware analysts as the unique characteristics of Rust binaries make static analysis more complex.

One of the primary challenges in reverse engineering malware developed with Rust lies in its layers of abstraction added through features such as memory safety and concurrency handling, making it more challenging to identify the behavior and intent of the malware. Compared to traditional languages, Rust binaries are often larger and more complex due to the incorporation of extensive library code. Consequently, reverse engineers must undertake the demanding task of distinguishing attacker-written code from standard library code, necessitating advanced expertise and specialized tools.

To address these pressing challenges, Microsoft Threat Intelligence Center has developed RIFT. RIFT underscores the growing need for specialized tools as cyber threat actors continue to leverage Rust’s features to evade detection and complicate analysis. The adoption of Rust by threat actors is a stark reminder of the ever-changing tactics employed in the cyber domain, and the increasing sophistication required to combat these threats effectively. In this blog post, we explore how threat actors are increasingly adopting Rust for malware development due to its versatility and how RIFT can be used to combat this threat by enhancing the efficiency and accuracy of Rust-based malware analysis.

Threat actors continue adopting Rust

As Rust gains popularity as a rapidly growing programming language, its use by malware authors is becoming more noticeable. Over the past five years, Microsoft Threat Intelligence Center and the broader security industry have observed financially motivated and state-supported groups increasingly using Rust for malware development.

Timeline from left to right: In December 2021 a Rust ransomware BlackCat report was released followed by Hive ransomware being rewritten in Rust in June 2022. In May 2023, Rust-based information stealers abused GitHub Codespace, then in March 2025 a report on Rust ransomware RALord was released, and finally in May 2025 the popular malware family AsyncRAT was rewritten in Rust.
Figure 1. Timeline of Rust-based threats

In 2021, the group behind the notorious BlackCat ransomware was among the first significant entities in the ransomware field to write their malicious programs in Rust. Following the appearance of the first malware families written in Rust, reverse engineers indicated that such malware presents a unique challenge for analysis.

Subsequently, several other groups began developing or rewriting their tools in the programming language. Nation-state threat actors have also selectively developed their malware in Rust.

Rust is a versatile language known for its performance, type safety, concurrency, and memory safety. While these features benefit legitimate development, they also complicate static analysis of malicious files. The community has extensively addressed many of these challenges. One of the core issues in analyzing Rust binaries is differentiating between library code and code written by malware authors.

To illustrate the significance of this problem, Microsoft Threat Intelligence Center conducted a simple experiment. A small PE EXE file that downloads data from a website and saves it on disk as sample_data.txt is generated with Microsoft 365 Copilot. The program is first compiled in C++ and then in Rust. The C++ program is compiled using Microsoft Visual C++ (MSVC) with Visual Studio 2022, in release mode for the 64-bit architecture and dynamically linked, using default settings. The Rust binary is compiled using compiler version rustc 1.89.0-nightly (16d2276fa 2025-05-16), also in release mode and with default settings.

Screenshot of code depicting a simple downloader program in C++ (or CPP) to the left and Rust to the right.
Figure 2. Simple downloader program in C++ to the left and Rust to the right

Next, both programs are loaded into IDA Pro, and a simple complexity analysis is performed by counting and comparing the number of disassembled and identified functions. Additionally, functions are categorized as annotated or not annotated. An annotated function is one that is automatically detected by IDA’s built-in signatures or algorithms. It should be noted that IDA has capabilities to enhance library recognition, but these were not used for this experiment.

While both programs implement similar functionalities, the total number of disassembled functions in the C++ program is lower than 100, while the Rust programs pack almost 10,000 functions. Furthermore, the size of the C++ program is lower than 20 KB, while the Rust program is larger than 3 MB.

Programs written in Rust are typically statically linked, embedding all dependencies directly into the executable. As a result, binaries are larger with a high volume of functions, requiring analysts to distinguish first between third-party library code and attacker-authored logic.

To address this key problem, Microsoft Threat Intelligence Center is releasing an internally developed tool: RIFT.

This open-source project is designed to help reverse engineers and analysts more efficiently identify attacker-authored logic within Rust-based malware.

From source code to binary

Diagram of the Rust developer toolset depicting the update manager rustup in the middle as it updates and manages cargo and rustc versions. One the left, the Rust compiler rustc engages with the hot pre-compiled compilation tools at static.rust-lang,org. On the right, the package manager cargo engages with the Rust community's crate registry at crates.io.
Figure 3. Overview of Rust developer toolset

Before delving into the inner workings of RIFT, it is essential to have a fundamental understanding of how Rust binaries are compiled. As illustrated in the diagram above, Rust developers typically engage with three primary components and two endpoints:

  • cargo – The package manager
  • rustc – The Rust compiler
  • rustup – The Rust update manager
  • static.rust-lang.org – S3 bucket that hosts pre-compiled compilers and toolchains
  • crates.io – Rust community’s crate registry

Once a developer has conceptualized what they intend to develop, a typical workflow may proceed as follows:

  1. Using the cargo tool, the developer initializes a new projected named “test”.
  2. They opt not to use the latest Rust compiler but a specific version. They execute rustup install 1.84.0-x86_64-pc-windows-msvc to install the desired compiler version and configure the project to use the installed compiler.
  3. They determine that their project should communicate via HTTP and incorporate a third-party dependency. They run cargo add request to install the latest version of the third-party library, request.

Following these steps will result in a fully configured project. Upon completion, the developer may run cargo build to finalize the binary, compiling the project.

Static artifacts and where to find them

Reverse engineers are usually handed the final development product of the malware author, oftentimes without information such as the compiler used or third-party dependencies. While it is highly likely that malware authors use the same tools as reverse engineers for development, no insights into the exact environment are available.

However, understanding the development toolchain can assist in quickly distinguishing library code from author written logic. Fortunately, various indicators can be extracted that provide insights.

Rust compiler version

Rust binaries typically include metadata from the compiler that identifies the Rust version used to compile the binary. A config.toml file is provided alongside pre-compiled Rust compilers and toolchains. This configuration file contains the commit hash and the corresponding Rust compiler version of the pre-compiled product. By extracting the commit hash from the final binary output, it is possible to map the Git commit hash back to the appropriate Rust compiler version by parsing all available config.toml files from the official release channels.

Rust crates

As mentioned above, cargo is used to add dependencies to a project. Next to the Git commit hash, metadata extracted from Rust binaries also include the statically linked dependencies and their versions.

Screenshot of the extractable dependencies, like rayon-core-1.12.1 and orion-0.19.9, from strings.
Figure 4. Extractable dependencies from strings

The above image shows how filtering for certain strings can display which dependencies were likely statically linked into RALord ransomware.

Introducing RIFT

RIFT is an open-source tool consisting of a set of IDA Pro (supporting versions >=9.0) plugins and Python scripts that aim to assist reverse engineers and other software analysts in annotating library code in Rust malware. It essentially consists of three components:

RIFT Static Analyzer: IDA Pro plugin to extract the Rust compiler commit hash and embedded dependencies from a binary.

RIFT Generator: A Python program to automate the process of Rust compiler identification, FLIRT signature generation of used Rust compiler and dependencies, as well as automation of binary diffing.

