Social engineering News and Insights | Microsoft Security Blog http://approjects.co.za/?big=en-us/security/blog/tag/social-engineering/ Expert coverage of cybersecurity topics Thu, 23 Jul 2026 15:04:09 +0000 en-US hourly 1 https://wordpress.org/?v=6.9.4 Email threat landscape: Q2 2026 trends and insights http://approjects.co.za/?big=en-us/security/blog/2026/07/23/email-threat-landscape-q2-2026-trends-and-insights/ Thu, 23 Jul 2026 15:00:00 +0000 http://approjects.co.za/?big=en-us/security/blog/?p=148775 In the second quarter of 2026, the continuing effects of Microsoft’s disruption of the Tycoon2FA phishing platform contributed to sustained declines in several major phishing techniques, while threat actors expanded into Teams-based social engineering and employed increasingly automated and multi-stage attack chains.

The post Email threat landscape: Q2 2026 trends and insights appeared first on Microsoft Security Blog.

]]>

The second quarter of 2026 (April–June) was largely defined by the continuing downstream effects following Microsoft’s Digital Crimes Unit-led disruption efforts against the Tycoon2FA phishing-as-a-service (PhaaS) platform in March. Phishing volume linked to the platform fell 92% from pre-disruption averages, including QR code phishing and CAPTCHA-gated phishing both declining from their March highs. Despite ongoing efforts to rebuild operations, Tycoon2FA did not recover its previous scale or influence during Q2, and no single service emerged to replace the platform at comparable scale.

These trends reflect both the measurable impact that disruption operations can have on phishing ecosystems and the adaptability of threat actors as they diversify delivery channels. At the same time, Microsoft Threat Intelligence observed continued growth in Teams-based social engineering, particularly voice phishing (vishing), with weekly malicious call attempts reaching nearly ten times the mid-2025 baseline by the end of the quarter. This activity illustrates how threat actors continue to expand beyond email into trusted workplace communication platforms where communications may appear more trustworthy to users.

Microsoft detected approximately 7.6 billion email-based phishing threats throughout the quarter, with monthly volumes declining modestly from 2.7 billion in April to 2.4 billion in June. Credential phishing remained the dominant objective behind malicious payloads, while business email compromise (BEC) activity largely returned to historical norms after a brief, anomalous surge in April. Notable campaigns observed during the quarter also demonstrated how threat actors combine automation, trusted services, and multi-stage delivery chains to scale operations. These campaigns ranged from an automated BEC campaign that reached more than 67,000 users across 42,000 organizations in under three hours, to a multi-stage phishing campaign that used nested EML files, calendar invitations, and a Microsoft authentication redirect to deliver malware.

This blog provides a view of email threat activity across the second quarter of 2026, highlighting key trends in phishing techniques, payload delivery, and threat actor behavior observed by Microsoft Threat Intelligence. We examine shifts in QR code and CAPTCHA-gated phishing activity, malicious payload trends, BEC activity, the growth of Teams-based threats, and notable campaigns observed during the quarter. We also provide recommendations and Microsoft Defender detections to help organizations identify and mitigate evolving threats while prioritizing defensive measures.

Tycoon2FA Q2 disruption impact

The disruption operation that Microsoft’s Digital Crimes Unit launched against Tycoon2FA infrastructure in early March continued to produce measurable results throughout Q2 2026. After falling 15% in March and another 22% in April, Tycoon2FA-linked phishing volume dropped 74% in May to just 1.5 million messages, then fell another 20% in June to 1.2 million, by far the lowest monthly volumes observed in at least a year. For reference, the average monthly volume of phishing messages linked to Tycoon2FA during the second half of 2025 was 15.1 million. By the end of Q2, volumes were running at roughly 8% of that baseline, representing a 92% total decline since the disruption operation began.

The diagram shows a descending line representing the number of phishing emails received each month, starting from 25 million in July and decreasing to nearly 0 by December.
Figure 1. Tycoon2FA monthly malicious messages volume (July 2025–June 2026)

Tycoon2FA’s influence across two primary phishing tactics, QR code lures and CAPTCHA-gated landing pages, also continued to decline throughout the quarter:

  • CAPTCHA-gated phishing: Tycoon2FA’s share of CAPTCHA-gated phishing sites fell from 41% in March to 16% in April and 12% by June, down from a peak of 76% in December 2025.
  • QR code phishing: The share of QR code campaigns redirecting to Tycoon2FA domains decreased from 20% in March to 17% in April and 14% by June, down from a peak of 33% in November 2025.

These declines indicate that the platform’s customer base has not migrated to replacement infrastructure at anything close to the scale they previously operated.

After being forced off Cloudflare, which had provided anti-analysis protection that made Tycoon2FA pages harder to scan and take down, the service continued to rely on infrastructure hosted on the .RU top-level domain (TLD), a shift that began in late March. More than 40% of newly observed Tycoon2FA domains used .RU registrations throughout Q2. While this reflects an ongoing effort to find replacement hosting, Tycoon2FA’s role in the phishing ecosystem has nonetheless been significantly diminished and the pace of recovery has been slow.

QR code phishing attacks

After peaking at 18.7 million attacks in March, the highest monthly volume in at least a year, QR code phishing declined for three consecutive months in Q2. Volume fell 7% in April to 17.4 million, then dropped more sharply in May (-38%) and June (-22%), closing the quarter at 8.3 million attacks. By June, QR code phishing had returned to levels last seen in mid-2025.

The line graph shows a steady increase in phishing emails received, starting from around 1 million on January 1, 2026, peaking around 6 million around April 9, before declining back down towards 1 million by the end of June.
Figure 2. Trend of QR code phishing attacks by weekly volume (January 2026–June 2026)

The delivery methods used in QR code attacks shifted notably during Q2. PDF attachments remained the dominant vehicle throughout, but their dominance weakened after April:

  • PDF attachments peaked at 79% of QR code attacks in April before falling to 59% in May and 58% in June. By raw volume, malicious PDFs containing QR codes dropped more than 60% between April and June.
  • DOC/DOCX attachments moved in the opposite direction, increasing 30% in May to account for 38% of QR code payloads, the highest share since December 2025. By June, DOC/DOCX payloads reached 40% of QR code attacks. This swap between PDF and DOC/DOCX dominance is a pattern that has recurred throughout the past year, as operators appear to rotate between delivery formats.
  • Email-embedded QR codes, which had surged 336% in March and accounted for 5% of QR code attacks, effectively disappeared in Q2. This delivery method dropped to near-zero across all three months, leaving QR code phishing almost entirely an attachment-based tactic.
The graph shows PDF attachments peaking in April at 79% before declining to 58% in June, while DOC attachments rising from around 20% in April up to 40% in June, and other attachments remained under 10% throughout the last 6 months.
Figure 3. QR code phishing delivery method share by month (January-June 2026)

CAPTCHA-gated phishing tactics

After accumulating to nearly 12 million attacks in March, the highest monthly volume observed over the past year, CAPTCHA-gated phishing declined sharply throughout Q2. Volume fell 32% in April to 8.2 million, then dropped another 65% in May and 24% in June, closing the quarter at just 2.2 million attacks. Since the March peak, CAPTCHA-gated phishing has fallen more than 81%, reaching its lowest monthly volume in more than a year.

