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October 30, 2024

Post-Exploitation Activities on Fortinet Devices: A Network-Based Analysis

This blog explores recent findings from Darktrace's Threat Research team on active exploitation campaigns targeting Fortinet appliances. This analysis focuses on the September 2024 exploitation of FortiManager via CVE-2024-47575, alongside related malicious activity observed in June 2024.
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
Adam Potter
Senior Cyber Analyst
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30
Oct 2024

Introduction: Uncovering active exploitation of Fortinet vulnerabilities

As part of the Darktrace Threat Research team's routine analysis of October's Patch Tuesday vulnerabilities, the team began searching for signs of active exploitation of a critical vulnerability (CVE-2024-23113) affecting the FortiGate to FortiManager (FGFM) protocol.[1]

Although the investigation was prompted by an update regarding CVE 2024-23113, results of the inquiry yielded evidence of widespread exploitation of Fortinet devices in both June and September 2024 potentially via multiple vulnerabilities including CVE 2024-47575. Analysts identified two clusters of activity involving overlapping indicators of compromise (IoCs), likely constituting unique campaigns targeting Fortinet appliances.

This blog will first highlight the finding and analysis of the network-based indicators of FortiManager post-exploitation activity in September, likely involving CVE 2024-47575. The article will then briefly detail a similar pattern of malicious activity observed in June 2024 that involved similar IoCs that potentially comprises a distinct campaign targeting Fortinet perimeter devices.

Fortinet CVE Disclosures

FortiManager devices allow network administrators to manage Fortinet devices on organizations’ networks.[2] One such subset of devices managed through this method are Fortinet firewalls known as FortiGate. These manager and firewall devices communicate with each other via a custom protocol known as FortiGate to FortiManager (FGFM), whereby devices can perform reachability tests and configuration-related actions and reporting.[3] By default, FortiManager devices operate this protocol via port 541.[4]

Fortinet Product Security Incident Response Team released multiple announcements revealing vulnerabilities within the daemon responsible for implementing operability of the FGFM service. Specifically, CVE 2024-23113 enables attackers to potentially perform arbitrary remote command execution through the use of a specially crafted format string to a FortiGate device running the “fgfm daemon”.[5][6]  Similarly, the exploitation of CVE 2024-47575  could also allow remote command execution due to a missing authentication mechanism when targeting specifically FortiManager devices.[7][8]  Given how prolific both FortiGate and FortiManager devices are within the global IT security ecosystem, Darktrace analysts hypothesized that there may have been specific targeting of such devices within the customer base using these vulnerabilities throughout mid to late 2024.

Campaign Analysis

In light of these vulnerability disclosures, Darktrace’s Threat Research team began searching for signs of active exploitation by investigating file download, lateral movement or tooling activity from devices that had previously received suspicious connections on port 541. The team first noticed increases in suspicious activity involving Fortinet devices particularly in mid-September 2024. Further analysis revealed a similar series of activities involving some overlapping devices identified in June 2024. Analysis of these activity clusters revealed a pattern of malicious activity against likely FortiManager devices, including initial exploitation, payload retrieval, and exfiltration of probable configuration data.

Below is an overview of malicious activity we have observed by sector and region:

Sector and region affected by malicious activity on fortigate devices
The sectors of affected customers listed above are categorized according to the United Kingdom’s Standard Industrial Classification (SIC).

Initial Exploitation of FortiManager Devices

Across many of the observed cases in September, activity began with the initial exploitation of FortiManager devices via incoming connectivity over TLS/SSL. Such activity was detected due to the rarity of the receiving devices accepting connections from external sources, particularly over destination port 541. Within nearly all investigated incidents, connectivity began with the source IP, 45.32.41[.]202, establishing an SSL session with likely FortiManager devices.  Device types were determined through a combination of the devices’ hostnames and the noted TLS certificate issuer for such encrypted connections.

