MITRE ATLAS is now an agent security framework

MITRE ATLAS is a monthly updated, ATT&CK-style knowledge base for threats against AI systems that, in version 2026.09, includes 16 tactics, 120 techniques, 88 sub-techniques, 40 mitigations, and 73 case studies. Originally focused on machine-learning risks such as adversarial examples, training-data poisoning, model inversion, and model extraction, it now places substantial emphasis on agentic AI, with 139 of 208 technique entries tagged for agents and 57 of those classified as realized in real incidents. The article distinguishes ATLAS from MITRE ATT&CK by explaining that ATLAS addresses attacks that exploit AI systems through prompts, data, tools, and model interfaces rather than conventional compromises of hosts or networks, while the two frameworks can describe different stages of the same intrusion. It highlights prompt injection, context and retrieval poisoning, malicious agent tools and supply-chain rug pulls, and inference-based data or model theft as key enterprise concerns, using reported cases involving a compromised MCP email tool and misuse of a coding agent. ATLAS is presented as a threat-modeling and detection reference rather than a compliance framework or complete defensive architecture, with the article arguing that practical controls should focus on agent-to-tool boundaries through permission scoping, tool validation, curated registries, credential management, human approvals, monitoring, and audit logging.

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