NIST GenAI Profile
Cross-sectoral companion profile to NIST AI RMF focused on risks and risk-management actions specific to generative AI.
Cross-sectoral companion profile to NIST AI RMF focused on risks and risk-management actions specific to generative AI.
Developers, deployers and users managing generative AI risks throughout the lifecycle.
Voluntary reference framework.
Cross-sectoral companion profile to NIST AI RMF focused on risks and risk-management actions specific to generative AI.
Assess provenance, content integrity and misuse controls where generated content can cause material harm.
Actor: all · Domain: transparency
Evidence: Provenance controls, watermark/label assessment and abuse monitoring.
Evaluate relevant generative-AI risks with methods suited to the use context, including capability and failure testing.
Actor: all · Domain: evaluation
Evidence: Evaluation suite, results, limitations and remediation tracking.
Assess prompt injection, data leakage, misuse, model/agent access and other relevant security risks.
Actor: all · Domain: security
Evidence: Threat model, red-team evidence, security test results and fixes.
Cybatar's mapping is designed for AI governance and assurance work. Legal interpretation remains anchored to the current primary text and competent authority guidance.
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