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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
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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

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August 13, 2025

ISO/IEC 42001: 2023: A milestone in AI standards at Darktrace  

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Darktrace announces ISO/IEC 42001 accreditation

Darktrace is thrilled to announce that we are one of the first cybersecurity companies to achieve ISO/IEC 42001 accreditation for the responsible management of AI systems. This isn’t just a milestone for us, it’s a sign of where the AI industry is headed. ISO/IEC 42001 is quickly emerging as the global benchmark for separating vendors who truly innovate with AI from those who simply market it.

For customers, it’s more than a badge, it’s assurance that a vendor’s AI is built responsibly, governed with rigor, and backed by the expertise of real AI teams, keeping your data secure while driving meaningful innovation.

This is a critical milestone for Darktrace as we continue to strengthen our offering, mature our governance and compliance frameworks for AI management, expand our research and development capabilities, and further our commitment to the development of responsible AI.  

It cements our commitment to providing secure, trustworthy and proactive cybersecurity solutions that our customers can rely on and complements our existing compliance framework, consisting of certifications for:

  • ISO/IEC 27001:2022 – Information Security Management System
  • ISO/IEC 27018:2019 – Protection of Personally Identifiable Information in Public Cloud Environments
  • Cyber Essentials – A UK Government-backed certification scheme for cybersecurity baselines

What is ISO/IEC 42001:2023?

In response to the unique challenges that AI poses, the International Organization for Standardization (ISO) introduced the ISO/IEC 42001:2023 framework in December 2023 to help organizations providing or utilizing AI-based products or services to demonstrate responsible development and use of AI systems. To achieve the accreditation, organizations are required to establish, implement, maintain, and continually improve their Artificial Intelligence Management System (AIMS).

ISO/IEC 42001:2023 is the first of its kind, providing valuable guidance for this rapidly changing field of technology. It addresses the unique ethical and technical challenges AI poses by setting out a structured way to manage risks such as transparency, accuracy and misuse without losing opportunities. By design, it balances the benefits of innovation against the necessity of a proper governance structure.

Being certified means the organization has met the requirements of the ISO/IEC 42001 standard, is conforming to all applicable regulatory and legislative requirements, and has implemented thorough processes to address AI risks and opportunities.

What is the  ISO/IEC 42001:2023 accreditation process?

Darktrace partnered with BSI over an 11-month period to undertake the accreditation. The process involved developing and implementing a comprehensive AI management system that builds on our existing certified frameworks, addresses the risks and opportunities of using and developing cutting-edge AI systems, underpins our AI objectives and policies, and meets our regulatory and legal compliance requirements.

The AI Management System, which takes in our people, processes, and products, was extensively audited by BSI against the requirements of the standard, covering all aspects spanning the design of our AI, use of AI within the organization, and our competencies, resources and HR processes. It is an in-depth process that we’re thrilled to have undertaken, making us one of the first in our industry to achieve certification for a globally recognized AI system.

The scope of Darktrace’s certification is particularly wide due to our unique Self-Learning approach to AI for cybersecurity, which uses multi-layered AI systems consisting of varied AI techniques to address distinct cybersecurity tasks. The certification encompasses production and provision of AI systems based on anomaly detection, clustering, classifiers, regressors, neural networks, proprietary and third-party large language models for proactive, detection, response and recovery cybersecurity applications. Darktrace additionally elected to adopt all Annex A controls present in the ISO/IEC 42001 standard.

What are the benefits of an AI Management System?

While AI is not a new or novel concept, the AI industry has accelerated at an unprecedented rate in the past few years, increasing operational efficiency, driving innovation, and automating cumbersome processes in the workplace.

At the same time, the data privacy, security and bias risks created by rapid innovation in AI have been well documented.

Thus, an AI Management System enables organizations to confidently establish and adhere to governance in a way that conforms to best practice, promotes adherence, and is in line with current and emerging regulatory standards.

Not only is this vital in a unique and rapidly evolving field like AI, it additionally helps organization’s balance the drive for innovation with the risks the technology can present, helping to get the best out of their AI development and usage.

What are the key components of ISO/IEC 42001?

The Standard puts an emphasis on responsible AI development and use, requiring organizations to:

  • Establish and implement an AI Management System
  • Commit to the responsible development of AI against established, measurable objectives
  • Have in place a process to manage, monitor and adapt to risks in an effective manner
  • Commit to continuous improvement of their AI Management System

The AI Standard is similar in composition to other ISO standards, such as ISO/IEC 27001:2022, which many organizations may already be familiar with. Further information as to the structure of ISO/IEC 42001 can be found in Annex A.

What it means for Darktrace’s customers

Our certification against ISO/IEC 42001 demonstrates Darktrace’s commitment to delivering industry-leading Self-Learning AI in the name of cybersecurity resilience. Our stakeholders, customers and partners can be confident that Darktrace is responsibly, ethically and securely developing its AI systems, and is managing the use of AI in our day-to-day operations in a compliant, secure and ethical manner. It means:

  • You can trust our AI: We can demonstrate our AI is developed responsibly, in a transparent manner and in accordance with ethical rules. For more information and to learn about Darktrace's responsible AI in cybersecurity approach, please see here.
  • Our products are backed by innovation and integrity: Darktrace drives cutting edge AI innovation with ethical governance and customer trust at its core.
  • You are partnering with an organization which stays ahead of regulatory changes: In an evolving AI landscape, partnering with Darktrace helps you to stay prepared for emerging compliance and regulatory demands in your supply chain.