RIFT Diff Applier: IDA Pro plugin to consume binary diffing information generated by RIFT Generator.

Extracting static information with RIFT Static Analyzer

In the previous section, we listed which indicators can be extracted from Rust binaries that give insights into which Rust compiler and dependencies were used. RIFT Static Analyzer automates the extraction process and stores the information in a JSON file for further processing. Furthermore, the plugin also extracts the architecture the binary was compiled for and the target operating system. In the below image, the target operating system is labeled as target_triple.

A screenshot of a computer
Figure 5. Overview of RIFT Static Analyzer

RIFT Generator: Automating FLIRT signature generation and auto diffing

Information gathered and stored by RIFT Static Analyzer can then be further processed by RIFT Generator.

Screenshot of code depicting the RIFT Generator command line options, such as -h or --help to show this help message and exit, or --flirt to enable flirt signature generation.
Figure 6. RIFT Generator command line options

The Python program automates the process of compilation, data collection, FLIRT signature generation, and binary comparison.

It is essentially a wrapper around the following tools:

  • Cargo (Rust package manager) to manage the downloading and compiling of dependencies
  • Hexray’s FLAIR tools, specifically sigmake.exe and pcf.exe, to generate FLIRT signatures
  • Hexray’s text interface version of IDA, idat.exe, to automate binary analysis and disassembly
  • The open-source tool Diaphora to facilitate binary diffing
Diagram of RIFT Generator phases. First is the compilation phase to put a wrapper around cargo and rustup, next is the collect phase to collect artifacts from the compilation phase. Third is the FLIRT signature generation which puts a wrapper around pcf and sigmake, then in the fourth phase is disassembly analysis and SQLite generation to put a wrapper around idat.exe and Diaphora. Finally, the fifth phase is SQLite diffing and merging to put a wrapper around Diaphora and automate diffing.
Figure 7. Phases of RIFT Generator

The above image provides an overview of the phases RIFT Generator processes through. RIFT Generator reads the JSON file produced by RIFT Static Analyzer and downloads the corresponding Rust compiler, as well as the dependencies.

It is worth noting that upon completion of phase 1, both the code of the downloaded compiler and compiled crates are compressed as COFF files into RLIB files. RLIB is essentially a Rust-specific archive format similar to TAR. Once decompressed in phase 2, the COFF files are extracted and further processed.

FLIRT signatures and binary diffing

To provide information necessary for annotating library code in Rust binaries accurately, RIFT uses two known techniques for pattern matching: FLIRT signatures and binary diffing.

FLIRT stands for Fast Library Identification and Recognition Technology and enables IDA to identify standard library functions produced by its supported compilers. A characteristic of this technology is that library recognition is very precise. Therefore, functions that have a high similarity may not be flagged by FLIRT signatures due to their strict criteria.

Additionally, RIFT automates the process of binary diffing the collected COFF files against the target binary by leveraging IDA’s command line utility (idat.exe) and the Diaphora plugin.

Diagram of batch binary diffing process. First is the disassembly analysis and SQLite generation, next is the batch binary diffing, and finally is the merging of diffing results to ultimately be consumed by the RIFT Diff Applier plugin.
Figure 8. Overview of experimental batch binary diffing process

In general, both approaches have their own advantages and disadvantages, which are listed below.

FLIRT signatures approachBinary diffing approach
Highly reliable annotation, low false positive rateHigher false positive rate, but less strict and can fill gaps where FLIRT signatures fail due to strictness
With RIFT, in majority of cases, FLIRT signatures can be generated quicklyIn current state, batch binary diffing approach might take multiple hours
Not well applicable if dependencies and Rust compiler version are not availableApproach might yield useful results even if Rust compiler version and dependencies were not available

Consuming binary diffing information

If the binary diffing approach is applied, a second IDA plugin called RIFT Diff Applier can be used to apply the diffing results. In contrast to FLIRT signatures, the RIFT Diff Applier offers analysts an interactive, semi-manual method for identifying library code. It operates in two modes:

  1. Interactive mode
  2. Auto rename mode
Screenshot of the GUI of the RIFT Diff Applier, requesting the JSON file to import, whether to enable auto renaming or name demangling, and selections for the ratio and the auto rename ratio.
Figure 9. GUI of RIFT Diff Applier

By default, symbol names in COFF files are mangled. Consequently, if RIFT Generator generates the binary diffing information and stores it in the JSON format, the symbol names are also mangled. To address this issue, enabling Name Demangling can assist in attempting to demangle these names. We are continuously improving the tool, and currently, rust-demangler is being used for this purpose.

For both modes, a minimum similarity ratio can be specified. Functions will only be displayed or renamed if they meet or exceed the specified similarity threshold. Once the user clicks “OK”, a new window will appear in IDA with the title RIFT. Users can now right click on a function name and display the top three matching functions with the highest similarity determined through binary diffing or use the CTRL+X shortcut.

Screenshot of the RIFT window in IDA displaying the top matching functions.
Figure 10. RIFT window in IDA displaying top matching functions

Applying RIFT on RALord ransomware

Having introduced the functionalities of RIFT, we will now examine its practical application in analyzing RALord ransomware and how RIFT’s FLIRT signature generation can be used to immensely reduce time identifying library functions in RALord.

First, RIFT Static Analyzer is used to dump the extractable dependencies, Git commit hash of the Rust compiler, target architecture, and target operating system. Next, the information is fed into RIFT Generator.

Once RIFT Generator has finished generating FLIRT signatures, they can either be loaded one by one manually or by using our script shared in the RIFT GitHub repository named “ida_apply_flirt_from_folder.py”.

The image below compares parts of the main function before and after application of RIFT. After applying the FLIRT signatures generated from the extracted dependencies and Rust compiler, the majority of library and compiler code is identified in the main function. As a result, reverse engineers can focus solely on the threat actor code instead of spending time weeding out the library code.

Screenshot depicting decompiled code before and after FLIRT signature application.
Figure 11. Comparing decompiled code before and after applying generated FLIRT signatures

Applying RIFT on SPICA

In some use cases, FLIRT signature application might not be enough, for example when conducting a deep dive. RIFT’s binary diffing approach can provide additional information to improve library code recognition in addition to FLIRT signatures.

Having demonstrated the effectiveness of RIFT in applying FLIRT signatures to streamline the analysis of RALord ransomware, we now turn our focus to applying the binary diffing approach on SPICA, a backdoor written in Rust. This transition highlights scenarios where FLIRT signatures alone might be insufficient, necessitating a deeper, complementary analysis.

Similar to before, RIFT Static Analyzer is used first and the extracted information is fed into RIFT Generator. However, this time, we apply FLIRT signature generation and binary diffing.

Screenshot of code depicting enabling FLIRT signature generation and binary diffing
Figure 12. Enabling FLIRT signature generation and binary diffing

To use the binary diffing approach, Diaphora must be used first to generate the corresponding SQLite file. It is worth noting that depending on the size of the binary and extracted dependencies, the binary diffing procedure can take multiple hours.

Once done, RIFT Diff Applier can be used to load the binary diffing output file.

