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November 27, 2024

Behind the veil: Darktrace's detection of VPN exploitation in SaaS environments

A recent phishing attack compromised an internal email account, but Darktrace’s advanced AI quickly intervened. By identifying unusual activity across email and SaaS environments, Darktrace uncovered the attacker’s use of VPNs to mask their location and shut down the threat.
Inside the SOC
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
Written by
Priya Thapa
Cyber Analyst
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27
Nov 2024

Introduction

In today’s digital landscape, Software-as-a-Service (SaaS) platforms have become indispensable for businesses, offering unparalleled flexibly, scalability, and accessibly across locations. However, this convenience comes with a significant caveat - an expanded attack surface that cyber criminals are increasingly exploiting. In 2023, 96.7% of organizations reported security incidents involving at least one SaaS application [1].

Virtual private networks (VPNs) play a crucial role in SaaS security, acting as gateways for secure remote access and safeguarding sensitive data and systems when properly configured. However, vulnerabilities in VPNs can create openings for attacks to exploit, allowing them to infiltrate SaaS environments, compromise data, and disrupt business operations. Notably, in early 2024, the Darktrace Threat Research team investigated the exploitation of zero-day vulnerabilities in Ivanti Connect Secure VPNs, which would allow threat actors to gain access to sensitive systems and execute remote code.

More recently, in August, Darktrace identified a SaaS compromise where a threat actor logged into a customer’s VPN from an unusual IP address, following an initial email compromise. The attacker then used a separate VPN to create a new email rule designed to obfuscate the phishing campaign they would later launch.

Attack Overview

The initial attack vector in this case appeared to be through the customer’s email environment. A trusted external contact received a malicious email from another mutual contact who had been compromised and forwarded it to several of the organization’s employees, believing it to be legitimate. Attackers often send malicious emails from compromised accounts to their past contacts, leveraging the trust associated with familiar email addresses. In this case, that trust caused an external victim to unknowingly propagate the attack further. Unfortunately, an internal user then interacted with a malicious payload included in the reply section of the forwarded email.

Later the same day, Darktrace / IDENTITY detected unusual login attempts from the IP 5.62.57[.]7, which had never been accessed by other SaaS users before. There were two failed attempts prior to the successful logins, with the error messages “Authentication failed due to flow token expired” and “This occurred due to 'Keep me signed in' interrupt when the user was signing in.” These failed attempts indicate that the threat actor may have been attempting to gain unauthorized access using stolen credentials or exploiting session management vulnerabilities. Furthermore, there was no attempt to use multi-factor authentication (MFA) during the successful login, suggesting that the threat actor had compromised the account’s credentials.

Following this, Darktrace detected the now compromised account creating a new email rule named “.” – a telltale sign of a malicious actor attempting to hide behind an ambiguous or generic rule name.

The email rule itself was designed to archive incoming emails and mark them as read, effectively hiding them from the user’s immediate view. By moving emails to the “Archive” folder, which is not frequently checked by end users, the attacker can conceal malicious communications and avoid detection. The settings also prevent any automatic deletion of the rules or forced overrides, indicating a cautious approach to maintaining control over the mailbox without raising suspicion. This technique allows the attacker to manipulate email visibility while maintaining a façade of normality in the compromised account.

Email Rule:

  • AlwaysDeleteOutlookRulesBlob: False
  • Force: False
  • MoveToFolder: Archive
  • Name: .
  • MarkAsRead: True
  • StopProcessingRules: True

Darktrace further identified that this email rule had been created from another IP address, 95.142.124[.]42, this time located in Canada. Open-source intelligence (OSINT) sources indicated this endpoint may have been malicious [2].

Given that this new email rule was created just three minutes after the initial login from a different IP in a different country, Darktrace recognized a geographic inconsistency. By analyzing the timing and rarity of the involved IP addresses, Darktrace identified the likelihood of malicious activity rather than legitimate user behavior, prompting further investigation.

Figure 1: The compromised SaaS account making anomalous login attempts from an unusual IP address in the US, followed by the creation of a new email rule from another VPN IP in Canada.