The graph shows a decline in the number of phishing emails from 12 million in March to 2.2 million by June.
Figure 4. CAPTCHA-gated phishing volume (January 2026–June 2026)

The rapid rotation of delivery methods that characterized Q1 continued into Q2, with no single payload type maintaining the top position for more than one or two months:

  • PDF attachments surged to 63% of CAPTCHA-gated attacks in April, the highest single-payload share observed in the past year, after more than quadrupling in March. This dominance was short-lived, however. PDF volumes dropped 69% in May and another 70% in June, falling to just 22% of attacks by the end of the quarter.
  • HTML attachments, which had been a major delivery vector through January (37% of attacks), declined sharply during Q2. After declining to 8% in April, HTML payloads fell to just 3% in May before recovering slightly to 5% in June, their lowest sustained share in at least a year.
  • SVG files reached their lowest observed volume in April (5% of attacks) before rebounding to 12% in May and 26% in June. While still well below the levels seen when Tycoon2FA actively used SVG files, this gradual recovery bears monitoring.
  • Email-embedded URLs reclaimed the top position in June for the first time since December 2025, accounting for 30% of CAPTCHA-gated attacks. This was more a function of every other delivery method declining in raw volume than a resurgence in URL-based delivery. The actual volume of URL-delivered CAPTCHA-gated phish in June was still far lower than most months over the past year.
  • DOC/DOCX files declined from their March spike, falling steadily from 15% to 10% of attacks over the quarter.
The bar chart displays PDF attachments peaking at over 60% in April before declining to closer to 20% by June, while SVG files and URLs rose from April lows to closer to 30% by June, DOC files hovered around 15% throughout the quarter, and HTML attachments and other payload types landed under 10% by June.
Figure 5. CAPTCHA-gated phishing distribution method share by month (January-June 2026)

Tycoon2FA’s continued decline was a significant factor in the overall volume reduction. The platform’s share of CAPTCHA-gated phishing fell from 41% in March to 16% in April, 18% in May, and 12% by June, down from a peak of 76% in December 2025. No single service has emerged to fill the gap at comparable scale, contributing to the sustained decline in CAPTCHA-gated phishing activity overall.

Malicious payloads

Credential phishing continued to dominate the malicious payload landscape throughout Q2, accounting for 94–96% of all payload-based attacks each month. These credential phishing payloads either linked users to phishing pages or locally loaded spoofed sign-in screens on a user’s device. Traditional malware delivery represented just 4–6% of payloads, consistent with its long-term decline.

HTML and PDF attachments remained the two most common malicious payload types across the quarter, together accounting for roughly 60–70% of all payload-based attacks each month:

  • HTML attachments held the top position across all three months at 35–41% of attacks. After peaking in April, HTML payload volume declined 33% in May and another 17% in June.
  • PDF attachments consistently ranked second at 24–31% of attacks. PDF volume was relatively stable in April before declining 41% in May and 4% in June.
  • SVG files continued the decline that has tracked closely with Tycoon2FA’s diminishing activity. After peaking at 23% of malicious payloads in July 2025, SVG’s share fell to around 7% by Q2, consistent with SVG’s historical role as a preferred Tycoon2FA payload format.
  • DOC/DOCX and ZIP/GZIP files oscillated without a clear directional trend. DOC/DOCX increased 26% in May before falling 17% in June, while ZIP/GZIP attachments declined 48% in April, rebounded 27% in May, then dropped 40% in June.
  • ICS files (calendar invitations), while still a small share of overall payload volume (roughly 4%), nearly quadrupled in June (+277%). These attacks take advantage of the fact that calendar invitations are processed differently than standard email attachments and can inject malicious links into a user’s calendar without requiring an explicit open-and-click interaction.
  • EXE files continued to decline, falling to their lowest monthly volume in June, reflecting the broader shift away from traditional malware delivery via email attachments.
The pie chart displays a breakdown of file types, with HTML (38%), PDF (27%), DOC/DOCX (9%), SVG (8%), ZIP/GZIP (6%), RAR (2%), ICS (2%), and Other (8%).
Figure 6. Malicious payload file type (Q2 2026)

Business email compromise

April 2026 produced the most anomalous BEC data point in more than a year: nearly 9 million attacks, a 121% increase from March and more than double any previous month. The spike was short-lived as volume fell 62% in May to 3.4 million and settled at 3.9 million in June, both figures consistent with the monthly baseline that had held throughout the prior year. The April surge appeared to be driven by a small number of high-volume campaigns rather than a fundamental escalation in BEC activity.

The diagram illustrates the number of BEC attacks peaking in April at over 9 million attacks before sharply declining in May and June down to 3.9 million attacks.
Figure 7. Monthly BEC attack volume (January 2026–June 2026)

The composition of BEC attacks remained consistent throughout Q2. Generic outreach messages (like “Are you at your desk?”) accounted for 87–92% of initial contact emails each month, while explicit requests for specific financial transactions or documents represented just 3–8%. This pattern underscores that BEC operators overwhelmingly favor establishing conversational rapport with targets before making fraudulent requests, rather than leading with direct financial asks.

The pie chart displays a breakdown of BEC outreach lures, with Generic outreach content (90%), Generic task request (4%), Payroll update (2%), gift card request (2%), invoice payment (2%), and other (0%).
Figure 8. Initial BEC email content by type (Q2 2026)

Within the smaller subset of explicit financial requests, the most notable trend was the near-disappearance of fake invoice payment requests:

  • Invoice payment requests fell 67% in May and another 77% in June, reaching their lowest volume in more than a year. By June, invoice-themed BEC accounted for less than 0.4% of all attacks, down from around 3.6% in March.
  • Payroll update requests declined moderately across the quarter, from roughly 4% of attacks in March to 2.3% by June.
  • Gift card requests remained at roughly 1–4% of attacks, with no clear directional trend.

Microsoft Teams threats

While email remains the dominant initial access vector, threat actors increasingly abused Microsoft Teams during Q2 to deliver social engineering, phishing, and malware payloads. Unlike email, Teams traffic typically bypasses secure email gateways and benefits from the perceived legitimacy of a colleague-initiated chat, which can make lures particularly effective in this environment.

Teams-based phishing volume climbed steadily throughout Q2, with the average number of detected attacks rising 19% from March to April, holding roughly flat into May (+1%), then increasing another 10% into June. Financial and executive impersonation has remained largely absent from Teams-based attacks over the past several months.