Screenshot of the Riff Diff Applier in use displaying several windows of code and functions
Figure 13. Rift Diff Applier in use

A benefit of this approach is that for certain functions where FLIRT signatures failed to properly label the library function due to its strictness, RIFT Diff Applier can provide useful and reliable information where the similarity is high. Furthermore, thinking about detection engineering, the approach can also help identify or filter out potential library functions, especially when writing signatures on code segments.

Afterwords: Open sourcing RIFT

Rust’s strong performance, safety-focused design, cross-compilation support, and concurrency features have led to its increased adoption by threat actors for developing complex malware. This growing shift towards Rust represents a yet another evolution in the threat landscape, enabling attackers to create malware that is not more resistant to detection and analysis.

For malware analysts, this trend introduces a daunting set of challenges. Rust’s innovative features often result in binaries that are harder to decompile and analyze, making reverse engineering a time-intensive process. Analysts are frequently left grappling with unfamiliar patterns and library-heavy outputs, which further complicate their efforts to dissect malware and develop detection methods.

To address these challenges, we are proud to announce the open sourcing of RIFT. Designed to help accelerate Rust malware analysis by assisting reverse engineers to recognize library code in Rust malware through FLIRT signatures and binary diffing, RIFT further reinforces global efforts to equip security professionals with proper tools to defend against threats. By making RIFT freely available to the cybersecurity community, we aim to foster collaboration and innovation in combating the rise of Rust-based malware. We would like to extend a special thanks to the author of the Diaphora project for their invaluable contribution to the reverse engineering community.

Microsoft’s ongoing research and development efforts, including the creation of tools like RIFT, underscore our commitment to protecting customers and securing the cyber landscape. By enhancing the efficiency and accuracy of malware analysis, we aim to keep pace with evolving threats and ensure the safety of users worldwide. This research highlights the critical need for advanced security measures to safeguard against such increasingly sophisticated cyber threats.

References

Acknowledgments

Learn more

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

For the latest security research from the Microsoft Threat Intelligence community, check out the Microsoft Threat Intelligence Blog

To get notified about new publications and to join discussions on social media, follow us on LinkedIn, X (formerly Twitter), and Bluesky

To hear stories and insights from the Microsoft Threat Intelligence community about the latest changes in the broader threat landscape, listen to the Microsoft Threat Intelligence podcast

The post Unveiling RIFT: Enhancing Rust malware analysis through pattern matching appeared first on Microsoft Security Blog.

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Defending against evolving identity attack techniques http://approjects.co.za/?big=en-us/security/blog/2025/05/29/defending-against-evolving-identity-attack-techniques/ Thu, 29 May 2025 17:00:00 +0000 Threat actors continue to develop and leverage various techniques that aim to compromise cloud identities. Despite advancements in protections like multifactor authentication (MFA) and passwordless solutions, social engineering remains a key aspect of phishing attacks. Implementing phishing-resistant solutions, like passkeys, can improve security against these evolving threats.

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

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

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

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

Pre-compromise techniques for stealing identities

Modern phishing techniques attempt to defeat authentication flows

Adversary-in-the-middle (AiTM)

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

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

Screenshot of Storm-0485's fake LinkedIn verify account lure stating Account Action Required with a button reading Verify Account and an alternative LinkedIn URL to copy and paste if the button does not work.
Figure 1. Example of Storm-0485’s fake LinkedIn verify account lure

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

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

Device code phishing

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

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

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

Screenshot of the OAuth app prompt requesting permissions for an unverified Share-File Point Document
Figure 2. OAuth app prompt seeks account permissions

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

Device join phishing

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

Lures remain an effective phishing weapon

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

Impersonation lures

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

Screenshot of Star Blizzard's file share spear-phishing email showing a redacted user shared a file with a button to Open the shared PDF. Clicked the Open button displays the embedded link was changed from a legitimate URL to an actor-controlled one.
Figure 3. Star Blizzard file share spear-phishing email

QR codes

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

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

Use of AI

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

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

Screenshot of a suspected AI-generated phishing email claiming to be hiring various services for a wedding.
Figure 4. One of multiple suspected AI-generated phishing email in a widespread phishing campaign

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

Phishing risks continue to expand beyond email

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

Teams phishing

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

Leveraging social media

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

Post-compromise identity attacks

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

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

AiTM phishing crafted using legitimate company resources

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

Intra-organization device code phishing

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

Screenshot of Storm-2372 lateral movement attempt containing a device code phishing payload
Figure 5. Storm-2372 lateral movement attempt contains device code phishing payload

Defending against credential phishing and social engineering

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

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

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

As part of hardening cloud identities, authentication using passwordless solutions like passkeys is essential, and implementing MFA remains a core pillar in identity security. Use the Microsoft Authenticator app for passkeys and MFA, and complement MFA with conditional access policies, where sign-in requests are evaluated using additional identity-driven signals. Conditional access policies can also be scoped to strengthen privileged accounts with phishing resistant MFA. Your passkey and MFA policy can be further secured by only allowing MFA and passkey registrations from trusted locations and devices.

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

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

Stay vigilant and prioritize your security at every step.

Recommendations

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

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

Learn more  

For the latest security research from the Microsoft Threat Intelligence community, check out the Microsoft Threat Intelligence Blog

To get notified about new publications and to join discussions on social media, follow us on LinkedIn, X (formerly Twitter), and Bluesky

To hear stories and insights from the Microsoft Threat Intelligence community about the ever-evolving threat landscape, listen to the Microsoft Threat Intelligence podcast

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

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Lumma Stealer: Breaking down the delivery techniques and capabilities of a prolific infostealer http://approjects.co.za/?big=en-us/security/blog/2025/05/21/lumma-stealer-breaking-down-the-delivery-techniques-and-capabilities-of-a-prolific-infostealer/ Wed, 21 May 2025 16:00:00 +0000 Over the past year, Microsoft Threat Intelligence observed the persistent growth and operational sophistication of Lumma Stealer, an info-stealing malware used by multiple financially motivated threat actors to target various industries. Microsoft, partnering with others across industry and international law enforcement, facilitated the disruption of Lumma infrastructure.

The post Lumma Stealer: Breaking down the delivery techniques and capabilities of a prolific infostealer appeared first on Microsoft Security Blog.

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Over the past year, Microsoft observed the persistent growth and operational sophistication of Lumma Stealer, an infostealer malware used by multiple financially motivated threat actors to target various industries. Our investigation into Lumma Stealer’s distribution infrastructure reveals a dynamic and resilient ecosystem that spans phishing, malvertising, abuse of trusted platforms, and traffic distribution systems. These findings underscore the importance of collaborative efforts to disrupt cybercrime. Microsoft, partnering with others across industry and international law enforcement, recently facilitated a disruption of Lumma infrastructure.

Lumma Stealer (also known as LummaC2) is a malware as a service (MaaS) offering that is capable of stealing data from various browsers and applications such as cryptocurrency wallets and installing other malware. Microsoft Threat Intelligence tracks the threat actor who developed and maintains the Lumma malware, command-and-control (C2) infrastructure, and the Lumma MaaS as Storm-2477. Affiliates who pay Storm-2477 for the service and operate their own Lumma campaigns access a panel to build the malware binary and manage the C2 communications and stolen information. We have observed ransomware threat actors like Octo Tempest, Storm-1607, Storm-1113, and Storm-1674 using Lumma Stealer in campaigns.

