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Home/Standards & Frameworks/NIST AI 100-2 E2025 — Adversarial Machine Learning: A Taxonomy and Terminology of Attacks and Mitigations

NIST AI 100-2 E2025 — Adversarial Machine Learning: A Taxonomy and Terminology of Attacks and Mitigations

Trustworthy and Responsible AI report on adversarial machine learning attacks and mitigations, 2025 edition

The reference taxonomy of attacks on predictive and generative AI (evasion, poisoning, privacy, misuse, prompt injection, agent hijacking) and their mitigations, with a shared vocabulary used by MITRE ATLAS, OWASP and the EU standards work. The 2025 edition added generative and agentic attacks.

adversarial machine learningtaxonomyattacksmitigations

Sources

doi.orghttps://doi.org/10.6028/NIST.AI.100-2e2025

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