Due to the encrypted nature of the connection, it was not possible to ascertain the exploit used in the analyzed cases. However, given the similarity of activities targeting FortiManager devices and research conducted by outside firms, attackers likely utilized CVE 2024-47575.[9] For example, the source IP initiating the SSL sessions also has been referenced by Mandiant as engaging in CVE 2024-47575 exploitation. In addition to a consistent source IP for the connections, a similar JA3 hash was noted across multiple examined accounts, suggesting a similarity in source process for the activity.

In most cases observed by Darktrace, the incoming connectivity was followed by an outgoing connection on port 443 to the IP 45.32.41[.]202. Uncommon reception of encrypted connections over port 541, followed by the initiation of outgoing SSL connections to the same endpoint would suggest probable successful exploitation of FortiManager CVEs during this time.

Model alert logs highlighting the incoming connectivity over port 541 to the FortiManager devices followed by outgoing connection to the external IP.
Figure 1: Model alert logs highlighting the incoming connectivity over port 541 to the FortiManager devices followed by outgoing connection to the external IP.

Payload Retrieval

Investigated devices commonly retrieved some form of additional content after incoming connectivity over port 541. Darktrace’s Threat Research team noted how affected devices would make HTTP GET requests to the initial exploitation IP for the URI: /dom.js. This URI, suggestive of JavaScript content retrieval, was then validated by the HTTP response content type. Although Darktrace could see the HTTP content of the connections, usage of destination port 443 featured prominently during these HTTP requests, suggesting an attempt at encryption of the session payload details.

Figure 2: Advanced Search HTTP log to the exploitation IP noting the retrieval of JavaScript content using the curl user agent.

Cyber AI Analyst investigation into the initial exploitation activity. This incident emphasizes the rare external connectivity over port 443 requesting JavaScript content following the incoming connections over port 541.
Figure 3: Cyber AI Analyst investigation into the initial exploitation activity. This incident emphasizes the rare external connectivity over port 443 requesting JavaScript content following the incoming connections over port 541.

The operators of the campaign also appear to have used a consistent user agent for payload retrieval: curl 8.4.0. Usage of an earlier version of the curl (version 7 .86.0) was only observed in one instance. The incorporation of curl utility to establish HTTP connections therefore suggests interaction with command-line utilities on the inspected Fortinet hosts. Command-line interaction also adds validity to the usage of exploits such as CVE 2024-47575 which enable unauthenticated remote command execution. Moreover, given the egress of data seen by the devices receiving this JavaScript content, Darktrace analysts concluded that this payload likely resulted in the configuration aggregation activity noted by external researchers.

Data Exfiltration

Nearly all devices investigated during the September time period performed some form of data exfiltration using the HTTP protocol. Most frequently, devices would initiate these HTTP requests using the same curl user agent already observed during web callback activity.  Again, usage of this tool heavily suggests interaction with the command-line interface and therefore command execution.

The affected device typically made an HTTP POST request to one or both of the following two rare external IPs: 104.238.141[.]143 and 158.247.199[.]37. One of the noted IPs, 104.238.141[.]143, features prominently within external research conducted by Mandiant during this time. These HTTP POST requests nearly always sent data to the /file endpoint on the destination IPs. Analyzed connections frequently noted an HTTP mime type suggestive of compressed archive content. Some investigations also revealed specific filenames for the data sent externally: “.tm”. HTTP POST requests occurred without a specified hostname. This would suggest the IP address may have already been cached locally on the device from a running process or the IP address was hardcoded into the details of unwarranted code running on the system. Moreover, many such POSTs occurred without a GET request, which can indicate exfiltration activity.

Model alert logs noting both the connection to the IP 158.247.199[.]37 over port 443 without a hostname, and the unusual activity metric describing how the request was made without a prior HTTP GET request. Such activity can indicate malicious data exfiltration.
Figure 4: Model alert logs noting both the connection to the IP 158.247.199[.]37 over port 443 without a hostname, and the unusual activity metric describing how the request was made without a prior HTTP GET request. Such activity can indicate malicious data exfiltration.

