The NIST AI Risk Management Framework is a voluntary guide for identifying, assessing, and managing risks from AI systems. It helps organizations think beyond model accuracy and examine the full AI stack: training data, access controls, logging, deployment security, monitoring, and governance.
In cyber security, the framework matters because AI can fail in ways that create real exposure, such as data leakage, poisoned training inputs, unsafe integrations, or weak post-deployment oversight. Defenders use it to build controls, document decisions, and prove that AI systems are tested and monitored. Attackers may target the same weak points, including data pipelines, model interfaces, and operational gaps. Even though it is voluntary, the framework often influences procurement, audits, and vendor requirements, turning guidance into a practical security baseline.