A line chart depicting an upward trend of Teams call attempts, starting around 2,000 attempts in early January and climbing up closer to 10,000 attempts by June 29.
Figure 9. Weekly observed malicious Microsoft Teams calls (January-June 2026)

The dominant lure theme remained technical support impersonation, with attackers posing as an employee’s information technology (IT) help desk, typically warning of an impending account lockout. However, the way attackers presented themselves continued to evolve:

  • Display names shifted away from IT- or help desk-branded identities. For the second consecutive month, more than half (52%) of Teams-based phishing attacks in June used generic display names rather than obvious IT support impersonation.
  • Attacker email addresses associated with these chats moved away from support-themed domains toward software-as-a-service (SaaS) terminology, scan/update language, and infrastructure keywords. This shift may align with the broader rise of ClickFix-style attacks adopting update-fix and similar themes.
Bar chart showing the types of Teams call impersonation attempts across April, May, and June. General display name attempts took the majority at 42% in April climbing to 52% by June. Help desk impersonations grew from 22% in April up to 31% by June while IT support impersonations declined 32% in April down to 16% in June. Other impersonation attempts made up 4% of attacks in April and declined down to 1% by June.
Figure 10. Malicious Teams call impersonation percentage (Q2 2026)

Vishing through Teams showed the steepest growth of any threat category tracked in this report during Q2. Average weekly malicious call attempts rose 31% from April to May and another 27% into June, with the final two weeks of June recording the two highest weekly volumes on record. Since the beginning of 2026, weekly vishing attempts have increased roughly 80% and now run at nearly ten times the mid-2025 baseline. Attackers time these calls deliberately when targets are most likely to be online and active, with the heaviest activity falling between 14:00 and 20:00 UTC, Monday through Friday, with near-zero weekend activity. Notably, a growing share of these calls go unanswered, end quickly, or are rejected outright, partly reflecting Microsoft’s ongoing efforts to harden the Teams attack surface and improve protections against social engineering abuse.

Notable phishing campaigns

The following campaigns were observed during the quarter and highlight notable credential phishing, BEC, and malware delivery activity. For analysis of a separate code of conduct-themed credential phishing campaign observed in April of Q2, see Breaking the code: Multi-stage ‘code of conduct’ phishing campaign leads to AiTM token compromise.

Automated BEC campaign scales aging report and payroll diversion lures

On June 1, 2026, Microsoft Defender Research observed a high-volume BEC campaign that used automation to operate at scale. Over a send window of under three hours (14:08–16:52 UTC), the actor reached more than 67,000 users across more than 42,000 organizations, almost exclusively in the United States. Targeting spanned a broad range of industries rather than a single vertical, most notably retail and consumer goods (17%), technology and software (15%), and financial services (14%). The campaign ran two lures in succession from shared infrastructure: arequest impersonating sales executives to obtain aging report data and customer contact details, and a payroll diversion pretext impersonating the CEO or President to redirect salary payments to attacker-controlled bank accounts.

A line chart illustrating the number of emails sent in both the aging reports and payroll diversion campaigns over time. The aging reports campaign started around 14:07 UTC, peaked around 14:40 UTC, and then declined at the same time that the payroll diversion campaign started ramping up.
Figure 11. Timeline of campaign messages sent by minute, separated by lure theme

Delivery was fully scripted. The messages were generated programmatically using Python’s email.mime library, identifiable from its default MIME boundary format (===============[integer]==), and dispatched through the Amazon Simple Email Service (SES) API rather than a manual webmail interface, as indicated by the SES Feedback-ID and Message-ID formats. This allowed the actor to iterate through a recipient list and inject per-message variables (like spoofed executive display names, recipient addresses, and unique tracking identifiers) at volume. Messages were sent from a DomainKeys Identified Mail (DKIM)-configured Slovak domain (ecajovna[.]sk) through SES, so they passed Sender Policy Framework (SPF) and achieved DKIM alignment. Neither lure contained a malicious link or attachment; both relied on eliciting a reply to attacker-controlled mailboxes that mimicked legitimate providers (ilyff[.]com, j-gmails[.]com, x2mails[.]com).

Automation also extended to targeting and follow-up. The actor addressed generic role-based mailboxes (like “ar”, “accountsreceivable”, “hr”, “payroll”) rather than named individuals, reducing per-target effort. Each message embedded a 1×1 open-tracking pixel served from an Amazon SES engagement subdomain, with per-message identifiers that let the actor confirm which recipients opened the email and prioritize follow-up against those targets. The combination of scripted message generation, API-based bulk delivery, role-based targeting, and automated engagement tracking allowed a single actor to run a personalized, financially motivated BEC operation at a scale not practical to execute manually.

A user's email requesting a copy of the most recent AR Aging Collection Report, including customer contact details.
Figure 12. Rendered example of aging report email used in this campaign
A supposed user is requesting assistance to update their salary payment details due to a change in their banking information.
Figure 13. Rendered example of payroll diversion email used in this campaign

Staff update campaign with nested EML file and calendar invitation leads to BAT file dropper

Between June 14–15, 2026, Microsoft Defender Research observed a phishing campaign targeting more than 107,000 users across nearly 19,000 organizations, almost exclusively in the United States. The campaign targeted a broad range of industries rather than a single vertical, most notably financial services (17%), technology and software (14%), and retail and consumer goods (14%). Emails impersonated an internal “Internal Affairs – Financials & Staff Updates” function at the recipient’s own organization, with the display name and subject line both opening with the recipient’s organization name and closing with constant trailing text. The messages were sent from a Postfix host on 9i6pokerdepot[.]com routed through Barracuda’s outbound mail service, and DKIM passed cleanly for the sending domain.

An email with a header indicating it is an internal employee briefing and meeting summary, with placeholders for confidential information and a request to download and review an attachment for further details.
Figure 14. Rendered sample of initial campaign email

The visible email body contained minimal content. One line told the reader to download the attached file for the meeting summary, followed by a confidentiality notice. Each message carried two attachments: a nested EML posing as a Teams archive recording, and an ICS calendar invite addressed to placeholder administrative accounts at the recipient’s domain. The nested EML’s file name retained an unfilled template token ( {{DATE2}} ), indicating a per-recipient templating tool.

When opened, the EML displayed a voicemail notification with a single action button. That button pointed to Microsoft’s OAuth sign-in endpoint at login.microsoftonline[.]com, with parameters that asked for a silent sign-in attempt against an Entra application that the attacker had registered as multi-tenant.

The image displays a message from the VOICEMAIL CENTER, indicating a new voicemail for the recipient, with instructions to download the attachment to listen to the message.
Figure 15. Rendered sample of voicemail notification from the nested EML

Because no active sign-in session could satisfy the silent request, Microsoft’s authentication service redirected the recipient to the destination the attacker had pre-registered on the application. That destination was a path on clickup-attachments[.]com, ClickUp’s public attachment host, and served a Windows batch file named Financial_report.bat. Because the link routed through Microsoft authentication infrastructure, both recipients and URL scanners saw a login.microsoftonline[.]com link.

The batch file ran a hidden PowerShell command that pulled installer.exe from pixeldrain[.]com, saved it under the user’s Temp directory, ran it with a silent flag, and deleted the dropper on exit. Rather than stealing credentials, the campaign ultimately resulted in silent malware execution on the user’s Windows device.

A scripted command line interface, specifically a batch file for a silent installation process, which includes downloading an installer, executing it, and cleaning up afterward.
Figure 16. Source code of Financial_report.bat

Mitigation and protection guidance

Microsoft recommends the following mitigations to reduce the impact of this threat. Check the recommendations card for the deployment status of monitored mitigations.