Just one minute later, Darktrace observed the attacker sending a large number of phishing emails to both internal and external recipients.

Figure 2: The compromised SaaS user account sending a high volume of outbound emails to new recipients or containing suspicious content.

Darktrace / EMAIL detected a significant spike in inbound emails for the compromised account, likely indicating replies to phishing emails.

Figure 3: The figure demonstrates the spike in inbound emails detected for the compromised account, including phishing-related replies.

Furthermore, Darktrace identified that these phishing emails contained a malicious DocSend link. While docsend[.]com is generally recognized as a legitimate file-sharing service belonging to Dropbox, it can be vulnerable to exploitation for hosting malicious content. In this instance, the DocSend domain in question, ‘hxxps://docsend[.]com/view/h9t85su8njxtugmq’, was flagged as malicious by various OSINT vendors [3][4].

Figure 4: Phishing emails detected containing a malicious DocSend link.

In this case, Darktrace Autonomous Response was not in active mode in the customer’s environment, which allowed the compromise to escalate until their security team intervened based on Darktrace’s alerts. Had Autonomous Response been enabled during the incident, it could have quickly mitigated the threat by disabling users and inbox rules, as suggested by Darktrace as actions that could be manually applied, exhibiting unusual behavior within the customer’s SaaS environment.

Figure 5: Suggested Autonomous Response actions for this incident that required human confirmation.

Despite this, Darktrace’s Managed Threat Detection service promptly alerted the Security Operations Center (SOC) team about the compromise, allowing them to conduct a thorough investigation and inform the customer before any further damage could take place.

Conclusion

This incident highlights the role of Darktrace in enhancing cyber security through its advanced AI capabilities. By detecting the initial phishing email and tracking the threat actor's actions across the SaaS environment, Darktrace effectively identified the threat and brought it to the attention of the customer’s security team.

Darktrace’s proactive monitoring was crucial in recognizing the unusual behavior of the compromised account. Darktrace / IDENTITY detected unauthorized access attempts from rare IP addresses, revealing the attacker’s use of a VPN to hide their location.

Correlating these anomalies allowed Darktrace to prompt immediate investigation, showcasing its ability to identify malicious activities that traditional security tools might miss. By leveraging AI-driven insights, organizations can strengthen their defense posture and prevent further exploitation of compromised accounts.

Credit to Priya Thapa (Cyber Analyst), Ben Atkins (Senior Model Developer) and Ryan Traill (Analyst Content Lead)

Appendices

Real-time Detection Models

  • SaaS / Compromise / Unusual Login and New Email Rule
  • SaaS / Compromise / High Priority New Email Rule
  • SaaS / Compromise / New Email Rule and Unusual Email Activity
  • SaaS / Compromise / Unusual Login and Outbound Email Spam
  • SaaS / Compliance / Anomalous New Email Rule
  • SaaS / Compromise / Suspicious Login and Suspicious Outbound Email(s)
  • SaaS / Email Nexus / Possible Outbound Email Spam

Autonomous Response Models

  • Antigena / SaaS / Antigena Email Rule Block
  • Antigena / SaaS / Antigena Enhanced Monitoring from SaaS User Block
  • Antigena / SaaS / Antigena Suspicious SaaS Activity Block

MITRE ATT&CK Mapping

Technique Name Tactic ID Sub-Technique of

  • Cloud Accounts. DEFENSE EVASION, PERSISTENCE, PRIVILEGE ESCALATION, INITIAL ACCESS T1078.004 T1078
  • Compromise Accounts RESOURCE DEVELOPMENT T1586
  • Email Accounts RESOURCE DEVELOPMENT T1586.002 T1586
  • Internal Spearphishing LATERAL MOVEMENT T1534 -
  • Outlook Rules PERSISTENCE T1137.005 T1137
  • Phishing INITIAL ACCESS T1566 -

Indicators of Compromise (IoCs)

IoC – Type – Description

5.62.57[.]7 – Unusual Login Source

95.142.124[.]42– IP – Unusual Source for Email Rule

hxxps://docsend[.]com/view/h9t85su8njxtugmq - Domain - Phishing Link

References

[1] https://wing.security/wp-content/uploads/2024/02/2024-State-of-SaaS-Report-Wing-Security.pdf