Interestingly, in many investigations, analysts noticed a lag period between the initial access and exploitation, and the exfiltration of data via HTTP. Such a pause, sometimes over several hours to over a day, could reflect the time needed to aggregate data locally on the host or as a strategic pause in activity to avoid detection. While not present within every compromise activity logs inspected, the delay could represent slight adjustments in behavior during the campaign by the threat actor.

Figure 5: Advanced search logs showing both the payload retrieval and exfiltration activity, emphasizing the gap in time between payload retrieval and exfiltration via HTTP POST request.

HTTP and file identification details identified during this time also directly correspond to research conducted by Mandiant. Not only do we see overlap in IPs identified as receiving the posted data (104.238.141[.]143) we also directly observed an overlap in filenames for the locally aggregated configuration data. Moreover, the gzip mime type identified in multiple customer investigations also corresponds directly to exfiltration activity noted by Mandiant researchers.

Advanced search logs noting the filename and URL of the posted data to one of the exfiltration IPs. The .tm filename corresponds to the locally stored file on affected FortiManager devices analyzed by external researchers.
Figure 6: Advanced search logs noting the filename and URL of the posted data to one of the exfiltration IPs. The .tm filename corresponds to the locally stored file on affected FortiManager devices analyzed by external researchers.

Activity detected in June 2024

Common indicators

Analysts identified a similar pattern of activity between June 23 and June 25. Activity in this period involved incoming connections from the aforementioned IP 45.32.41[.]202 on either port 541 or port 443 followed by an outgoing connection to the source. This behavior was then followed by HTTP POSTs to the previously mentioned IP address 158.247.199[.]37 in addition to the novel IP: 195.85.114[.]78  using same URI ‘/file’ noted above. Given the commonalties in indicators, time period, and observed behaviors, this grouping of exploitation attempts appears to align closely with the campaign described by Mandiant and may represent exploitation of CVE 2024-47575 in June 2024. The customers targeted in June fall into the same regions and sectors as seen those in the September campaign.

Deviations in behavior

Notably, Darktrace detected a different set of actions during the same June timeframe despite featuring the same infrastructure. This activity involved an initial incoming connection from 158.247.199[.]37 to an internal device on either port 541 or port 443. This was then followed by an outgoing HTTP connection to 158.247.199[.]37 on port 443 with a URI containing varying external IPs. Upon further review, analysts noticed the IPs listed may be the public IPs of the targeted victim, suggesting a potential form device registration by the threat actor or exploit validation. While the time period and infrastructure closely align with the previous campaign described, the difference in activity may suggest another threat actor sharing infrastructure or the same threat actor carrying out a different campaign at the same time. Although the IP 45.32.41[.]202 was contacted, paralleling activity seen in September, analysts did notice a different payload received from the external host, a shell script with the filename ver.sh.

Figure 7: AI Analyst timeline noting the suspicious HTTP behavior from a FortiManager device involving the IP 158.247.199[.] 37.

Darktrace's depth of detection and investigation

Darktrace detected spikes in anomalous behavior from Fortinet devices within the customer base between September 22 and 23, 2024. Following an in-depth investigation into affected accounts and hosts, Darktrace identified a clear pattern where one, or multiple, threat actors leveraged CVEs affecting likely FortiManager devices to execute commands on the host, retrieve malicious content, and exfiltrate sensitive data. During this investigation, analysts then identified possibly related activity in June 2024 highlighted above.

The gathering and exfiltration of configuration data from network security management or other perimeter hosts is a technique that can enable future access by threat actors. This parallels activity previously discussed by Darktrace focused on externally facing devices, such as Palo Alto Networks firewall devices.  Malicious entities could utilize stolen configuration data and potentially stored passwords/hashes to gain initial access in the future, irrespective of the state of device patching. This data can also be potentially sold by initial access brokers on illicit sites. Moreover, groups can leverage this information to establish persistence mechanisms within devices and host networks to enable more impactful compromise activity.