Unlike earlier infostealers that relied heavily on bulk spam or exploits, Lumma Stealer exemplifies a shift toward multi-vector delivery strategies. Its operators demonstrate resourcefulness and proficiency in impersonation tactics. The Lumma Stealer distribution infrastructure is flexible and adaptable. Operators continually refine their techniques, rotating malicious domains, exploiting ad networks, and leveraging legitimate cloud services to evade detection and maintain operational continuity. This dynamic structure enables operators to maximize the success of campaigns while complicating efforts to trace or dismantle their activities.

The growth and resilience of Lumma Stealer highlights the broader evolution of cybercrime and underscores the need for layered defenses and industry collaboration to counter threats. In this blog post, we share our analysis of Lumma Stealer and its infrastructure and provide guidance on how users and organizations can protect themselves from this threat. Microsoft remains committed to sharing insights, developing protections, and working with partners across industries to disrupt malicious ecosystems and safeguard users worldwide.

Heat map of Lumma Stealer infections around the world
Figure 1. Heat map detailing global spread of Lumma Stealer malware infections and encounters across Windows devices.

Lumma Stealer delivery techniques

Lumma Stealer leverages a broad and evolving set of delivery vectors. Campaigns often combine multiple techniques, dynamically adapting to evade detection and increase infection success rates. Delivery infrastructure is designed to be ephemeral, shifting rapidly across domains, platforms, and geographies to avoid takedowns.

  • Phishing emails: Lumma Stealer emails impersonate known brands and services to deliver links or attachments. These campaigns involve expertly crafted emails designed to evoke urgency, often masquerading as urgent hotel reservation confirmations or pending cancellations. The emails lead victims to cloned websites or malicious servers that deploy the Lumma payload to the targets’ environment.
  • Malvertising: Threat actors inject fake advertisements into search engine results, targeting software-related queries such as “Notepad++ download” or “Chrome update.” Clicking these poisoned links leads users to cloned websites that closely mimic legitimate vendors but instead deliver the Lumma Stealer.
  • Drive-by download on compromised websites: Threat actors were observed compromising groups of legitimate websites, typically through a particular vulnerability or misconfiguration. They modify site content by inserting malicious JavaScript. The JavaScript runs when sites are visited by unsuspecting users, leading to delivery of a payload, intermediary script, or displaying further lures to convince users to perform an action.
  • Trojanized applications: In many campaigns, cracked or pirated versions of legitimate applications are bundled with Lumma binaries and distributed through file-sharing platforms. These modified installers often contain no visible payload during installation, executing the malware silently post-launch.
  • Abuse of legitimate services and ClickFix: Public repositories like GitHub are abused and populated with scripts and binaries, often disguised as tools or utilities. A particularly deceptive method involves fake CAPTCHA pages, commonly observed in the ClickFix ecosystem. Targets are instructed to copy malicious commands into their system’s Run utility under the pretense of passing a verification check. These commands often download and execute Lumma directly in memory, using Base64 encoding and stealthy delivery chains.
  • Dropped by other malware: Microsoft Threat Intelligence observed other loaders and malware such as DanaBot delivering Lumma Stealer as an additional payload.

All these mechanisms reflect threat actor behavior that prioritizes abuse of user trust, manipulation of legitimate infrastructure, and multi-layered distribution chains designed to evade both technical and human defenses. The following sections discuss some examples of campaigns where the mentioned distribution methods were used to deliver Lumma Stealer.

Drive-by download campaign leveraging EtherHiding and ClickFix to deliver Lumma

In early April 2025, Microsoft observed a cluster of compromised websites leveraging EtherHiding and ClickFix techniques to install Lumma Stealer. EtherHiding is a technique that involves leveraging smart contracts on blockchain platforms like Binance Smart Chain (BSC) to host parts of malicious code. Traditional methods of blocking malicious code, such as IP or domain blocking or content-based detections, are less effective against EtherHiding because the code is embedded in the blockchain. Meanwhile, 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.

Attack flow diagram displaying the Lumma Stealer affiliate using the ClickFix technique to socially engineer users to ultimately download and deploy Lumma on their device, which exfiltrates targeted information to the attacker's C2 server.
Figure 2. Attack flow for ClickFix to Lumma Stealer

In this campaign, the JavaScript injected into compromised websites directly contacted BSC to retrieve the ClickFix code and lure, which was then presented to the target. Users needed to click the “I’m not a robot” prompt, at which point a command was copied into their clipboard. Users were then instructed to paste and launch this command via the Windows Run prompt. The command downloaded and initiated further code using mshta from check.foquh[.]icu.

Screenshot of a fake CAPTCHA on a compromised website stating "I'm not a robot" with a box for users to check
Figure 3. Compromised website used EtherHiding and ClickFix techniques to present a fake CAPTCHA lure to visitors
Screenshot of the injected JavaScript code
Figure 4. Snippet of the injected JavaScript after Base64 decoding. It implements the EtherHiding technique and communicates with data-seed-prebsc-1-s1.bnbchain[.]org to fetch ClickFix code.
Screenshot of the fake verification page with steps for the user to copy and paste a command that is malicious
Figure 5. This fake verification page is the final part of the ClickFix technique. It instructs users how to launch a malicious command. The command was silently copied into their clipboard during the previous step when they clicked “I’m not a robot”.

Email campaign targeting organizations in Canada to deliver Lumma Stealer

On April 7, 2025, Microsoft Threat Intelligence observed an email campaign consisting of thousands of emails targeting organizations in Canada. The emails used invoice lures for a fitness plan or an online education platform. The emails’ subject lines were personalized to include recipient-specific details such as “Invoice for [recipient email]”. Notably, the attack chain utilized multiple tools available for purchase on underground forums for traffic filtering and social engineering.

The emails contained URLs leading to the Prometheus traffic direction system (TDS) hosted on numerous compromised sites. The TDS in turn, redirected users to the attacker-controlled website binadata[.]com that hosted the ClickFix social engineering framework. Like the previous campaign, targets were instructed to click a “I’m not a robot” prompt and run malicious code via a multi-step process. The malicious code was an mshta command that downloaded and executed JavaScript from the IP address 185.147.125[.]174. The JavaScript ran a PowerShell command that downloaded more PowerShell code, which finally downloaded and launched a Lumma Stealer executable. Notably, Xworm malware was also bundled into this executable.