[2] https://www.virustotal.com/gui/ip-address/95.142.124.42

[3] https://urlscan.io/result/0caf3eee-9275-4cda-a28f-6d3c6c3c1039/

[4] https://www.virustotal.com/gui/url/8631f8004ee000b3f74461e5060e6972759c8d38ea8c359d85da9014101daddb

Inside the SOC
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
Written by
Priya Thapa
Cyber Analyst

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December 18, 2025

Why organizations are moving to label-free, behavioral DLP for outbound email

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Why outbound email DLP needs reinventing

In 2025, the global average cost of a data breach fell slightly — but remains substantial at USD 4.44 million (IBM Cost of a Data Breach Report 2025). The headline figure hides a painful reality: many of these breaches stem not from sophisticated hacks, but from simple human error: mis-sent emails, accidental forwarding, or replying with the wrong attachment. Because outbound email is a common channel for sensitive data leaving an organization, the risk posed by everyday mistakes is enormous.

In 2025, 53% of data breaches involved customer PII, making it the most commonly compromised asset (IBM Cost of a Data Breach Report 2025). This makes “protection at the moment of send” essential. A single unintended disclosure can trigger compliance violations, regulatory scrutiny, and erosion of customer trust –consequences that are disproportionate to the marginal human errors that cause them.

Traditional DLP has long attempted to mitigate these impacts, but it relies heavily on perfect labelling and rigid pattern-matching. In reality, data loss rarely presents itself as a neat, well-structured pattern waiting to be caught – it looks like everyday communication, just slightly out of context.

How data loss actually happens

Most data loss comes from frustratingly familiar scenarios. A mistyped name in auto-complete sends sensitive data to the wrong “Alex.” A user forwards a document to a personal Gmail account “just this once.” Someone shares an attachment with a new or unknown correspondent without realizing how sensitive it is.

Traditional, content-centric DLP rarely catches these moments. Labels are missing or wrong. Regexes break the moment the data shifts formats. And static rules can’t interpret the context that actually matters – the sender-recipient relationship, the communication history, or whether this behavior is typical for the user.

It’s the everyday mistakes that hurt the most. The classic example: the Friday 5:58 p.m. mis-send, when auto-complete selects Martin, a former contractor, instead of Marta in Finance.

What traditional DLP approaches offer (and where gaps remain)

Most email DLP today follows two patterns, each useful but incomplete.

  • Policy- and label-centric DLP works when labels are correct — but content is often unlabeled or mislabeled, and maintaining classification adds friction. Gaps appear exactly where users move fastest
  • Rule and signature-based approaches catch known patterns but miss nuance: human error, new workflows, and “unknown unknowns” that don’t match a rule

The takeaway: Protection must combine content + behavior + explainability at send time, without depending on perfect labels.

Your technology primer: The three pillars that make outbound DLP effective

1) Label-free (vs. data classification)

Protects all content, not just what’s labeled. Label-free analysis removes classification overhead and closes gaps from missing or incorrect tags. By evaluating content and context at send time, it also catches misdelivery and other payload-free errors.

  • No labeling burden; no regex/rule maintenance
  • Works when tags are missing, wrong, or stale
  • Detects misdirected sends even when labels look right

2) Behavioral (vs. rules, signatures, threat intelligence)

Understands user behavior, not just static patterns. Behavioral analysis learns what’s normal for each person, surfacing human error and subtle exfiltration that rules can’t. It also incorporates account signals and inbound intel, extending across email and Teams.

  • Flags risk without predefined rules or IOCs
  • Catches misdelivery, unusual contacts, personal forwards, odd timing/volume
  • Blends identity and inbound context across channels

3) Proprietary DSLM (vs. generic LLM)

Optimized for precise, fast, explainable on-send decisions. A DSLM understands email/DLP semantics, avoids generative risks, and stays auditable and privacy-controlled, delivering intelligence reliably without slowing mail flow.

