Blog
/
Identity
/
May 25, 2022

Multi-Account Compromise in Office 365

Learn how internal phishing can compromise accounts swiftly & how Darktrace/Apps can prevent future attacks effectively.
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
Laura Leyland
Cyber Analyst
Default blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog image
25
May 2022

In February 2022, Darktrace detected the compromise of three SaaS accounts within a customer’s Office 365 environment. This incident provides an effective use case for highlighting how Darktrace/Apps and Darktrace/Email can work together to alert to unusual logins, app permission changes, new email rules and outbound spam. It also emphasizes an instance where Darktrace RESPOND/Apps could have been set to autonomous mode and stopped additional compromise.

Account Compromise Timeline

February 9 2022

Account A was logged into from a rare IP from Nigeria with the BAV2ROPC user agent which is commonly associated with SaaS account attacks. BAV2ROPC stands for ‘Basic Authentication Version 2 Resource Owner Password Credential’ and is commonly used by old email apps such as iOS Mail. It is often seen in SaaS/email account compromises where accounts have ‘legacy authentication’ enabled. This is because, even if multi-factor authentication (MFA) is activated, legacy protocols like IMAP/POP3 are not configured for MFA and so do not result in an MFA notification being sent.[1][2]

Account A then created a new email rule which was named as a single full stop. Attackers commonly create new email rules to give themselves persistent access by using the ability to forward certain emails to external email accounts they own. This means that even if the account’s password is changed or MFA is turned on, the attacker keeps getting the forwarded emails as long as the rule remains in place. In this case, the attacker configured the new email rule using the following fields and features:

  • AlwaysDeleteOutlookRulesBlob – hides any warning messages when using Outlook on the web or Powershell to edit inbox rules. It is likely that the attacker had a set list of commands to run and didn’t want to be slowed down in the exploitation of the account by having to click confirmation messages.
  • Force – hides warning or confirmation messages.
  • MoveToFolder – moves emails to a folder. This is often used to move bounced emails away from the inbox in order to hide the fact the account is being used to send emails by the attacker.
  • Name – specifies the name of the rule, in this case a single full stop.
  • SubjectOrBodyContainsWords – emails with key words are actioned.
  • StopProcessingRules – determines whether subsequent rules are processed if the conditions of this rule are met. It is likely in this case the attacker set this to false so that any subsequent rules would still be processed to avoid raising suspicion.

Account A was then observed giving permission to the email management app Spike. This was likely to allow the rapid automated exploitation of the compromised account. Attackers want to speed up this process to reduce the time between account compromise and malicious use of the account, thus reducing the time security teams have to respond.

Figure 1: Screenshot from SaaS console showing the timeline of giving consent to the email management application Spike and the creation of the new inbox rule

The account was then observed sending 794 emails over a 15 minute period to both internal and external recipients. These emails shared similar qualities including the same subject line and related phishing links. This mass spam was likely due to the attacker wanting to compromise as many accounts and credentials as possible within the shortest timeframe. The domain of the link sent in the emails was spikenow[.]com and was hidden by the text ‘View Shared Link’. This suggests that the attacker used Spike to send the emails and host the phishing link.

Figure 2: Screenshot of AGE UI showing the spike in outbound messages from the compromised account – the messages all appear to be the same format
Figure 3: Screenshot from Darktrace/Email of the link and text that masked the link: ‘View Shared File’

Within 15 minutes of this large volume of outbound email from Account A, Account B was accessed from the same rare IP located in Nigeria. Account B also created a new email rule which was named a single full stop. In addition to the previous rules, the following rules were observed:

  • From – specifies that emails from certain addresses will be processed by the rule.
  • MarkAsRead – specifies that emails are to be marked as read.

Due to the short timeframe between the phishing emails and the anomalous behavior from Account B, it is possible that Account B was an initial phishing victim.

Figure 4: Screenshot of the SaaS console showing Account B login failures, then successful login and inbox rule creation from the rare Nigerian IP

February 10 2022

The next day, a third account (Account C) was also accessed from the same rare IP. This occurred on two occasions, once with the user agent Mozilla/5.0 and once with BAV2ROPC. After the login at 13:08 with BAV2ROPC, the account gave the same permission as Account A to the email management app Spike. It then created what appears to be the same email rule, named a single full stop. As with Account B, it is possible that this account was compromised by one of the phishing emails sent by Account A.