Achieving ISO/IEC 42001:2023 certification is not just a checkpoint for us. It represents our unwavering commitment to setting a higher standard for AI in cybersecurity. It reaffirms our leadership in building and implementing responsible AI and underscores our mission to continuously innovate and lead the way in the industry.

Why ISO/IEC 42001 matters for every AI vendor you trust

In a market where “AI” can mean anything from a true, production-grade system to a thin marketing layer, ISO/IEC 42001 acts as a critical differentiator. Vendors who have earned this certification aren’t just claiming they build responsible AI, they’ve proven it through an independent, rigorous audit of how they design, deploy, and manage their systems.

For you as a customer, that means:

You know their AI is real: Certified vendors have dedicated, skilled AI teams building and maintaining systems that meet measurable standards, not just repackaging off-the-shelf tools with an “AI” label.

Your data is safeguarded: Compliance with ISO/IEC 42001 includes stringent governance over data use, bias, transparency, and risk management.

You’re partnering with innovators: The certification process encourages continuous improvement, meaning your vendor is actively advancing AI capabilities while keeping ethics and security in focus.

In short, ISO/IEC 42001 is quickly becoming the global badge of credible AI development. If your vendor can’t show it, it’s worth asking how they manage AI risk, whether their governance is mature enough, and how they ensure innovation doesn’t outpace accountability.

Annex A: The Structure of ISO/IEC 42001

ISO/IEC 42001 has requirements for which seven adherence is required for an organization seeking to obtain or maintain its certification:

  • Context of the organization – organizations need to demonstrate an understanding of the internal and external factors influencing the organization’s AI Management System.
  • Leadership – senior leadership teams need to be committed to implementing AI governance within their organizations, providing direction and support across all aspects AI Management System lifecycle.
  • Planning – organizations need to put meaningful and manageable processes in place to identify risks and opportunities related to the AI Management System to achieve responsible AI objectives and mitigate identified risks.
  • Support – demonstrating a commitment to provisioning of adequate resources, information, competencies, awareness and communication for the AI Management System is a must to ensure that proper oversight and management of the system and its risks can be achieved.
  • Operation – establishing processes necessary to support the organization’s AI system development and usage, in conformance with the organization’s AI policy, objectives and requirements of the standard. Correcting the course of any deviations within good time is paramount.
  • Performance evaluation – the organization must be able to demonstrate that it has the capability and willingness to regularly monitor and evaluate the performance of the AI Management System effectively, including actioning any corrections and introducing new processes where relevant.
  • Improvement – relying on an existing process will not be sufficient to ensure compliance with the AI Standard. Organizations must commit to monitoring of existing systems and processes to ensure that the AI Management System is continually enhanced and improved.

To assist organizations in seeking the above, four annexes are included within the AI Standard’s rubric, which outline the objectives and measures an organization may wish to implement to address risks related to the design and operation of their AI Management System through the introduction of normative controls. Whilst they are not prescriptive, Darktrace has implemented the requirements of these Annexes to enable it to appropriately demonstrate the effectiveness of its AI Management System. We have placed a heavy emphasis on Annex A which contains these normative controls which we, and other organizations seeking to achieve certification, can align with to address the objectives and measures, such as:

  • Enforcement of policies related to AI.
  • Setting responsibilities within the organization, and expectation of roles and responsibilities.
  • Creating processes and guidelines for escalating and handling AI concerns.
  • Making resources for AI systems available to users.
  • Assessing impacts of AI systems internally and externally.
  • Implementing processes across the entire AI system life cycle.
  • Understanding treatment of Data for AI systems.
  • Defining what information is, and should be available, for AI systems.
  • Considering and defining use cases for the AI systems.
  • Considering the impact of the AI System on third-party and customer relationships.

The remaining annexes provide guidance on implementing Annex A’s controls, objectives and primary risk sources of AI implementation, and considering how the AI Management System can be used across domains or sectors responsibly.

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August 12, 2025

Minimizing Permissions for Cloud Forensics: A Practical Guide to Tightening Access in the Cloud

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Most cloud environments are over-permissioned and under-prepared for incident response.

Security teams need access to logs, snapshots, and configuration data to understand how an attack unfolded, but giving blanket access opens the door to insider threats, misconfigurations, and lateral movement.

So, how do you enable forensics without compromising your security posture?

The dilemma: balancing access and security

There is a tension between two crucial aspects of cloud security that create a challenge for cloud forensics.

One aspect is the need for Security Operations Center (SOC) and Incident Response (IR) teams to access comprehensive data for investigating and resolving security incidents.

The other conflicting aspect is the principle of least privilege and minimal manual access advocated by cloud security best practices.