  • Low-latency, on-send enforcement
  • Non-generative for predictable, explainable outcomes
  • Governed model with strong privacy and auditability

The Darktrace approach to DLP

Darktrace / EMAIL – DLP stops misdelivery and sensitive data loss at send time using hold/notify/justify/release actions. It blends behavioral insight with content understanding across 35+ PII categories, protecting both labeled and unlabeled data. Every action is paired with clear explainability: AI narratives show exactly why an email was flagged, supporting analysts and helping end-users learn. Deployment aligns cleanly with existing SOC workflows through mail-flow connectors and optional Microsoft Purview label ingestion, without forcing duplicate policy-building.

Deployment is simple: Microsoft 365 routes outbound mail to Darktrace for real-time, inline decisions without regex or rule-heavy setup.

A buyer’s checklist for DLP solutions

When choosing your DLP solution, you want to be sure that it can deliver precise, explainable protection at the moment it matters – on send – without operational drag.  

To finish, we’ve compiled a handy list of questions you can ask before choosing an outbound DLP solution:

  • Can it operate label free when tags are missing or wrong? 
  • Does it truly learn per user behavior (no shortcuts)? 
  • Is there a domain specific model behind the content understanding (not a generic LLM)? 
  • Does it explain decisions to both analysts and end users? 
  • Will it integrate with your label program and SOC workflows rather than duplicate them? 

For a deep dive into Darktrace’s DLP solution, check out the full solution brief.

[related-resource]

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About the author
Carlos Gray
Senior Product Marketing Manager, Email

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December 17, 2025

Beyond MFA: Detecting Adversary-in-the-Middle Attacks and Phishing with Darktrace

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What is an Adversary-in-the-middle (AiTM) attack?

Adversary-in-the-Middle (AiTM) attacks are a sophisticated technique often paired with phishing campaigns to steal user credentials. Unlike traditional phishing, which multi-factor authentication (MFA) increasingly mitigates, AiTM attacks leverage reverse proxy servers to intercept authentication tokens and session cookies. This allows attackers to bypass MFA entirely and hijack active sessions, stealthily maintaining access without repeated logins.

This blog examines a real-world incident detected during a Darktrace customer trial, highlighting how Darktrace / EMAILTM and Darktrace / IDENTITYTM identified the emerging compromise in a customer’s email and software-as-a-service (SaaS) environment, tracked its progression, and could have intervened at critical moments to contain the threat had Darktrace’s Autonomous Response capability been enabled.

What does an AiTM attack look like?

Inbound phishing email

Attacks typically begin with a phishing email, often originating from the compromised account of a known contact like a vendor or business partner. These emails will often contain malicious links or attachments leading to fake login pages designed to spoof legitimate login platforms, like Microsoft 365, designed to harvest user credentials.

Proxy-based credential theft and session hijacking

When a user clicks on a malicious link, they are redirected through an attacker-controlled proxy that impersonates legitimate services.  This proxy forwards login requests to Microsoft, making the login page appear legitimate. After the user successfully completes MFA, the attacker captures credentials and session tokens, enabling full account takeover without the need for reauthentication.

Follow-on attacks

Once inside, attackers will typically establish persistence through the creation of email rules or registering OAuth applications. From there, they often act on their objectives, exfiltrating sensitive data and launching additional business email compromise (BEC) campaigns. These campaigns can include fraudulent payment requests to external contacts or internal phishing designed to compromise more accounts and enable lateral movement across the organization.

Darktrace’s detection of an AiTM attack

At the end of September 2025, Darktrace detected one such example of an AiTM attack on the network of a customer trialling Darktrace / EMAIL and Darktrace / IDENTITY.

In this instance, the first indicator of compromise observed by Darktrace was the creation of a malicious email rule on one of the customer’s Office 365 accounts, suggesting the account had likely already been compromised before Darktrace was deployed for the trial.

Darktrace / IDENTITY observed the account creating a new email rule with a randomly generated name, likely to hide its presence from the legitimate account owner. The rule marked all inbound emails as read and deleted them, while ignoring any existing mail rules on the account. This rule was likely intended to conceal any replies to malicious emails the attacker had sent from the legitimate account owner and to facilitate further phishing attempts.