  • Review the recommended settings for Exchange Online Protection and Microsoft Defender for Office 365 to ensure your organization has established essential defenses and knows how to monitor and respond to threat activity.
  • Invest in user awareness training and phishing simulations. 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.
  • Enable 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.
  • Responders could also manually check for and purge unwanted emails containing URLs and/or Subject fields that are similar, but not identical, to those of known bad messages. Investigate malicious email that was delivered in Microsoft 365 and use Threat Explorer to find and delete phishing emails.
  • Turn on Safe Links and Safe Attachments in Microsoft Defender for Office 365.
  • Enable network protection in Microsoft Defender for Endpoint.
  • Encourage users to use Microsoft Edge and other web browsers that support Microsoft Defender SmartScreen, which identifies and blocks malicious websites, including phishing sites, scam sites, and sites that host malware.
  • Enable password-less authentication methods (for example, Windows Hello, FIDO keys, or Microsoft Authenticator) for accounts that support password-less. For accounts that still require passwords, use authenticator apps like Microsoft Authenticator for MFA. Refer to this article for the different authentication methods and features.
  • Configure automatic attack disruption in Microsoft Defender XDR. Automatic attack disruption is designed to contain attacks in progress, limit the impact on an organization’s assets, and provide more time for security teams to remediate the attack fully.

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.

Microsoft Defender for Endpoint

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

  • Suspicious activity likely indicative of a connection to an adversary-in-the-middle (AiTM) phishing site

Microsoft Defender for Office 365

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

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

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 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.

Indicators of compromise (IOCs)

IndicatorTypeDescriptionFirst seenLast seen
9i6pokerdepot[.]comDomainSending domain; DKIM-signed by the operator2026-06-152026-06-15
Customer.Service[@]9i6pokerdepot[.]comEmail addressCampaign sender address2026-06-152026-06-15
t90141296286.p.clickup-attachments[.]comDomainClickUp attachment subdomain hosting the stage 2 BAT dropper2026-06-152026-06-15
hxxps://t90141296286.p.clickup-attachments[.]com/t90141296286/fb39c3a9-3161-40ad-847b-0683e0409d6f/Financial_report.batURLStage 2 BAT dropper download URL2026-06-152026-06-15
hxxps://pixeldrain[.]com/api/file/3v92oJiLURLFinal installer payload download URL2026-06-152026-06-15
Re: Teams Archive Recording for {{DATE2}}.emlFile nameNested EML attachment template name; the literal {{DATE2}} indicates an unfilled per-recipient template token2026-06-152026-06-15
Financial_report.batFile nameStage 2 dropper batch file delivered from the OAuth error redirect2026-06-152026-06-15
ecajovna[.]skDomainDomain used to send campaign emails2026-06-012026-06-01
ilyff[.]comDomainReply-to domain used to receive victim responses2026-06-012026-06-01
j-gmails[.]comDomainReply-to domain used to receive victim responses2026-06-012026-06-01
x2mails[.]comDomainReply-to domain used to receive victim responses2026-06-012026-06-01
contact[@]ecajovna[.]skEmail addressAddress used to send campaign emails2026-06-012026-06-01
mail[@]ilyff[.]comEmail addressReply-to address2026-06-012026-06-01
me[@]j-gmails[.]comEmail addressReply-to address2026-06-012026-06-01
me[@]x2mails[.]comEmail addressReply-to address2026-06-012026-06-01
compliance-protectionoutlook[.]deDomainDomain hosting malicious campaign content2026-04-142026-04-16
acceptable-use-policy-calendly[.]deDomainDomain hosting malicious campaign content2026-04-142026-04-16
cocinternal[.]comDomain  Domain hosting sender email address2026-04-142026-04-16
gadellinet[.]comDomain  Domain hosting sender email address2026-04-142026-04-16
harteprn[.]comDomainDomain hosting sender email address2026-04-142026-04-16
cocpostmaster[@]cocinternal[.]cmEmail addressEmail address used to send campaign emails2026-04-142026-04-16
nationaladmin[@]gadellinet[.]comEmail addressEmail address used to send campaign emails2026-04-142026-04-16
nationalintegrity[@]harteprn[.]comEmail addressEmail address used to send campaign emails2026-04-142026-04-16
m365premiumcommunications[@]cocinternal[.]comEmail addressEmail address used to send campaign emails2026-04-142026-04-16
documentviewer[@]na[.]businesshellosign[.]deEmail addressEmail address used to send campaign emails2026-04-142026-04-16
5DB1ECBBB2C90C51D81BDA138D4300B90EA5EB2885CCE1BD921D692214AECBC6SHA-256File hash of campaign PDF attachment2026-04-142026-04-16
B5A3346082AC566B4494E6175F1CD9873B64ABE6C902DB49BD4E8088876C9EADSHA-256  File hash of campaign PDF attachment2026-04-142026-04-16
11420D6D693BF8B19195E6B98FEDD03B9BCBC770B6988BC64CB788BFABE1A49DSHA-256  File hash of campaign PDF attachment2026-04-142026-04-16

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 Email threat landscape: Q2 2026 trends and insights appeared first on Microsoft Security Blog.

]]>
ACR Stealer: Two observed intrusion chains amid increased threat activity http://approjects.co.za/?big=en-us/security/blog/2026/07/16/acr-stealer-two-observed-intrusion-chains-amid-increased-threat-activity/ Thu, 16 Jul 2026 23:12:02 +0000 http://approjects.co.za/?big=en-us/security/blog/?p=148744 From late April 2026 to mid-June 2026, Microsoft Defender Experts observed increased ACR Stealer activity across customer environments. These campaigns are successfully using ClickFix lures to steal browser credentials, authentication tokens, and sensitive documents from enterprise environments.

The post ACR Stealer: Two observed intrusion chains amid increased threat activity appeared first on Microsoft Security Blog.

]]>

From late April 2026 to mid-June 2026, Microsoft Defender Experts observed increased ACR Stealer activity across customer environments. These campaigns are successfully using ClickFix lures to steal browser credentials, authentication tokens, and sensitive documents from enterprise environments. Successful compromise can expose browser credentials, session tokens, authentication artifacts, and sensitive enterprise data, potentially enabling account compromise, unauthorized access to cloud resources, and follow-on intrusion activity. Security teams should prioritize monitoring for ClickFix lures, suspicious WebDAV activity, obfuscated PowerShell execution, and attempts to access browser credential stores.

ACR Stealer is an information-stealing malware family reportedly offered through a malware-as-a-service (MaaS) model and associated with the rebranding of Amatera Stealer. During this period, two campaigns stand out, together appearing frequently in reviewed recent intrusions. Both begin the same way, with a ClickFix social engineering technique that tricks targets into running the threat actor’s command, but the intrusion chains that follow diverge in how they deliver payloads, establish execution, and evade detection.

The first campaign relies on WebDAV-delivered payloads, staged PowerShell, Python-based loaders and persistence, and, in some intrusions, blockchain-backed dead-drop command-and-control (C2) resolution. The second campaign takes a more fileless route, using MSHTA, obfuscated PowerShell, and steganography-assisted in-memory execution. Despite these differences, both campaigns ultimately pursue the same goal: stealing browser-stored credentials and other sensitive data for exfiltration.

These two campaigns represent some of the most prevalent ACR Stealer delivery campaigns observed by Defender Experts; however, they do not represent the full range of delivery methods used by this malware family. Attribution to ACR Stealer is based on the observed behavior and post-exploitation tradecraft, corroborated by open-source intelligence on the infrastructure associated with this malware family. Additional campaigns, infrastructure patterns, and execution chains are likely active, and organizations should treat the indicators and techniques described here as representative.