Figure 5: Timeline of key incidents with Darktrace/Apps actions

Whilst the motive of the threat actor was unclear, this may have been the result of:

  • Credential harvesting for future use against the organization or to sell to a third party.
  • Possible impersonation of compromised users on professional websites (LinkedIn, Indeed) to phish further company accounts:
  • Fake accounts of one user were discovered on LinkedIn.
  • Emails registering for Indeed for this same user were seen during compromise.

How did the attack bypass the rest of the security stack?

  • Compromised Office 365 credentials, combined with the use of the user agent BAV2ROPC meant MFA could not stop the suspicious login.
  • RESPOND was in Human Confirmation Mode and was therefore not confirmed to take autonomous action, showing only the detections. Disabling Account A would likely have prevented the phishing emails and the subsequent compromise of Accounts B and C.
  • The organization was not signed up to Darktrace Proactive Threat Notifications or Ask The Expert services which could have allowed further triage from Darktrace SOC analysts.

Cyber AI Analyst Investigates

Darktrace’s Cyber AI Analyst automates investigations at speed and scale, prioritizing relevant incidents and creating actionable insights, allowing security teams to rapidly understand and act against a threat.

In this case, AI Analyst automatically investigated all three account compromises, saving time for the customer’s security team and allowing them to quickly investigate the incident themselves in more detail. The technology also highlighted some of the viewed files by the compromised accounts which was not immediately obvious from the model breaches alone.

Figure 6: Screenshot of AI Analyst for Account A
Figure 7: Screenshot of AI Analyst for Account B
Figure 8: Screenshot of AI Analyst for Account C

Darktrace RESPOND (Antigena) actions

The organization in question did not have RESPOND/Apps configured in Active Mode, and so it did not take any action in this case. The table below shows the critical defensive actions RESPOND would have taken.[3]

Nonetheless, we can see what actions RESPOND would have taken, and when, had the technology been enabled.

The above tables illustrate that all three users would have been disabled during the incident had RESPOND been active. The highlighted row shows that Account A would have been disabled when the internal phishing emails were sent and possibly then prevented the cascade of compromised email accounts (B and C).

Conclusion

SaaS accounts greatly increase a company’s attack surface. Not only is exploitation of compromised accounts quick, but a single compromised account can easily lead to further compromises via an internal phishing campaign. Together this reinforces the ongoing need for autonomous and proactive security to complement existing IT teams and reduce threats at the point of compromise. Whilst disabling ‘legacy authentication’ for all accounts and providing MFA would give some extra protection, Darktrace/Apps has the ability to block all further infection.

Credit to: Adam Stevens and Anthony Wong for their contributions.

Appendix

List of Darktrace Model Detections

User A – February 9 2022

  • 04:55:51 UTC | SaaS / Access / Suspicious Login User-Agent
  • 04:55:51 UTC | SaaS / Access / Unusual External Source for SaaS Credential Use
  • 04:55:52 UTC | Antigena / SaaS / Antigena Suspicious SaaS and Email Activity Block
  • 04:55:52 UTC | Antigena / SaaS / Antigena Suspicious SaaS Activity Block
  • 14:16:48 UTC | SaaS / Compliance / New Email Rule
  • 14:16:48 UTC | SaaS / Compromise / Unusual Login and New Email Rule
  • 14:16:49 UTC | Antigena / SaaS / Antigena Significant Compliance Activity Block
  • 14:16:49 UTC | Antigena / SaaS / Antigena Suspicious SaaS Activity Block
  • 14:45:06 UTC | IaaS / Admin / Azure Application Administration Activities
  • 14:45:07 UTC | SaaS / Admin / OAuth Permission Grant
  • 14:45:07 UTC | Device / Multiple Model Breaches
  • 14:45:08 UTC | SaaS / Compliance / Multiple Unusual SaaS Activities
  • 15:03:25 UTC | SaaS / Email Nexus / Possible Outbound Email Spam
  • 15:03:25 UTC | SaaS / Compromise / Unusual Login and Outbound Email Spam

User B – February 9 2022

  • 15:18:21 UTC | SaaS / Compliance / New Email Rule
  • 15:18:21 UTC | SaaS / Compromise / Unusual Login and New Email Rule
  • 15:18:22 UTC | Antigena / SaaS / Antigena Significant Compliance Activity Block
  • 15:18:22 UTC | Antigena / SaaS / Antigena Suspicious SaaS Activity Block

