Source URL: https://www.microsoft.com/en-us/security/blog/2025/04/24/new-whitepaper-outlines-the-taxonomy-of-failure-modes-in-ai-agents/
Source: Microsoft Security Blog
Title: New whitepaper outlines the taxonomy of failure modes in AI agents
Feedly Summary: Read the new whitepaper from the Microsoft AI Red Team to better understand the taxonomy of failure mode in agentic AI.
The post New whitepaper outlines the taxonomy of failure modes in AI agents appeared first on Microsoft Security Blog.
AI Summary and Description: Yes
**Summary:** The text discusses Microsoft’s release of a new whitepaper that outlines a taxonomy of failure modes in AI agents, which is designed to help security professionals and machine learning engineers understand and mitigate potential risks associated with AI systems. This effort is a continuation of Microsoft’s commitment to improving safety and security in AI through the identification of unique and existing failure modes in agentic AI systems.
**Detailed Description:**
Microsoft’s new whitepaper detailing the taxonomy of failure modes in agentic AI systems serves as a crucial resource for professionals in AI security, helping them to think systematically about how these systems can fail.
Key points in the text include:
– **Background and Context:**
– The taxonomy builds on previous works of the Microsoft AI Red Team, which documented traditional AI system failure modes.
– Key collaborative efforts include partnerships with MITRE and various organizations to develop an Adversarial ML Threat Matrix, now evolved into MITRE ATLAS™.
– **Three-Prong Approach to Development:**
– Internal red teaming of Microsoft’s agent-based AI systems.
– Collaboration with internal stakeholders across Microsoft to refine the taxonomy.
– Interviews with external practitioners to ensure the taxonomy addresses real-world challenges.
– **Focus on Real-World Applications:**
– The whitepaper provides a case study illustrating how a cyber attacker could exploit an agent’s memory—demonstrating the practical implications of security failures.
– **Failure Modes Classification:**
– Two major categories are identified:
– **Security Failures:** Impact confidentiality, availability, or integrity (e.g., modifying the AI’s intent).
– **Safety Failures:** Affect responsible AI implementation and can harm users or society (e.g., biased service delivery).
– **Mapping Failures:**
– Novel failure modes are unique to agentic AI systems.
– Existing failure modes are familiar but are more significant in the context of agentic AI.
– **Mitigation Strategies and Controls:**
– Strategies against memory poisoning, including:
– External authentication for memory updates.
– Restricting access to memory components.
– Defining structured formats for memory storage.
– **Guidance for Various Stakeholders:**
– **Engineers:** Use the taxonomy for designing agents and enhancing security development practices.
– **Security Professionals:** Use it to assess and probe AI systems before launch, informing defensive strategies.
– **Governance Professionals:** Gain insight into both novel and traditional failure modes prevalent in agentic AI.
– **Future Updates:**
– The taxonomy is positioned as a living document, with the expectation of revisions as technology and threats evolve.
This whitepaper is particularly relevant for engineers, security professionals, and risk governance teams as it provides a systematic approach to identifying and mitigating risks in AI systems, reinforcing the importance of safety and security in the development of such technologies.