Microsoft Defender for Endpoint can help surface both campaigns through behavioral coverage for living-off-the-land execution, suspicious WebDAV and MSHTA activity, obfuscated PowerShell, scheduled-task persistence, in-memory payload execution, and browser credential theft. In this blog, we analyze both campaigns in detail, including their delivery mechanisms, post-exploitation tradecraft, indicators of compromise, hunting opportunities, and guidance to help defenders detect and disrupt related activity in their environments.

Campaign 1: WebDAV-based ClickFix with Python loaders and blockchain C2

Initial access

In this campaign, a ClickFix prompt, likely delivered through malvertising or SEO-manipulated search results, instructs the target user to run a command that launches cmd.exe. The command subsequently invokes rundll32.exe to load a DLL from a remote WebDAV share accessed over HTTPS. The WebDAV path commonly uses a GUID-based directory structure and filenames designed to resemble legitimate resources (for example, google.ct), enabling the activity to blend with expected network traffic and evade casual inspection.

We observed three variants of the initial execution command:

Variant 1: Direct rundll32 invocation

Variant 2: pushd-Mounted WebDAV Share

Variant 3: Headless and obfuscated pushd execution

Variants 2 and 3 are notable for their use of pushd, which transparently maps the remote WebDAV share to a temporary local drive prior to execution. This technique allows threat actors to execute remotely hosted content through what appears to be a local path, simplifying payload execution while reducing user awareness. In the more advanced variant, threat actors further enhance stealth by launching commands through conhost.exe –headless, suppressing visible console windows, and employing environment variable obfuscation with delayed variable expansion to conceal critical execution components such as pushd, rundll32, and the remote host name. Combined with minimized or headless execution, these techniques reduce user visibility, complicate static analysis and detection, and enable the infection chain to execute with minimal indication to the victim.

Execution, persistence, and evasion through process masquerading

Once rundll32.exe loads the DLL retrieved from the remote server, the malware establishes communication with threat actor-controlled infrastructure and executes a heavily obfuscated PowerShell script. The script employs excessive arithmetic no-ops, dead loops, fake control flow, and randomized variable names to hinder static analysis and evade signature-based detection.

The PowerShell script subsequently deploys another stage that functions as both a malware installer and a persistence mechanism. It:

  • Downloads a ZIP-packaged payload from a remote server and extracts it into a deceptive directory under %LocalAppData%\Temp (for example, LogiOptionsPlus).
  • Launches a Python script using a bundled pythonw.exe instance to avoid displaying a console window.
  • Removes previous deployments and terminates running instances before installation, effectively operating as an updater.
  • Establishes persistence through a hidden scheduled task disguised as a legitimate software update, ensuring execution at user sign-in.
  • Copies timestamps from a trusted Windows binary (notepad.exe) to the deployed files and clears PowerShell command history to reduce forensic visibility.
PowerShell loader downloads and executes a payload through a masqueraded scheduled task.

Python loader launching the stealer

The Python component serves as a heavily obfuscated loader designed to conceal its true functionality until runtime. It employs multiple layers of defense against static analysis, including dynamic API resolution, encoded string reconstruction, junk-data removal, character shifting, string reversal, Base64 decoding, and zlib decompression. These techniques ensure that the embedded payload remains unreadable in its static form and is reconstructed only during execution, significantly hindering signature-based detection and automated analysis.

Once decoded, the final-stage payload functions as an in-memory shellcode loader. It extracts an archive file masquerading as a legitimate application installer, reads a file from the archive, and injects the payload into a system process. The loader allocates executable memory using VirtualAlloc, copies the payload into the allocated memory region, and transfers execution through the Windows Fiber API (ConvertThreadToFiber, CreateFiber, and SwitchToFiber). This technique facilitates stealthy in-memory execution while minimizing artifacts written to disk.

Decoded Python shellcode loader using VirtualAlloc and Fiber-based execution.

Credential theft and data staging for exfiltration

The malware (injected code) aggressively harvests information from browser credential stores. It invokes Windows Data Protection API (DPAPI) routines to decrypt locally stored browser passwords, cookies, and authentication tokens. It also enumerates files across the system, targeting PDFs, Microsoft 365 documents, and data stored in enterprise-synchronized directories such as OneDrive and SharePoint. The collected data is subsequently archived, indicating preparation for exfiltration.

Blockchain dead-drop C2 resolution

A notable variation in this campaign is the use of blockchain services for C2 resolution, utilizing a technique known as EtherHiding. While most intrusions rely on more conventional C2 mechanisms, a subset deploys an additional secondary Python loader that leverages blockchain services as dead-drop resolvers. When this loader executes, it has been observed communicating with public blockchain RPC endpoints and third-party Web3 node infrastructure, likely querying data stored on a decentralized public ledger to retrieve follow-up payloads or a C2 address.

By externalizing C2 information to the blockchain, operators could dynamically update infrastructure without modifying or redeploying the malware, significantly complicating detection and takedown efforts. This behavior was observed across both variants of the campaign.

Campaign 2: MSHTA-initiated PowerShell chain with steganographic payload delivery

The second campaign takes a distinctly different approach to both delivery and execution. Where Campaign 1 relies on disk-based artifacts (Python runtime, scheduled tasks, and masquerading binaries), this campaign achieves its objectives almost entirely through fileless, in-memory execution, making it harder to detect through file-based scanning and forensic analysis.

Initial access through MSHTA and ClickFix

The execution chain begins when the victim, directed through malvertising or SEO-manipulated search results, encounters a ClickFix prompt that triggers a command spawning MSHTA to fetch and execute remote HTA content from an threat actor-controlled domain. The embedded VBScript loader abuses COM objects to decode and execute encoded PowerShell content.

VBScript loader using COM objects to decode and launch a PowerShell payload.

PowerShell downloader and obfuscation

The decoded PowerShell stage employs obfuscation techniques similar to those seen in Campaign 1: randomized variable names, arithmetic no-op operations, dead loops, misleading control flow, and custom encryption routines. Prior to contacting its next-stage infrastructure, the malware generates a victim-specific identifier and disables certificate validation. The retrieved content is executed directly in memory.

Steganography-based payload delivery

A notable technique in this campaign is the use of steganography to conceal malicious content inside a publicly hosted image. Instead of downloading a secondary script (as in Campaign 1), the malware retrieves a JPEG image from an image-hosting service.

Steganographic payload extraction from a downloaded image prior to decryption and execution.

Analysis of the script revealed custom routines that extract an embedded payload from image pixels, decrypt and decompress it, and execute it entirely in memory. The payload dynamically resolves APIs such as LoadLibrary, GetProcAddress, VirtualAlloc, CreateThread, and WaitForSingleObject at runtime to perform reflective shellcode execution. By combining steganography with in-memory execution, the malware minimizes on-disk artifacts and complicates both detection and analysis.

Credential theft, data collection, and exfiltration

Following execution, the malware accesses credential stores belonging to Chromium-based browsers, including Google Chrome and Microsoft Edge, specifically the Login Data and Web Data databases, alongside Windows DPAPI decryption activity. This behavior indicates attempts to recover stored browser credentials, session cookies, authentication tokens, and other sensitive user information.

The malware also enumerates and accesses multiple high-value PDF documents across Desktop and Downloads locations, suggesting targeted collection of potentially sensitive files. The combination of browser credential harvesting and systematic document access points to an information-stealing objective focused on staging credentials and valuable user data for exfiltration.