User C – February 10 2022

  • 14:25:20 UTC | SaaS / Admin / OAuth Permission Grant
  • 14:38:09 UTC | SaaS / Compliance / New Email Rule
  • 14:38:09 UTC | SaaS / Compromise / Unusual Login and New Email Rule
  • 14:38:10 UTC | Antigena / SaaS / Antigena Significant Compliance Activity Block
  • 14:38:10 UTC | Antigena / SaaS / Antigena Suspicious SaaS Activity Block

Refrences

1. https://www.ncsc.gov.uk/guidance/phishing#section_3

2. https://www.bleepingcomputer.com/news/security/microsoft-scammers-bypass-office-365-mfa-in-bec-attacks/

3. https://customerportal.darktrace.com/product-guides/main/antigena-saas-inhibitors

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
Laura Leyland
Cyber Analyst

More in this series

No items found.

Blog

/

Compliance

/

November 25, 2025

UK Cyber Security & Resilience Bill: What Organizations Need to Know

Default blog imageDefault blog image

Why the Bill has been introduced

The UK’s cyber threat landscape has evolved dramatically since the 2018 NIS regime was introduced. Incidents such as the Synnovis attack against hospitals and the British Library ransomware attack show how quickly operational risk can become public harm. In this context, the UK Department for Science, Innovation and Technology estimates that cyber-attacks cost UK businesses around £14.7 billion each year.

At the same time, the widespread adoption of AI has expanded organisations’ attack surfaces and empowered threat actors to launch more effective and sophisticated activities, including crafting convincing phishing campaigns, exploiting vulnerabilities and initiating ransomware attacks at unprecedented speed and scale.  

The CSRB responds to these challenges by widening who is regulated, accelerating incident reporting and tightening supply chain accountability, while enabling rapid updates that keep pace with technology and emerging risks.

Key provisions of the Cyber Security and Resilience Bill

A wider set of organisations in scope

The Bill significantly broadens the range of organisations regulated under the NIS framework.

  • Managed service providers (MSPs) - medium and large MSPs, including MSSPs, managed SOCs, SIEM providers and similar services,will now fall under NIS obligations due to their systemic importance and privileged access to client systems. The Information Commissioner’s Office (ICO) will act as the regulator. Government analysis anticipates that a further 900 to 1,100 MSPs will be in scope.
  • Data infrastructure is now recognised as essential to the functioning of the economy and public services. Medium and large data centres, as well as enterprise facilities meeting specified thresholds, will be required to implement appropriate and proportionate measures to manage cyber risk. Oversight will be shared between DSIT and Ofcom, with Ofcom serving as the operational regulator.
  • Organisations that manage electrical loads for smart appliances, such as those supporting EV charging during peak times, are now within scope.

These additions sit alongside existing NIS-regulated sectors such as transport, energy, water, health, digital infrastructure, and certain digital services (including online marketplaces, search engines, and cloud computing).

Stronger supply chain requirements

Under the CSRB, regulators can now designate third-party suppliers as ‘designated critical suppliers’ (DCS) when certain threshold criteria are met and where disruption could have significant knock-on effects. Designated suppliers will be subject to the same security and incident-reporting obligations as Operators of Essential Services (OES) and Relevant Digital Service Providers (RDSPs).

Government will scope the supply chain duties for OES and RDSPs via secondary legislation, following consultation. infrastructure incidents where a single supplier’s compromise caused widespread disruption.

Faster incident reporting

Sector-specific regulators, 12 in total, will be responsible for implementing the CSRB, allowing for more effective and consistent reporting. In addition, the CSRB introduces a two-stage reporting process and expands incident reporting criteria. Regulated entities must submit an initial notification within 24 hours of becoming aware of a significant incident, followed by an incident report within 72 hours. Incident reporting criteria are also broadened to capture incidents beyond those which actually resulted in an interruption, ensuring earlier visibility for regulators and the National Cyber Security Centre (NCSC). The importance of information sharing across agencies, law enforcement and regulators is also facilitated by the CSRB.

The reforms also require data centres and managed service providers to notify affected customers where they are likely to have been impacted by a cyber incident.