Diagram of the ClickFix attack flow depicting the Lumma Stealer affiliate redirecting users to the ClickFix framework. Users deploy Lumma Stealer and Xworm on their device, which exfiltrates targeted information to the attacker's C2 server.
Figure 6. Attack flow for ClickFix leading to Lumma Stealer targeting users in Canada
Screenshot of a fitness plan subscription themed email lure
Figure 7. Fitness plan subscription themed email lure
Screenshot of the ClickFix landing page requesting the user to prove whether they are a robot by following the instructions to launch a malicious command.
Figure 8. Screenshot of the ClickFix landing after Prometheus TDS redirection

Lumma Stealer malware analysis

The core Lumma Stealer malware is written in a combination of C++ and ASM. The malware author designed it as a MaaS offering. Threat actors can access the panel to build the malware binary and manage the C2 communications and stolen information. The core binary is obfuscated with advanced protection such as low-level virtual machine (LLVM core), Control Flow Flattening (CFF), Control Flow Obfuscation, customized stack decryption, huge stack variables, and dead codes, among others. These techniques are implemented on the critical functions to make static analysis difficult, as these can cause tools like Hex-Rays’ IDA fail to produce equivalent decompiled codes. In addition, most of the critical APIs are implemented via low-level syscalls and Heavens Gate Technology.

Lumma Stealer is designed to steal from browsers based on Chromium and Mozilla technology, including Microsoft Edge. In addition, it has the capability to install other malware or plugins, including Clipboard stealer plugin and coin miners, either by downloading to disk or directly in memory.

Process injection and process hollowing

Lumma loader may use process hollowing to inject its malicious payload into legitimate system processes like msbuild.exe, regasm.exe, regsvcs.exe, and explorer.exe. This technique enables execution under the guise of a trusted binary to bypass behavioral detection and endpoint monitoring tools.

Information-stealing capabilities

Lumma Stealer targets a comprehensive set of user data using a specialized collection routine for each type of data. These capabilities have evolved over time, and Microsoft Threat Intelligence has recently observed that the instructions for the target credentials are specified in the configuration file retrieved from the active C2 server. The configuration file is divided into several parts: the “ex” section that pertains to the target list of apps for cryptocurrency wallets and extensions, and “c” sections that pertain to the list of applications and configuration details for browsers, user file’s locations, and other applications.

  • Browser credentials and cookies: Lumma Stealer extracts saved passwords, session cookies, and autofill data from Chromium (including Edge), Mozilla, and Gecko-based browsers.
  • Cryptocurrency wallets and extensions: Lumma Stealer actively searches for wallet files, browser extensions, and local keys associated with wallets like MetaMask, Electrum, and Exodus.
  • Various applications: Lumma Stealer targets data from various virtual private networks (VPNs) (.ovpn), email clients, FTP clients, and Telegram applications.  
  • User documents: Lumma Stealer harvests files found on the user profiles and other common directories, especially those with .pdf, .docx, or .rtf extensions.
  • System metadata: Lumma Stealer collects host telemetry such as CPU information, OS version, system locale, and installed applications for tailoring future exploits or profiling victims.
A screenshot of the malware configuration file
Figure 9. Lumma Stealer configuration file

C2 communication

Lumma Stealer maintains a robust C2 infrastructure, using a combination of hardcoded tier 1 C2s that are regularly updated and reordered, and fallback C2s hosted as Steam profiles and Telegram channels that also point to the tier 1 C2s. The Telegram C2, if available, is always checked first, while the Steam C2 is checked only when all the hardcoded C2s are not active. To further hide the real C2 servers, all the C2 servers are hidden behind the Cloudflare proxy.

While Lumma Stealer affiliates share the tier 1 C2s, there is a capability to add a personal tier 1 C2 domain for an extra cost. The diagram below shows an overview of the Lumma Stealer infrastructure. All traffic is encrypted by HTTPS.

A diagram of a diagram
Figure 10. Lumma Stealer C2 communication

Different types of obfuscation are applied to each set of C2 servers. For example, the hardcoded list of C2s, and including the Telegram fallback C2 URL are protected with ChaCha20 crypto, while the Steam profile fallback C2 URL is encrypted using custom stack-based crypto algorithm that can change on each version of Lumma malware.

We have identified up to six versions of Lumma Stealer, and while each of these versions focuses on improving techniques to evade antivirus detections, there are also several changes in the C2 communication protocol and formats such as the C2 domains, URI path, POST data, and others. The core Lumma malware stores the build date as part of the embedded configuration to keep track of improvements, but in our investigation, we tracked major changes using the labels “version 1” through “version 6”.

Lumma Stealer keeps track of the active C2 for sending the succeeding commands. Each command is sent to a single C2 domain that is active at that point. In addition, each C2 command contains one or more C2 parameters specified as part of the POST data as form data. The parameters are:  

  • act: Indicates the C2 command. Note: This C2 parameter no longer exists in Lumma version 6.
  • ver: Indicates C2 protocol version. This value is always set to 4.0 and has never changed since the first version Lumma.
  • lid (for version 5 and below)/uid (for version 6): This ID identifies the Lumma client/operator and its campaign.
  • j (for version 5 and below )/cid (for version 6): This is an optional field that identifies additional Lumma features.
  • hwid: Indicates the unique identifier for the victim machine.
  • pid: Used in SEND_MESSAGE command to identify the source of the stolen data. A value of 1, indicates it came from the Lumma core process.

The following are some of the most common Lumma Stealer C2 commands and associated parameters:

  • PING / LIFE: Initial command to check if the C2 is active. Note: This command does not exist in version 6.
    • act=life
  • RECEIVE_MESSAGE: Command to download the stealer’s configuration. As noted above, this contains the specifications on the list of targets.
    • version 3 and below: act=recive_message&ver=4.0&lid=[<lid_value>]&j=[<j_value>]
    • version 4 and 5: act=receive_message&ver=4.0&lid=[<lid_value>]&j=[<j_value>]
    • version 6: uid=<uid_value>&cid=[<cid_value>]
  • SEND_MESSAGE: Command to send back stolen data in chunks. The C2 parameters are specified as individual section in the whole POST data. The fields included are act=send_message, hwid, pid, lid/uid, and j/cid. The act field was removed in version 6.
  • GET_MESSAGE: Command to download the second configuration. This configuration contains information about the plugins and additional malware to install on the target systems. We have observed that in most cases this command will respond with valid but empty records “[]”, meaning nothing to download. So far, we have observed Lumma Stealer installing an updated version of the Clipboard stealer plugin and coin miners.
    • versions 5 and below: act=get_message&ver=4.0&lid=[<lid_value>]&j=[<j_value>]&hwid=<hwid_value>
    • version 6: uid=<uid_value>&cid=[<cid_value>]&hwid=<hwid_value>

Microsoft Digital Crimes Unit (DCU) engineered tools that identify and map the Lumma Stealer C2 infrastructure. As part of the disruption announced on May 21, Microsoft’s DCU has facilitated the takedown, suspension, and blocking of approximately 2,300 malicious domains that formed the backbone of the Lumma Stealer infrastructure.  More details of this operation are presented in the DCU disruption announcement.

Recommendations

Microsoft Threat Intelligence 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.
  • Leverage phishing-resistant authentication methods such as FIDO Tokens, or Microsoft Authenticator with passkey. Avoid telephony-based MFA methods to avoid risks associated with SIM-jacking.
  • 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 with 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.