Mitigation and protection guidance

Microsoft recommends the following mitigations to reduce the impact of ClickFix lures, script-based payload delivery, credential theft, and post-compromise activity.

  • Educate users to recognize ClickFix-style prompts, fake verification checks, and paste-and-run instructions as malicious, especially when they invoke command interpreters or script hosts such as cmd.exe, PowerShell, rundll32.exe, or mshta.exe.
  • Reduce exposure to malvertising, SEO poisoning, and other web-based delivery chains by enforcing web filtering, blocking low-reputation or newly observed domains, and limiting access to remote content sources that are not required for business operations.
  • Use application control and attack surface reduction rules to restrict PowerShell, Python, mshta.exe, rundll32.exe, and similar tools from launching untrusted or internet-delivered content, particularly from user-writable directories such as Downloads, Temp, and %LocalAppData%.
  • Monitor for suspicious persistence and defense-evasion behavior, including scheduled tasks masquerading as software updates, timestomping, PowerShell history clearing, and execution chains that progress from remote content retrieval into PowerShell, Python, or shellcode-loading behavior.
  • Investigate abnormal access to Chromium-based browser databases, DPAPI-related decryption activity, staged collection of Microsoft 365 documents or PDFs, and compression activity that may indicate credential theft or data staging for exfiltration.
  • If compromise is suspected, isolate affected devices, rotate exposed credentials, revoke potentially compromised tokens, review persistence mechanisms, and investigate outbound connections to remote shares, image-hosting services, or other infrastructure used to resolve or retrieve follow-on payloads.
  • Harden endpoints against credential theft by reducing reliance on browser-stored credentials, enforcing multifactor authentication and conditional access, and reviewing how privileged accounts access sensitive applications and synchronized enterprise data.
  • Turn on cloud-delivered protection and behavior-based detections to help identify rapidly evolving threats, suspicious script execution, in-memory payload delivery, abuse of browser credential stores, and unusual child-process activity.
  • Run endpoint detection and response (EDR) in block mode and enable automated investigation and remediation so post-breach detections are contained, and malicious artifacts can be removed with minimal delay.
  • Harden PowerShell by enforcing appropriate execution policies, turning on script block logging, module logging, and transcription, and monitoring this telemetry for signs of malicious script activity.
  • Turn on tamper protection and prevent local administrators from weakening antivirus protection through local policy or exclusion changes.

Microsoft Defender XDR detections

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

TacticObserved ActivityMicrosoft Defender Coverage
Execution– Suspicious MSHTA launch through ClickFix execution
– Rundll32 loads remote WebDAV DLL
– COM objects launch in-memory PowerShell
Microsoft Defender for Endpoint
– Use of living-off-the-land binary to run malicious code
– Obfuscated command line was launched
– Suspicious process executed PowerShell command
– Suspicious process launch by Rundll32.exe

Microsoft Defender for Antivirus
Behavior:Win32/Interhta.Int
PersistencePowerShell creates Scheduled task, masquerading as a software updateMicrosoft Defender for Endpoint
– Suspicious Scheduled Task Process Launched  
– Suspicious scheduled task
Stealth/Defense Evasion– Fiber-API in-memory shellcode execution
– Reflective shellcode via CreateThread
Microsoft Defender for Endpoint
Possible process hollowing
Credential AccessCollects browser credentials, cookies, and tokens while enumerating files for exfiltrationMicrosoft Defender for Endpoint
– Information stealing malware activity  
– Suspicious DPAPI activity
– Possible theft of passwords and other sensitive web browser information

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 current information available in the Defender portal about the threat actor, malicious activity, and techniques discussed in this blog. These reports provide the intelligence, protection information, and recommended actions to help prevent, mitigate, or respond to associated threats found in customer environments:

Microsoft 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.

Advanced hunting queries

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

Run the query below to identify suspicious commands executed through ClickFix-based activity observed while delivering this stealer

DeviceRegistryEvents
| where RegistryKey has "RunMRU"
| where (RegistryValueData has_all ("rundll32", "@ssl", " /c ", " start ") and (RegistryValueData matches regex @"\\\\[^\\]+@ssl\\[0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{12}\\\w+\.\w+,#1" or
RegistryValueData matches regex @"(?i)pushd \\\\[^\\]+@ssl\\[0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{12} ")) 
or RegistryValueData has_all ("@ssl", " /c ", "conhost --headless ") and RegistryValueData contains "rundll32"

Run the query below to identify scheduled task creation used for persistence by a malicious PowerShell script

DeviceProcessEvents
| where InitiatingProcessFileName =~ "powershell.exe"
| where InitiatingProcessCommandLine has_all ("-Command", "powershell")
| where ProcessCommandLine has_all ("schtasks", " /run /tn ", " Autoupdate ") and ProcessCommandLine matches regex "[0-9]{8}"

Run the query below to identify suspicious MSHTA launch through PowerShell

DeviceProcessEvents
| where InitiatingProcessParentFileName has "explorer.exe"
| where InitiatingProcessFileName =~ "powershell.exe" and InitiatingProcessCommandLine in~ ('"PowerShell.exe" ', '"PowerShell.exe"')
| where ProcessCommandLine has_all ('"mshta.exe" https://') and ProcessCommandLine matches regex "/[0-9]{7}"

MITRE ATT&CK techniques observed

The following mapping summarizes the primary tactics and techniques observed across the two ACR Stealer intrusion chains. The mapping is intended to help defenders align observed behaviors with existing detection coverage, response playbooks, and hunting priorities.

TacticTechniqueObserved behavior
Initial AccessDrive-by Compromise; User ExecutionClickFix lure prompts command execution.
ExecutionCommand and Scripting Interpreter: Windows Command Shell; PowerShell; Pythoncmd.exe, PowerShell, and pythonw.exe launch staged payloads.
ExecutionSystem Binary Proxy Execution: Rundll32; MshtaRundll32 loads WebDAV DLLs; mshta.exe runs remote HTA content.
PersistenceScheduled Task/Job: Scheduled TaskHidden scheduled task maintains user-logon execution.
Defense EvasionObfuscated Files or Information; Masquerading; Indicator Removal: Clear Command HistoryObfuscation, timestomping, history clearing, and masquerading.
Defense EvasionObfuscated Files or Information: SteganographyJPEG pixel data hides the encrypted payload.
Defense Evasion / ExecutionReflective Code Loading; Process InjectionIn-memory shellcode execution via runtime API resolution.
Credential AccessCredentials from Web BrowsersBrowser stores and DPAPI activity used to recover credentials and tokens.
CollectionData from Local System; Data StagedPDFs, Office files, and synced enterprise data are staged.
Command and ControlWeb Service; Dead Drop ResolverInfrastructure and blockchain RPC endpoints resolve payload or C2 data.

Indicators of compromise (IOC)

Campaign 1
IndicatorDescription
looksta[.]icuC2 domain
contrite.quirksturdy[.]icuC2 domain
ux.strainedeasily[.]icuC2 domain
cpppemwjewjoiwejow[.]saleC2 domain
breaksd.wifihot[.]icuC2 domain
walter.filloco[.]icuC2 domain
fast.raidher[.]icuC2 domain
apigrokcloud[.]icuC2 domain
Campaign 2
enhanceblabber[.]ccC2 domain
deep-harborio[.]com1st Stage payload hosting site
auramatrixa[.]com1st Stage payload hosting site
zealpraxis[.]com1st Stage payload hosting site
prism-vertex[.]com1st Stage payload hosting site
prism-matrixs[.]com1st Stage payload hosting site
proton-network[.]com1st Stage payload hosting site
creativecommunityinfo[.]artPayload hosting site

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 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.