An agile regulatory framework

To keep pace with technological change, the CSRB will enable the Secretary of State to update elements of the framework via secondary legislation. Supporting materials such as the NCSC Cyber Assessment Framework (CAF) are to be "put on a stronger footing” allowing for requirements to be more easily followed, managed and updated. Regulators will also now be able to recover full costs associated with NIS duties meaning they are better resourced to carry out their associated responsibilities.

Relevant Managed Service Providers must identify and take appropriate and proportionate measures to manage risks to the systems they rely on for providing services within the UK. Importantly, these measures must, having regard to the state of the art, ensure a level of security appropriate to the risk posed, and prevent or minimise the impact of incidents.

The Secretary of State will also be empowered to issue a Statement of Strategic Priorities, setting cross-regime outcomes to drive consistency across the 12 competent authorities responsible for implementation.

Penalties

The enforcement framework will be strengthened, with maximum fines aligned with comparable regimes such as the GDPR, which incorporate maximums tied to turnover. Under the CSRB, maximum penalties for more serious breaches could be up to £17 million or 4% of global turnover, whichever is higher.

Next steps

The Bill is expected to progress through Parliament over the course of 2025 and early 2026, with Royal Assent anticipated in 2026. Once enacted, most operational measures will not take immediate effect. Instead, Government will bring key components into force through secondary legislation following further consultation, providing regulators and industry with time to adjust practices and prepare for compliance.

Anticipated timeline

  • 2025-2026: Parliamentary scrutiny and passage;
  • 2026: Royal Assent;  
  • 2026 consultation: DSIT intends to consult on detailed implementation;
  • From 2026 onwards: Phased implementation via secondary legislation, following further consultation led by DSIT.

How Darktrace can help

The CSRB represents a step change in how the UK approaches digital risk, shifting the focus from compliance to resilience.

Darktrace can help organisations operationalise this shift by using AI to detect, investigate and respond to emerging threats at machine speed, before they escalate into incidents requiring regulatory notification. Proactive tools which can be included in the Darktrace platform allow security teams to stress-test defences, map supply chain exposure and rehearse recovery scenarios, directly supporting the CSRB’s focus on resilience, transparency and rapid response. If an incident does occur, Darktrace’s autonomous agent, Cyber AI Analyst, can accelerate investigations and provide a view of every stage of the attack chain, supporting timely reporting.  

Darktrace’s AI can provide organisations with a vital lens into both internal and external cyber risk. By continuously learning patterns of behaviour across interconnected systems, Darktrace can flag potential compromise or disruption to detect supply chain risk before it impacts your organisation.

In a landscape where compliance and resilience go hand in hand, Darktrace can equip organisations to stay ahead of both evolving threats and evolving regulatory requirements.

[related-resource]

Continue reading
About the author
The Darktrace Community

Blog

/

OT

/

November 20, 2025

Managing OT Remote Access with Zero Trust Control & AI Driven Detection

managing OT remote access with zero trust control and ai driven detectionDefault blog imageDefault blog image

The shift toward IT-OT convergence

Recently, industrial environments have become more connected and dependent on external collaboration. As a result, truly air-gapped OT systems have become less of a reality, especially when working with OEM-managed assets, legacy equipment requiring remote diagnostics, or third-party integrators who routinely connect in.

This convergence, whether it’s driven by digital transformation mandates or operational efficiency goals, are making OT environments more connected, more automated, and more intertwined with IT systems. While this convergence opens new possibilities, it also exposes the environment to risks that traditional OT architectures were never designed to withstand.

The modernization gap and why visibility alone isn’t enough

The push toward modernization has introduced new technology into industrial environments, creating convergence between IT and OT environments, and resulting in a lack of visibility. However, regaining that visibility is just a starting point. Visibility only tells you what is connected, not how access should be governed. And this is where the divide between IT and OT becomes unavoidable.

Security strategies that work well in IT often fall short in OT, where even small missteps can lead to environmental risk, safety incidents, or costly disruptions. Add in mounting regulatory pressure to enforce secure access, enforce segmentation, and demonstrate accountability, and it becomes clear: visibility alone is no longer sufficient. What industrial environments need now is precision. They need control. And they need to implement both without interrupting operations. All this requires identity-based access controls, real-time session oversight, and continuous behavioral detection.

The risk of unmonitored remote access

This risk becomes most evident during critical moments, such as when an OEM needs urgent access to troubleshoot a malfunctioning asset.