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 this threat as the following malware:

Microsoft Defender for Endpoint

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

  • Suspicious command in RunMRU registry
  • Possible Lumma Stealer activity
  • Information stealing malware activity
  • 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
  • Renamed AutoIt tool
  • Suspicious phishing activity detected
  • Suspicious implant process from a known emerging threat
  • A process was injected with potentially malicious code
  • Process hollowing detected
  • Suspicious PowerShell download or encoded command execution
  • A process was launched on a hidden desktop

Microsoft Defender for Office 365

Microsoft Defender for Office 365 identifies and blocks malicious emails. These alerts, however, can also be triggered by unrelated threat activity:

  • A potentially malicious URL click was detected
  • Email messages containing malicious URL removed after delivery
  • Email messages removed after delivery
  • A user clicked through to a potentially malicious URL
  • Suspicious email sending patterns detected
  • Email reported by user as malware or phish

Defender for Office 365 also detects and blocks Prometheus TDS, EtherHiding patterns, ClickFix landing pages.

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:

ClickFix commands execution

Identify ClickFix commands execution.

DeviceRegistryEvents
| where ActionType =~ "RegistryValueSet"
| where InitiatingProcessFileName =~ "explorer.exe"
| where RegistryKey has @"\CurrentVersion\Explorer\RunMRU"
| where RegistryValueData has "✅"
        or (RegistryValueData has_any ("powershell", "mshta", "curl", "msiexec", "^")
             and RegistryValueData matches regex "[\u0400-\u04FF\u0370-\u03FF\u0590-\u05FF\u0600-\u06FF\u0E00-\u0E7F\u2C80-\u2CFF\u13A0-\u13FF\u0530-\u058F\u10A0-\u10FF\u0900-\u097F]")
        or (RegistryValueData has "mshta" and RegistryValueName !~ "MRUList" and RegistryValueData !in~ ("mshta.exe\\1", "mshta\\1"))
        or (RegistryValueData has_any ("bitsadmin", "forfiles", "ProxyCommand=") and RegistryValueName !~ "MRUList")
        or ((RegistryValueData startswith "cmd" or RegistryValueData startswith "powershell")
            and (RegistryValueData has_any ("-W Hidden ", " -eC ", "curl", "E:jscript", "ssh", "Invoke-Expression", "UtcNow", "Floor", "DownloadString", "DownloadFile", "FromBase64String",  "System.IO.Compression", "System.IO.MemoryStream", "iex", "Invoke-WebRequest", "iwr", "Get-ADDomainController", "InstallProduct", "-w h", "-X POST", "Invoke-RestMethod", "-NoP -W", ".InVOKe", "-useb", "irm ", "^", "[char]", "[scriptblock]", "-UserAgent", "UseBasicParsing", ".Content")
              or RegistryValueData matches regex @"[-/–][Ee^]{1,2}[NnCcOoDdEeMmAa^]*\s[A-Za-z0-9+/=]{15,}"))

DPAPI decryption via AutoIT or .NET Framework processes

Identify DPAPI decryption activity originating from AutoIT scripts .NET Framework processes.

DeviceEvents
| where ActionType == "DpapiAccessed"
| where InitiatingProcessVersionInfoInternalFileName == "AutoIt3.exe"
      or InitiatingProcessFolderPath has "\\windows\\microsoft.net\\framework\\"
      or InitiatingProcessFileName =~ "powershell.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", "Chromium", "Opera", "Opera GX", "IMAP Password", "Brave Browser", "AVG Secure Browser") 
        and opType =~ "SPCryptUnprotect"
| project Timestamp, ReportId, DeviceId, ActionType, InitiatingProcessParentFileName, InitiatingProcessFileName, InitiatingProcessVersionInfoInternalFileName, InitiatingProcessCommandLine, AdditionalFields, dataDesp, opType

Sensitive browser file access via AutoIT or .NET Framework processes

Identify .NET Framework processes (such as RegAsm.exe, MSBuild.exe, etc.) 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" 
      or InitiatingProcessFolderPath has "\\windows\\microsoft.net\\framework\\" 
      or InitiatingProcessFileName =~ "powershell.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

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, on X (formerly Twitter) at https://x.com/MsftSecIntel, and Bluesky at https://bsky.app/profile/threatintel.microsoft.com.

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 Lumma Stealer: Breaking down the delivery techniques and capabilities of a prolific infostealer appeared first on Microsoft Security Blog.

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Threat actors leverage tax season to deploy tax-themed phishing campaigns http://approjects.co.za/?big=en-us/security/blog/2025/04/03/threat-actors-leverage-tax-season-to-deploy-tax-themed-phishing-campaigns/ Thu, 03 Apr 2025 16:00:00 +0000 http://approjects.co.za/?big=en-us/security/blog/?p=138252 As Tax Day approaches in the United States on April 15, Microsoft has detected several tax-themed phishing campaigns employing various tactics. These campaigns use malicious hyperlinks and attachments to deliver credential phishing and malware including RaccoonO365, AHKBot, Latrodectus, BruteRatel C4 (BRc4), and Remcos.

The post Threat actors leverage tax season to deploy tax-themed phishing campaigns appeared first on Microsoft Security Blog.

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March 2026 update: Every year, there is an observable uptick in tax-themed campaigns as Tax Day (April 15) approaches in the United States, and 2026 is no different: When tax season becomes cyberattack season: Phishing and malware campaigns using tax-related lures.


As Tax Day approaches in the United States on April 15, Microsoft has observed several phishing campaigns using tax-related themes for social engineering to steal credentials and deploy malware. These campaigns notably use redirection methods such as URL shorteners and QR codes contained in malicious attachments and abuse legitimate services like file-hosting services and business profile pages to avoid detection. These campaigns lead to phishing pages delivered via the RaccoonO365 phishing-as-a-service (PhaaS) platform, remote access trojans (RATs) like Remcos, and other malware like Latrodectus, BruteRatel C4 (BRc4), AHKBot, and GuLoader.

Every year, threat actors use various social engineering techniques during tax season to steal personal and financial information, which can result in identity theft and monetary loss. These threat actors craft campaigns that mislead taxpayers into revealing sensitive information, making payments to fake services, or installing malicious payloads. Although these are well-known, longstanding techniques, they could still be highly effective if users and organizations don’t use advanced anti-phishing solutions and conduct user awareness and training. 

In this blog, we share details on the different campaigns observed by Microsoft in the past several months leveraging the tax season for social engineering. This also includes additional recommendations to help users and organizations defend against tax-centric threats. Microsoft Defender for Office 365 blocks and identifies the malicious emails and attachments used in the observed campaigns. Microsoft Defender for Endpoint also detects and blocks a variety of threats and malicious activities related but not limited to the tax threat landscape. Additionally, the United States Internal Revenue Service (IRS) does not initiate contact with taxpayers by email, text messages or social media to request personal or financial information.