Review our documentation to learn more about our real-time protection capabilities and see how to enable them within your organization.   

The post ACR Stealer: Two observed intrusion chains amid increased threat activity appeared first on Microsoft Security Blog.

]]>
Defending SaaS-based applications against ShinyHunters OAuth abuse http://approjects.co.za/?big=en-us/security/blog/2026/07/13/defending-saas-based-applications-against-shinyhunters-oauth-abuse/ Mon, 13 Jul 2026 22:02:41 +0000 http://approjects.co.za/?big=en-us/security/blog/?p=148665 Microsoft Threat Intelligence identified threat actor activity with overlapping tradecraft commonly associated with ShinyHunters, including voice phishing (vishing), supply-chain compromise, and misconfigured guest access targeting SaaS-based applications.

The post Defending SaaS-based applications against ShinyHunters OAuth abuse appeared first on Microsoft Security Blog.

]]>

In a series of campaigns observed between mid-2025 and mid-2026, Microsoft identified threat actor activity with overlapping tradecraft commonly associated with ShinyHunters, including voice phishing (vishing) and supply chain compromise, to target customer SaaS-based applications such as Salesforce instances. The threat actors abused trusted OAuth relationships for unauthorized access, data exfiltration, and persistence.

Two primary intrusion paths were observed including vishing techniques targeting OAuth consent and supply chain compromise through trusted workflows and integrations such as Salesloft and Gainsight. Abuse of these access paths led to inherited user and application privileges, allowing successful enumeration and querying of customer relationship management (CRM) records while evading conventional authentication detections. These intrusion paths often led to persistent access and exfiltration of data at scale. This tradecraft highlights how a single entry point can rapidly expand to greater enterprise impacts.

Microsoft observed activity associated with these techniques in many tenants from various industries such as retail, education and manufacturing. These findings reinforce the importance of monitoring OAuth-connected applications, validating third-party integrations, reviewing configurations, and enabling Salesforce event monitoring. Leveraging this data, Microsoft consulted with Salesforce to improve granularity in telemetry for Defender for Cloud Apps with near-real-time detection, offering connected application attribution and expanded application permission insights. This activity was not the result of a vulnerability inherent to Salesforce. Rather, the threat actors abused trusted OAuth relationships for unauthorized access, data exfiltration, and persistence.

Attack chain overview

Threat actor campaigns targeting Salesforce customers and using tradecraft associated with ShinyHunters pose a high-impact risk to sensitive data and downstream SaaS ecosystems. These campaigns abuse OAuth trust relationships to operate within pre-existing, legitimate workflows.

Figure 1. Commonly observed attack paths for SaaS applications.

Observed activity can be grouped into two primary intrusion paths:

In campaigns beginning in mid-2025, the threat actors conducted vishing attacks impersonating IT support personnel. Threat actors socially engineered employees into authorizing attacker-controlled connected apps within their Salesforce tenant. In several confirmed cases, threat actors guided users through the OAuth consent workflow to grant access to a malicious application disguised as a legitimate Salesforce Data Loader tool. After users granted consent, these highly privileged OAuth applications enabled threat actors to perform API calls on behalf of the victim user, facilitating:

  • Enumeration of Salesforce instances belonging to targeted organizations
  • Persistent access to Salesforce CRM data
  • Possible lateral movement into other SaaS platforms through discovered credentials

This intrusion path exploits the OAuth authorization flow of trusted SaaS services rather than relying on malware or credential replay. Threat actors exfiltrate data through sanctioned application access inherited from user privileges.

SaaS supplychain compromise targeting trusted integrations

Following initial access campaigns, threat actors  escalated into supply‑chain-driven attacks targeting third‑party SaaS vendors offering popular solutions that integrate with Salesforce, often using OAuth tokens. In August 2025, compromised Salesloft Drift credentials enabled attackers to obtain connection secrets used by downstream SaaS applications, enabling the use of OAuth tokens in multiple customer Salesforce instances.

A subsequent campaign in November 2025 targeted Gainsight-published applications integrated with Salesforce, allowing attackers to leverage trusted external connections to maintain persistent API access in multiple Salesforce customer instances. These activities often appeared indistinguishable from legitimate integration behavior. Threat actors performed discovery, bulk data queries, and mass exfiltration of sensitive CRM records, including accounts, contacts, and service case data, without generating traditional sign-in anomalies.
More recently, in June 2026, the market intelligence platform Klue experienced an incident where a threat actor, Storm-3138, gained access to its system.  Credentials used to access Salesforce customer instances were used in the same fashion, to discover, query, and exfiltrate data.

Improving visibility into Salesforce OAuth abuse

For customers using Salesforce Shield: Event Monitoring, the upgraded Microsoft Defender for Cloud Apps Salesforce connector onboards the Real-Time Event Monitoring (RTEM) framework, enabling faster detection and investigation of Salesforce-based attacks.

Investigations into these campaigns exposed a recurring challenge for security teams: malicious activity often appeared indistinguishable from legitimate Salesforce usage because threat actors operated through trusted identities, approved OAuth applications, and authorized integrations. Traditional authentication-focused detections frequently provided limited visibility into the resulting application activity.

To improve investigation and detection of these scenarios, Microsoft expanded Salesforce visibility in Defender for Cloud Apps through additional event telemetry, connected application attribution, and enhanced application permissions insights. These capabilities help security teams identify suspicious OAuth activity, investigate potentially compromised integrations, and better understand how access was obtained and used within customer Salesforce instances.

Key capabilities include:

  • Near-real-time visibility into Salesforce security and activity events.
  • Connected application attribution, including application identity and granted OAuth scopes.
  • Expanded identity, session, and API activity context to support investigations.
  • Improved correlation within Microsoft Defender to help identify suspicious activity spanning identities, applications, and SaaS environments.

Together with Salesforce Shield: Event Monitoring, these capabilities help security teams investigate suspicious OAuth activity, validate the legitimacy of connected applications, and better understand the potential impact of a compromise.

New posture and governance capabilities for connected OAuth apps

While improved detection is critical, recent incidents have also highlighted the need for stronger preventive controls and ongoing governance of OAuth-connected applications. To address this, Microsoft Defender introduces new posture capabilities for connected and external client apps in Salesforce. Security teams can gain visibility into each OAuth app and its non-human identity, prioritize risk, and reduce the attack surface.

Deep visibility into app permissions and access

Microsoft Defender provides comprehensive visibility into all Salesforce-integrated connected and external client apps, including granted OAuth scopes and privileges.

Figure 2. Complete permission visibility for Salesforce connected apps and external client apps.

Highly privileged apps

Security teams often struggle to identify applications with powerful administrative or sensitive permissions. The highly privileged apps insight highlights applications that have been granted elevated scopes, enabling quick identification of apps that may pose significant risk.

Additionally, security teams can use permission-based filters to identify apps with specific high-risk scopes and validate whether such access is justified.

Figure 3. Identity inventory to identify highly privileged Salesforce apps.