Uncover threat pattens before they strike your network

Network and endpoint management services are essential tools for network administrators and will remain a critical part of IT infrastructure. However, these devices are often configured as internet-facing systems, which can unintentionally expose organizations networks' to attacks. Internet exposure provides malicious groups with novel entry routes into target environments. Although threat actors can swap vulnerabilities to access target networks, the exploitation process leaves behind unusual traffic patterns, making their presence detectable with the right network detection tools.

By detecting the unusual patterns of network traffic which inevitably ensue from exploitation of novel vulnerabilities, Darktrace’s anomaly-based detection and response approach can continue to identify and inhibit such intrusion activities irrespective of exploit used. Eulogizing the principle of least privilege, configuration and asset management, and maintaining the CIA Triad across security operations will continue to help security teams boost their defense posture.

See how anomaly-based detection can enhance your security operations—schedule a personalized demo today.

Get a demo button for Darktrace

Credit to Adam Potter (Senior Cyber Analyst), Emma Foulger (Principal Cyber Analyst), Nahisha Nobregas (Senior Cyber Analyst), Hyeongyung Yeom (Principal Cyber Analyst & Analyst Team Lead, East Asia), Sam Lister (Senior Cyber Analyst)

Appendix

Model Alerts

  • Anomalous Connection / Posting HTTP to IP without Hostname
  • Anomalous Connection / Callback on Web Facing Device
  • Anomalous Server Activity / New Internet Facing Server
  • Anomalous Server Activity / Outgoing from Server

Cyber AI Analyst Incidents

  • Possible HTTP Command and Control
  • Possible HTTP Command and Control to Multiple Endpoints

IoCs

Indicator – Type - Description

104.238.141[.]143 -  IP Address  - C2 infrastructure

158.247.199[.]37 - IP Address - C2 infrastructure

45.32.41[.]202 - IP Address - C2 infrastructure

104.238.141[.]143/file – URL - C2 infrastructure

158.247.199[.]37/file  - URL - C2 infrastructure

45.32.41[.]202/dom.js – URL - C2 infrastructure

.tm – Filename - Gzip file

MITRE Attack Framework

  • Initial Access
    T1190 Exploiting Public-Facing Application
  • Execution:
    T1059 Command and Scripting Interpreter  (Sub-Techniques: T1059.004 Unix Shell, T1059.008 Network Device CLI)
  • Discovery:
    T1083 File and System Discovery
    T1057 Process Discovery
  • Collection:
    T1005 Data From Local System
  • Command and Control:
    T1071 Application Layer Protocols (Sub-Technique:
    T1071.001 Web Protocols)
    T1573  Encrypted Channel
    T1573.001  Symmetric Cryptography
    T1571 Non-Standard Port
    T1105 Ingress Tool Transfer
    T1572 Protocol Tunnelling 
  • Exfiltration:
    T1048.003 Exfiltration Over Unencrypted Non-C2 Protocol

References

{1} https://cloud.google.com/blog/topics/threat-intelligence/fortimanager-zero-day-exploitation-cve-2024-47575/

{2} https://docs.fortinet.com/document/fortimanager/6.4.0/ports-and-protocols/606094/fortigate-fortimanager-protocol#:~:text=The%20FortiGate%2DFortiManager%20(FGFM),by%20using%20the%20FGFM%20protocol.

{3)https://docs.fortinet.com/document/fortigate/6.4.0/ports-and-protocols/373486/fgfm-fortigate-to-fortimanager-protocol
{4} https://www.fortiguard.com/psirt/FG-IR-24-029
{5} https://www.fortiguard.com/psirt/FG-IR-24-423
{6}https://www.fortinet.com/content/dam/fortinet/assets/data-sheets/fortimanager.pdf

{7} https://doublepulsar.com/burning-zero-days-fortijump-fortimanager-vulnerability-used-by-nation-state-in-espionage-via-msps-c79abec59773

{8} https://darktrace.com/blog/post-exploitation-activities-on-pan-os-devices-a-network-based-analysis

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
Adam Potter
Senior 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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