BruteRatel C4 and Latrodectus delivered in tax and IRS-themed phishing emails

On February 6, 2025, Microsoft observed a phishing campaign that involved several thousand emails targeting the United States. The campaign used tax-themed emails that attempted to deliver the red-teaming tool BRc4 and Latrodectus malware. Microsoft attributes this campaign to Storm-0249, an access broker active since 2021 and known for distributing, at minimum, BazaLoader, IcedID, Bumblebee, and Emotet malware. The following lists the details of the phishing emails used in the campaign:

Example email subjects:

  • Notice: IRS Has Flagged Issues with Your Tax Filing
  • Unusual Activity Detected in Your IRS Filing
  • Important Action Required: IRS Audit

Example PDF attachment names:

  • lrs_Verification_Form_1773.pdf
  • lrs_Verification_Form_2182.pdf
  • lrs_Verification_Form_222.pdf

The emails contained a PDF attachment with an embedded DoubleClick URL that redirected users to a Rebrandly URL shortening link. That link in turn redirected the browser to a landing site that displayed a fake DocuSign page hosted on a domain masquerading as DocuSign. When users clicked the Download button on the landing page, the outcome depended on whether their system and IP address were allowed to access the next stage based on filtering rules set up by the threat actor:

  • If access was permitted, the user received a JavaScript file from Firebase, a platform sometimes misused by cybercriminals to host malware. If executed, this JavaScript file downloaded a Microsoft Software Installer (MSI) containing BRc4 malware, which then installed Latrodectus, a malicious tool used for further attacks.
  • If access was restricted, the user received a benign PDF file from royalegroupnyc[.]com. This served as a decoy to evade detection by security systems.
Screenshot of a sample phishing email claiming to be from the IRS
Figure 1. Sample phishing email that claims to be from the IRS
Screenshot of a fake DocuSign page that leads to a malicious PDF file.
Figure 2. PDF attachment masquerading as a DocuSign document

Latrodectus is a loader primarily used for initial access and payload delivery. It features dynamic command-and-control (C2) configurations, anti-analysis features such as minimum process count and network adapter check, C2 check-in behavior that splits POST data between the Cookie header and POST data. Latrodectus 1.9, the malware’s latest evolution first observed in February 2025, reintroduced scheduled tasks for persistence and added the ability to run Windows commands via the command prompt.

BRc4 is an advanced adversary simulation and red-teaming framework designed to bypass modern security defenses, but it has also been exploited by threat actors for post-exploitation activities and C2 operations.

Between February 12 and 28, 2025, tax-themed phishing emails were sent to over 2,300 organizations, mostly in the United States in the engineering, IT, and consulting sectors. The emails had an empty body but contained a PDF attachment with a QR code and subjects indicating that the documents needed to be signed by the recipient. The QR code pointed to a hyperlink associated with a RaccoonO365 domain: shareddocumentso365cloudauthstorage[.]com. The URL included the recipient email as a query string parameter, so the PDF attachments were all unique. RaccoonO365 is a PhaaS platform that provides phishing kits that mimic Microsoft 365 sign-in pages to steal credentials. The URL was likely a phishing page used to collect the targeted user’s credentials.

The emails were sent with a variety of display names, which are the names that recipients see in their inboxes, to make the emails appear as if they came from an official source. The following display names were observed in these campaigns:

  • EMPLOYEE TAX REFUND REPORT
  • Project Funding Request Budget Allocation
  • Insurance Payment Schedule Invoice Processing
  • Client Contract Negotiation Service Agreement
  • Adjustment Review Employee Compensation
  • Tax Strategy Update Campaign Goals
  • Team Bonus Distribution Performance Review
  • proposal request
  • HR|Employee Handbooks
Screenshot of a PDF file that features a QR code purporting to lead to a file named Q1 Tax Refundreport.pdf
Figure 3. Screenshot of the opened PDF with the QR code

AHKBot delivered in IRS-themed phishing emails

On February 13, 2025, Microsoft observed a campaign using an IRS-themed email that targeted users in the United States. The email’s subject was IRS Refund Eligibility Notification and the sender was jessicalee@eboxsystems[.]com.

The email contained a hyperlink that directed users to download a malicious Excel file. The link (hxxps://business.google[.]com/website_shared/launch_bw[.]html?f=hxxps://historyofpia[.]com/Tax_Refund_Eligibility_Document[.]xlsm) abused an open redirector on what appeared to be a legitimate Google Business page. It redirected users to historyofpia[.]com, which was likely compromised to host the malicious Excel file. If the user opened the Excel file, they were prompted to enable macros, and if the user enabled macros, a malicious MSI file was downloaded and run.

The MSI file contained two files. The first file, AutoNotify.exe, is a legitimate copy of the executable used to run AutoHotKey script files. The second file, AutoNotify.ahk, is an AHKBot Looper script which is a simple infinite loop that receives and runs additional AutoHotKey scripts. The AHKBot Looper was in turn observed downloading the Screenshotter module, which includes code to capture screenshots from the compromised device. Both Looper and Screenshotter used the C2 IP address 181.49.105[.]59 to receive commands and upload screenshots.

Screenshot of an email claiming to be from the IRS. The email contains a link to a malicious Excel file.
Figure 4. Screenshot of the email showing the link to download a malicious Excel file
Screenshot of macro code that installs a malicious MSI file
Figure 5. Macro code to install the malicious MSI file from hxxps://acusense[.]ae/umbrella/

GuLoader and Remcos delivered in tax-themed phishing emails

On March 3, 2025, Microsoft observed a tax-themed phishing campaign targeting CPAs and accountants in the United States, attempting to deliver GuLoader and Remcos malware. The campaign, which consisted of less than 100 emails, began with a benign rapport-building email from a fake persona asking for tax filing services due to negligence by a previous CPA. If the recipient replied, they would then receive a second email with the malicious PDF. This technique increases the click rates on the malicious payloads due to the established rapport between attacker and recipient.

The malicious PDF attachment contained an embedded URL. If the attachment was opened and the URL clicked, a ZIP file was downloaded from Dropbox. The ZIP file contained various .lnk files set up to mimic tax documents. If launched by the user, the .lnk file uses PowerShell to download a PDF and a .bat file. The .bat file in turn downloaded the GuLoader executable, which then installed Remcos.

Screenshot of a phishing email wherein the sender requests for tax filing services from the target.
Figure 6. Sample phishing email shows the original benign request for tax filing services, followed by another email containing a malicious PDF attachment if the target replies.
A close up of a web page
Figure 7. The PDF attachment contains a prominent blue “Download” button that links to download of the malicious payload. The button is overlaid over a blurred background mimicking a “W-2” tax form, which further contributes to the illusion of the attachment being a legitimate tax file.

GuLoader is a highly evasive malware downloader that leverages encrypted shellcode, process injection, and cloud-based hosting services to deliver various payloads, including RATs and infostealers. It employs multiple anti-analysis techniques, such as sandbox detection and API obfuscation, to bypass security defenses and ensure successful payload execution.

Remcos is a RAT that provides attackers with full control over compromised systems through keylogging, screen capturing, and process manipulation while employing stealth techniques to evade detection.

Mitigation and protection guidance

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.
  • Turn on Zero-hour auto purge (ZAP) in Defender for 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.
  • Pilot and deploy phishing-resistant authentication methods for users.
  • Enforce multifactor authentication (MFA) on all accounts, remove users excluded from MFA, and strictly require MFA from all devices in all locations at all times.
  • 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 contain exploits and host malware.
  • Educate users about using the browser URL navigator to validate that upon clicking a link in search results they have arrived at an expected legitimate domain.
  • Enable network protection to prevent applications or users from accessing malicious domains and other malicious content on the internet.
  • 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 Office 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 that are used in phishing and other attacks.
  • 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 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.
  • Run endpoint detection and response (EDR) in block mode, so that Defender for Endpoint can block malicious artifacts, even when your non-Microsoft antivirus doesn’t 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 detected post-breach.

