NIST opens an agentic adversarial-ML taxonomy for comment
NIST released draft SP 2400-102e2026, a taxonomy of adversarial-machine-learning attacks and mitigations focused on agentic systems. It organizes attack life-cycle stages, goals, capabilities and attacker knowledge, with an agentic attack index for fine-grained references.
Why it matters: A shared vocabulary can make threat models, test plans and incident records comparable across teams. Because the document is a public draft, practitioners can also shape terminology before later standards and practice guides build on it.