Under that time pressure, access is often provisioned quickly with minimal verification, bypassing established processes. Once inside, there’s little to no real-time oversight of user actions whether they’re executing commands, changing configurations, or moving laterally across the network. These actions typically go unlogged or unnoticed until something breaks. At that point, teams are stuck piecing together fragmented logs or post-incident forensics, with no clear line of accountability.  

In environments where uptime is critical and safety is non-negotiable, this level of uncertainty simply isn’t sustainable.

The visibility gap: Who’s doing what, and when?

The fundamental issue we encounter is the disconnect between who has access and what they are doing with it.  

Traditional access management tools may validate credentials and restrict entry points, but they rarely provide real-time visibility into in-session activity. Even fewer can distinguish between expected vendor behavior and subtle signs of compromise, misuse or misconfiguration.  

As a result, OT and security teams are often left blind to the most critical part of the puzzle, intent and behavior.

Closing the gaps with zero trust controls and AI‑driven detection

Managing remote access in OT is no longer just about granting a connection, it’s about enforcing strict access parameters while continuously monitoring for abnormal behavior. This requires a two-pronged approach: precision access control, and intelligent, real-time detection.

Zero Trust access controls provide the foundation. By enforcing identity-based, just-in-time permissions, OT environments can ensure that vendors and remote users only access the systems they’re explicitly authorized to interact with, and only for the time they need. These controls should be granular enough to limit access down to specific devices, commands, or functions. By applying these principles consistently across the Purdue Model, organizations can eliminate reliance on catch-all VPN tunnels, jump servers, and brittle firewall exceptions that expose the environment to excess risk.

Access control is only one part of the equation

Darktrace / OT complements zero trust controls with continuous, AI-driven behavioral detection. Rather than relying on static rules or pre-defined signatures, Darktrace uses Self-Learning AI to build a live, evolving understanding of what’s “normal” in the environment, across every device, protocol, and user. This enables real-time detection of subtle misconfigurations, credential misuse, or lateral movement as they happen, not after the fact.

By correlating user identity and session activity with behavioral analytics, Darktrace gives organizations the full picture: who accessed which system, what actions they performed, how those actions compared to historical norms, and whether any deviations occurred. It eliminates guesswork around remote access sessions and replaces it with clear, contextual insight.

Importantly, Darktrace distinguishes between operational noise and true cyber-relevant anomalies. Unlike other tools that lump everything, from CVE alerts to routine activity, into a single stream, Darktrace separates legitimate remote access behavior from potential misuse or abuse. This means organizations can both audit access from a compliance standpoint and be confident that if a session is ever exploited, the misuse will be surfaced as a high-fidelity, cyber-relevant alert. This approach serves as a compensating control, ensuring that even if access is overextended or misused, the behavior is still visible and actionable.

If a session deviates from learned baselines, such as an unusual command sequence, new lateral movement path, or activity outside of scheduled hours, Darktrace can flag it immediately. These insights can be used to trigger manual investigation or automated enforcement actions, such as access revocation or session isolation, depending on policy.

This layered approach enables real-time decision-making, supports uninterrupted operations, and delivers complete accountability for all remote activity, without slowing down critical work or disrupting industrial workflows.

Where Zero Trust Access Meets AI‑Driven Oversight:

  • Granular Access Enforcement: Role-based, just-in-time access that aligns with Zero Trust principles and meets compliance expectations.
  • Context-Enriched Threat Detection: Self-Learning AI detects anomalous OT behavior in real time and ties threats to access events and user activity.
  • Automated Session Oversight: Behavioral anomalies can trigger alerting or automated controls, reducing time-to-contain while preserving uptime.
  • Full Visibility Across Purdue Layers: Correlated data connects remote access events with device-level behavior, spanning IT and OT layers.
  • Scalable, Passive Monitoring: Passive behavioral learning enables coverage across legacy systems and air-gapped environments, no signatures, agents, or intrusive scans required.

Complete security without compromise

We no longer have to choose between operational agility and security control, or between visibility and simplicity. A Zero Trust approach, reinforced by real-time AI detection, enables secure remote access that is both permission-aware and behavior-aware, tailored to the realities of industrial operations and scalable across diverse environments.

Because when it comes to protecting critical infrastructure, access without detection is a risk and detection without access control is incomplete.

Continue reading
About the author
Pallavi Singh
Product Marketing Manager, OT Security & Compliance
Your data. Our AI.
Elevate your network security with Darktrace AI