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 used in the campaigns shared in this blog as the following:

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.

  • Possible Latrodectus activity
  • Brute Ratel toolkit related behavior
  • A file or network connection related to ransomware-linked actor Storm-0249 detected
  • Suspicious phishing activity detected

Microsoft Defender for Office 365

Microsoft Defender for Office 365 offers enhanced solutions for blocking and identifying malicious emails. These alerts, however, can be triggered by unrelated threat activity.

  • A potentially malicious URL click was detected 
  • Email messages containing malicious URL removed after delivery
  • Email messages removed after delivery
  • A user clicked through to a potentially malicious URL
  • Suspicious email sending patterns detected
  • Email reported by user as malware or phish

Defender for Office 365 also detects the malicious PDF attachments used in the phishing campaign launched by Storm-0249.

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 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.

Furthermore, listed below are some sample queries utilizing Sentinel ASIM Functions for threat hunting across both Microsoft first-party and third-party data sources.

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

let lookback = 7d;
let ioc_ip_addr = dynamic(["181.49.105.59 "]); 
_Im_NetworkSession(starttime=todatetime(ago(lookback)), endtime=now())
| where DstIpAddr in (ioc_ip_addr) 
| summarize imNWS_mintime=min(TimeGenerated), imNWS_maxtime=max(TimeGenerated), EventCount=count() by SrcIpAddr, DstIpAddr, DstDomain, Dvc, EventProduct, EventVendor

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

let ioc_sha_hashes=dynamic(["fe0b2e0fe7ce26ae398fe6c36dae551cb635696c927761738f040b581e4ed422","bb3b6262a288610df46f785c57d7f1fa0ebc75178c625eaabf087c7ec3fccb6a","9728b7c73ef25566cba2599cb86d87c360db7cafec003616f09ef70962f0f6fc",
"3c482415979debc041d7e4c41a8f1a35ca0850b9e392fecbdef3d3bc0ac69960","165896fb5761596c6f6d80323e4b5804e4ad448370ceaf9b525db30b2452f7f5","a31ea11c98a398f4709d52e202f3f2d1698569b7b6878572fc891b8de56e1ff7",
"a1b4db93eb72a520878ad338d66313fbaeab3634000fb7c69b1c34c9f3e17727","0b22a0d84afb8bc4426ac3882a5ecd2e93818a2ea62d4d5cbae36d942552a36a","4d5839d70f16e8f4f7980d0ae1758bb5a88b061fd723ea4bf32b4b474c222bec","9bffe9add38808b3f6021e6d07084a06300347dd5d4b7e159d97e949735cff1e"]);  
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"

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

let lookback = 7d;
let ioc_domains = dynamic(["slgndocline.onlxtg.com ", "cronoze.com ", "muuxxu.com ", "proliforetka.com ", "porelinofigoventa.com ", "shareddocumentso365cloudauthstorage.com", "newsbloger1.duckdns.org"]);
  _Im_WebSession (starttime=ago(lookback), eventresult='Success', url_has_any=ioc_domains)
 | summarize imWS_mintime=min(TimeGenerated), imWS_maxtime=max(TimeGenerated), EventCount=count() by SrcIpAddr, DstIpAddr, Url, Dvc, EventProduct, EventVendor  

In addition to the above, Sentinel users can also leverage the following queries, which may be relevant to the content of this blog.

Indicators of compromise

BruteRatel C4 and Lactrodectus infection chain

IndicatorTypeDescription
9bffe9add38808b3f6021e6d07084a06300347dd5d4b7e159d97e949735cff1eSHA-256lrs_Verification_Form_1730.pdf
0b22a0d84afb8bc4426ac3882a5ecd2e93818a2ea62d4d5cbae36d942552a36aSHA-256Irs_verif_form_2025_214859.js
4d5839d70f16e8f4f7980d0ae1758bb5a88b061fd723ea4bf32b4b474c222becSHA-256bars.msi
a1b4db93eb72a520878ad338d66313fbaeab3634000fb7c69b1c34c9f3e17727SHA-256BRc4, filename: nvidiamast.dll
hxxp://rebrand[.]ly/243eaaDomain nameURL shortener to load fake DocuSign page
slgndocline.onlxtg[.]comDomain nameDomain used to host fake DocuSign page
cronoze[.]comDomain nameBRc4 C2
muuxxu[.]comDomain nameBRc4 C2
proliforetka[.]comDomain nameLatrodectus C2
porelinofigoventa[.]comDomain nameLatrodectus C2
hxxp://slgndocline.onlxtg[.]com/87300038978/URLFake DocuSign URL
hxxps://rosenbaum[.]live/bars.phpURLJavaScript downloading MSI

RaccoonO365

IndicatorTypeDescription
shareddocumentso365cloudauthstorage[.]comDomain nameRaccoonO365 domain

AHKBot

IndicatorTypeDescription
a31ea11c98a398f4709d52e202f3f2d1698569b7b6878572fc891b8de56e1ff7SHA-256Tax_Refund_Eligibility_Document.xlsm
165896fb5761596c6f6d80323e4b5804e4ad448370ceaf9b525db30b2452f7f5SHA-256umbrella.msi
3c482415979debc041d7e4c41a8f1a35ca0850b9e392fecbdef3d3bc0ac69960SHA-256AutoNotify.ahk
9728b7c73ef25566cba2599cb86d87c360db7cafec003616f09ef70962f0f6fcSHA-256AHKBot Screenshotter module
hxxps://business.google[.]com/website_shared/launch_bw.html?f=hxxps://historyofpia[.]com/Tax_Refund_Eligibility_Document.xlsmURLURL redirecting to URL hosting malicious Excel file
hxxps://historyofpia[.]com/Tax_Refund_Eligibility_Document.xlsmURLURL hosting malicious Excel file
hxxps://acusense[.]ae/umbrella/URLURL in macro that hosted the malicious MSI file
181.49.105[.]59IP addressAHKBot C2

Remcos

IndicatorTypeDescription
bb3b6262a288610df46f785c57d7f1fa0ebc75178c625eaabf087c7ec3fccb6aSHA-2562024 Tax Document_Copy (1).pdf
fe0b2e0fe7ce26ae398fe6c36dae551cb635696c927761738f040b581e4ed422SHA-2562024 Tax Document.zip
hxxps://www.dropbox[.]com/scl/fi/ox2fv884k4mhzv05lf4g1/2024-Tax-Document.zip?rlkey=fjtynsx5c5ow59l4zc1nsslfi&st=gvfamzw3&dl=1URLURL in PDF
newsbloger1.duckdns[.]orgDomain nameRemcos C2

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 Threat actors leverage tax season to deploy tax-themed phishing campaigns appeared first on Microsoft Security Blog.

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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 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.

The post Phishing campaign impersonates Booking.com, delivers a suite of credential-stealing malware appeared first on Microsoft Security Blog.

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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

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