Unused apps

Organizations often create applications for temporary or one-time use, but those applications are rarely removed afterward. These unused apps continue to retain permissions, creating unnecessary exposure. With the recent changes, Defender now allows security teams to identify applications that have been inactive for extended periods (for example, 90 days or more), making it easy to review and revoke access where appropriate to reduce the attack surface.

Figure 4. Identity inventory to discover unused Salesforce apps.

Risk-based prioritization of connected apps

To further streamline investigation and response, Defender introduces a comprehensive risk scoring model for connected applications. Each application is assigned a numerical risk score [0-100] based on multiple risk indicators, such as usage patterns, permission sensitivity, and behavioral signals. This allows security teams to prioritize efforts effectively and focus on applications that require immediate attention. Security teams can create custom policies based on risk thresholds to trigger alerts, actions, and notifications.

Figure 5. Use actionable insights to identify apps exceeding a defined risk threshold.

Risk score investigation

To further investigate the specific Non-Human identity risk details, the factors contributing to the risk score are available in Non-Human Identities Risk score tab.

Figure 6. Detailed risk insights explaining factors contributing to the risk score.

Mitigation and protection guidance

Microsoft recommends the following mitigations to reduce the impact of this threat. Check the recommendations card for the deployment status of monitored mitigations.  

Microsoft Defender detections

Microsoft Defender customers can refer to the list of applicable detections including new detections powered by the upgraded Microsoft Defender for Cloud Apps Salesforce connector. Microsoft Defender coordinates detection, prevention, investigation, and response for endpoints, identities, email, and apps to provide integrated protection against attacks like the threat discussed in this blog.

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

Tactic Observed activity Microsoft Defender coverage 
Initial AccessA user’s Salesforce session was hijacked and usedSalesforce detected a possibly hijacked user session
Credential AccessA user was the target of credential stuffing activitySalesforce detected a successful credential stuffing attack
Lateral MovementA user with a very high risk score is signing into Salesforce via SSOSalesforce SSO sign-in by high-risk user
Collection / ExfiltrationAPI-heavy access, report export, and scraping patterns; potential multi-SaaS expansion depending on victim footprint.– Possible Salesforce scraping activity
– Salesforce detected a user performing anomalous API activity
– Salesforce detected a user performing anomalous report activity
Collection / ExfiltrationAnomalous behavior from Salesforce Connected Apps– Salesforce Connected App activity from a new IP address
– Salesforce Connected App activity involving new Salesforce entity
– Salesforce Connected App activity involving new endpoint(s)
Collection / ExfiltrationGuest user activity associated with the AuraInspector frameworkSuspicious Salesforce Aura Activity
Collection / ExfiltrationAnomalous behavior from a guest userSalesforce detected a guest user performing anomalous activity

Threat intelligence reports 

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

Advanced hunting

NOTE: The sample queries let you search one week of events. To inspect events and hunt for threat actor-related indicators over a longer period, go to the Advanced Hunting page > Query tab, and use the calendar dropdown to set the time range to Last 30 days (the maximum for raw data).

Hunt for Salesforce connected-app activity from suspicious infrastructure

CloudAppEvents
| where Application == "Salesforce"
| where ActionType in ("ApiTotalUsage", "API Event")
| extend ConnectedAppId = tostring(
    coalesce(
        RawEventData.CONNECTED_APP_ID, // from ApiTotalUsage 
        RawEventData.ConnectedAppId // from API Event
    )
)
| where isnotempty(ConnectedAppId)
| where array_length(UncommonForUser) > 0 // at least 1 attribute is flagged as uncommon

Hunt for API activity associated with connected apps and relevant user ids

CloudAppEvents
| where Application == "Salesforce"
| where ActionType in ("ApiTotalUsage", "API Event")
| extend SalesforceUserId=coalesce(tostring(RawEventData.USER_ID), tostring(RawEventData.UserId))
| extend ConnectedAppName=tostring(RawEventData.CONNECTED_APP_NAME)  // Connected App Name is not available on the ApiEvent event
| summarize count() by AccountObjectId, AccountId, AccountDisplayName, SalesforceUserId, IPAddress, UserAgent, ConnectedAppName

Hunt for anomalous report export / large data access

CloudAppEvents
| where Application == "Salesforce"
| where ActionType  == "ReportExport"
| extend SalesforceUserId = tostring(RawEventData.USER_ID)
| summarize Events=count() by AccountObjectId, AccountId, AccountName, SalesforceUserId, IPAddress, UserAgent

Pivot from a suspicious connected app (name/id) to impacted users and actions

CloudAppEvents
| where Application == "Salesforce"
| where RawEventData has ""
| project Timestamp, AccountId, AccountDisplayName, ActionType, IPAddress, UserAgent, RawEventData
| order by Timestamp desc

Audit queries to verify what objects users are accessing

CloudAppEvents
| where Application == "Salesforce"
| where ActionType == "UniqueQuery"
| extend 
    QueryText = tostring(RawEventData.QUERY_IDENTIFIER), // Full query text
    QueryObject = extract(@"(?i)\bfrom\s+([^\s]+)", 1, tostring(RawEventData.QUERY_IDENTIFIER)), // Extract just the target object
    SalesforceUserId = tostring(RawEventData.USER_ID)
| where QueryText != "SOQL"
| project Timestamp, AccountDisplayName, SalesforceUserId, QueryObject, QueryText

Hunt for users with very high Defender risk score signing into Salesforce

let VeryRiskyUsers = IdentityInfo
| where RiskScore >= 90
| distinct AccountObjectId
CloudAppEvents
| where Application == "Salesforce"
| where ActionType has "sso" or ActionType has "saml"
| where AccountObjectId in (VeryRiskyUsers)
| project Timestamp, AccountObjectId, AccountDisplayName, ActionType, UserAgent
| order by Timestamp desc

Indicators of compromise (IOC)

After further investigation, Microsoft has discovered that two of the reported IP addresses belong to a researcher conducting attack research. We have removed the IOCs from this report.

Indicator  Type  Description  
138.226.246.94 IP address Used by the Klue integration to call Salesforce API to perform CRM queries on June 11. Previously disclosed by Klue in their notification about the breach.
212.86.125.24 IP address 
213.111.148.90 IP address 
94.154.32.160 IP address 

MITRE ATT&CK techniques observed

Initial Access

  • T1566.004 Phishing: Voice Phishing: Impersonating IT support to get victims to grant access.
  • T1528 Steal Application Access Token: Using stolen OAuth tokens from Salesloft and Gainsight.

Persistence

  • T1671 Cloud Application Integration: Leveraging Connected Apps for access to a customer Salesforce environment.

Collection

  • T1213.004 Data from Information Repositories: Customer Relationship Management Software: Stealing data from a customer Salesforce environment.

Exfiltration

  • T1567 Exfiltration Over Web Service: Usage of the fake Data Loader application to steal data.

This research is provided by Microsoft Defender Security Research, Shruti Ranjit, Doug Cranston, Anand Deshpande, Ronen Rafaeli, and with contributions from members of Microsoft Threat Intelligence.

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 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.

Review our documentation to learn more about our real-time protection capabilities and see how to enable them within your organization.   

The post Defending SaaS-based applications against ShinyHunters OAuth abuse appeared first on Microsoft Security Blog.

]]>