Darktrace’s detection of the anomalous email rule creation.
Figure 1: Darktrace’s detection of the anomalous email rule creation.

Internal and external phishing

Following the creation of the email rule, Darktrace / EMAIL observed a surge of suspicious activity on the user’s account. The account sent emails with subject lines referencing payment information to over 9,000 different external recipients within just one hour. Darktrace also identified that these emails contained a link to an unusual Google Drive endpoint, embedded in the text “download order and invoice”.

Darkrace’s detection of an unusual surge in outbound emails containing suspicious content, shortly following the creation of a new email rule.
Figure 2: Darkrace’s detection of an unusual surge in outbound emails containing suspicious content, shortly following the creation of a new email rule.
Darktrace / EMAIL’s detection of the compromised account sending over 9,000 external phishing emails, containing an unusual Google Drive link.
Figure 3: Darktrace / EMAIL’s detection of the compromised account sending over 9,000 external phishing emails, containing an unusual Google Drive link.

As Darktrace / EMAIL flagged the message with the ‘Compromise Indicators’ tag (Figure 2), it would have been held automatically if the customer had enabled default Data Loss Prevention (DLP) Action Flows in their email environment, preventing any external phishing attempts.

Figure 4: Darktrace / EMAIL’s preview of the email sent by the offending account.
Figure 4: Darktrace / EMAIL’s preview of the email sent by the offending account.

Darktrace analysis revealed that, after clicking the malicious link in the email, recipients would be redirected to a convincing landing page that closely mimicked the customer’s legitimate branding, including authentic imagery and logos, where prompted to download with a PDF named “invoice”.

Figure 5: Download and login prompts presented to recipients after following the malicious email link, shown here in safe view.

After clicking the “Download” button, users would be prompted to enter their company credentials on a page that was likely a credential-harvesting tool, designed to steal corporate login details and enable further compromise of SaaS and email accounts.

Darktrace’s Response

In this case, Darktrace’s Autonomous Response was not fully enabled across the customer’s email or SaaS environments, allowing the compromise to progress,  as observed by Darktrace here.

Despite this, Darktrace / EMAIL’s successful detection of the malicious Google Drive link in the internal phishing emails prompted it to suggest ‘Lock Link’, as a recommended action for the customer’s security team to manually apply. This action would have automatically placed the malicious link behind a warning or screening page blocking users from visiting it.

Autonomous Response suggesting locking the malicious Google Drive link sent in internal phishing emails.
Figure 6: Autonomous Response suggesting locking the malicious Google Drive link sent in internal phishing emails.

Furthermore, if active in the customer’s SaaS environment, Darktrace would likely have been able to mitigate the threat even earlier, at the point of the first unusual activity: the creation of a new email rule. Mitigative actions would have included forcing the user to log out, terminating any active sessions, and disabling the account.

Conclusion

AiTM attacks represent a significant evolution in credential theft techniques, enabling attackers to bypass MFA and hijack active sessions through reverse proxy infrastructure. In the real-world case we explored, Darktrace’s AI-driven detection identified multiple stages of the attack, from anomalous email rule creation to suspicious internal email activity, demonstrating how Autonomous Response could have contained the threat before escalation.

MFA is a critical security measure, but it is no longer a silver bullet. Attackers are increasingly targeting session tokens rather than passwords, exploiting trusted SaaS environments and internal communications to remain undetected. Behavioral AI provides a vital layer of defense by spotting subtle anomalies that traditional tools often miss

Security teams must move beyond static defenses and embrace adaptive, AI-driven solutions that can detect and respond in real time. Regularly review SaaS configurations, enforce conditional access policies, and deploy technologies that understand “normal” behavior to stop attackers before they succeed.

Credit to David Ison (Cyber Analyst), Bertille Pierron (Solutions Engineer), Ryan Traill (Analyst Content Lead)

Appendices

Models

SaaS / Anomalous New Email Rule

Tactic – Technique – Sub-Technique  

Phishing - T1566

Adversary-in-the-Middle - T1557

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