This conflict is particularly pronounced in modern cloud environments, where traditional physical access controls no longer apply, and infrastructure-as-code and containerization have transformed the landscape.

There are several common but less-than-ideal approaches to this challenge:

  • Accepting limited data access, potentially leaving incidents unresolved
  • Granting root-level access during major incidents, risking further compromise

Relying on cloud or DevOps teams to retrieve data, causing delays and potential miscommunication

[related-resource]

Challenges in container forensics

Containers present unique challenges for forensic investigations due to their ephemeral and dynamic nature. The orchestration and management of containers, whether on private clusters or using services like AWS Elastic Kubernetes Service (EKS), introduce complexities in capturing and analyzing forensic data.

To effectively investigate containers, it's often necessary to acquire the underlying volume of a node or perform memory captures. However, these actions require specific Identity and Access Management (IAM) and network access to the node, as well as familiarity with the container environment, which may not always be straightforward.

An alternative method of collection in containerized environments is to utilize automated tools to collect this evidence. Since they can detect malicious activity and collect relevant data without needing human input, they can act immediately, securing evidence that might be lost by the time a human analyst is available to collect it manually.

Additionally, automation can help significantly with access and permissions. Instead of analysts needing the correct permissions for the account, service, and node, as well as deep knowledge of the container service itself, for any container from which they wish to collect logs. They can instead collect them, and have them all presented in one place, at the click of a button.

A better approach: practical strategies for cloud forensics

It's crucial to implement strategies that strike a balance between necessary access and stringent security controls.

Here are several key approaches:

1. Dedicated cloud forensics accounts

Establishing a separate cloud account or subscription specifically for forensic activities is foundational. This approach isolates forensic activities from regular operations, preventing potential contamination from compromised environments. Dedicated accounts also enable tighter control over access policies, ensuring that forensic operations do not inadvertently expose sensitive data to unauthorized users.

A separate account allows for:

  • Isolation: The forensic investigation environment is isolated from potentially compromised environments, reducing the risk of cross-contamination.
  • Tighter access controls: Policies and controls can be more strictly enforced in a dedicated account, reducing the likelihood of unauthorized access.
  • Simplified governance: A clear and simplified chain of custody for digital evidence is easier to maintain, ensuring that forensic activities meet legal and regulatory requirements.

For more specifics:

2. Cross-account roles with least privilege

Using cross-account IAM roles, the forensics account can access other accounts, but only with permissions that are strictly necessary for the investigation. This ensures that the principle of least privilege is upheld, reducing the risk of unauthorized access or data exposure during the forensic process.

3. Temporary credentials for just-in-time access

Leveraging temporary credentials, such as AWS STS tokens, allows for just-in-time access during an investigation. These credentials are short-lived and scoped to specific resources, ensuring that access is granted only when absolutely necessary and is automatically revoked after the investigation is completed. This reduces the window of opportunity for potential attackers to exploit elevated permissions.

For AWS, you can use commands such as:

aws sts get-session-token --duration-seconds 43200

aws sts assume-role --role-arn role-to-assume --role-session-name "sts-session-1" --duration-seconds 43200

For Azure, you can use commands such as:

az ad app credential reset --id <appId> --password <sp_password> --end-date 2024-01-01

For more details for Google Cloud environments, see “Create short-lived credentials for a service account” and the request.time parameter.

4. Tag-based access control

Pre-deploying access control based on resource tags is another effective strategy. By tagging resources with identifiers like "Forensics," access can be dynamically granted only to those resources that are relevant to the investigation. This targeted approach minimizes the risk of overexposure and ensures that forensic teams can quickly and efficiently access the data they need.

For example, in AWS:

Condition: StringLike: aws:ResourceTag/Name: ForensicsEnabled

Condition: StringLike: ssm:resourceTag/SSMEnabled: True

For example, in Azure:

"Condition": "StringLike(Resource[Microsoft.Resources/tags.example_key], '*')"

For example, in Google Cloud:

expression: > resource.matchTag('tagKeys/ForensicsEnabled', '*')

Tighten access, enhance security

The shift to cloud environments demands a rethinking of how we approach forensic investigations. By implementing strategies like dedicated cloud forensic accounts, cross-account roles, temporary credentials, and tag-based access control, organizations can strike the right balance between access and security. These practices not only enhance the effectiveness of forensic investigations but also ensure that access is tightly controlled, reducing the risk of exacerbating an incident or compromising the investigation.

Find the right tools for your cloud security

Darktrace delivers a proactive approach to cyber resilience in a single cybersecurity platform, including cloud coverage.

Darktrace’s cloud offerings have been bolstered with the acquisition of Cado Security Ltd., which enables security teams to gain immediate access to forensic-level data in multi-cloud, container, serverless, SaaS, and on-premises environments.

In addition to having these forensics capabilities, Darktrace / CLOUD is a real-time Cloud Detection and Response (CDR) solution built with advanced AI to make cloud security accessible to all security teams and SOCs. By using multiple machine learning techniques, Darktrace brings unprecedented visibility, threat detection, investigation, and incident response to hybrid and multi-cloud environments.

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