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Lornets

Evidence note

NIST AI 600-1: Generative Artificial Intelligence Profile

Government Guidance2024National Institute of Standards and Technology

What does it cover?

A Generative AI profile extending the NIST AI Risk Management Framework with risks and actions particularly relevant to generative AI systems.

Key points

  1. 01The profile addresses risks including confabulation, data privacy, information integrity, information security and component integration.
  2. 02It recommends evaluating system performance under conditions similar to deployment.
  3. 03It recommends reassessing risk when systems are adapted to materially new domains or contexts.
  4. 04It emphasises ongoing testing, monitoring, security evaluation and incident management.

Why it matters. Lornets interpretation.

Generic model benchmarks are insufficient evidence for a production AI application. Assurance needs to consider the actual deployment context, integrations, monitoring and change over time.

This is the Lornets reading of the source, not a finding of the source itself.

What it does not establish

  1. 01The profile does not certify individual applications.
  2. 02It is risk-management guidance rather than a guarantee of safe system behaviour.
  3. 03Applicable depth should remain proportionate to context.

Source

Organisation
National Institute of Standards and Technology
Evidence type
Government Guidance
Published
2024-07
Status
Current

View official guidance

Relevant Lornets framework areas

Framework domains

  • AI Assurance
  • Security & Access Control
  • Reliability & Recoverability
  • Data & Privacy Engineering
  • Observability & Operations

Related evidence

Government Guidance

2022

NIST Secure Software Development Framework v1.1

National Institute of Standards and Technology, SP 800-218, SSDF v1.1

SSDF organises secure-development practices into a structured set of outcomes rather than prescribing one development methodology.

  • Security & Supply Chain
  • Software Quality & Maintainability

Current, revision underway

Read Evidence Note

Source record

Published
2024-07
Last verified
2026-08-11
Source status
Current