Law / Frameworks / Crosswalk / OWASP LLM Top 10 to NIST AI RMF

The OWASP Top 10 for LLM Applications, mapped to the NIST AI Risk Management Framework

5 of OWASP LLM Top 10's controls connect to 18 of NIST AI RMF's through 224 laws in 125 jurisdictions. Two controls connect when the same duties, in at least 2 laws we track, reach both. The connections are our own reading of the law; no framework publisher has reviewed or endorsed them.

From
OWASP Top 10 for LLM Applications, 2026 edition, August 2026, OWASP GenAI Security Project
To
NIST AI Risk Management Framework, version 1.0, January 2023 (NIST AI 100-1), National Institute of Standards and Technology
See also
NIST AI RMF to OWASP LLM Top 10, the other way · every pair in the crosswalk · law library as of

Download this mapping, with every law behind each connection: nist-ai-rmf--owasp-llm-top-10.csv · nist-ai-rmf--owasp-llm-top-10.json

OWASP LLM Top 10NIST AI RMFLawsJurisdictionsWhere the laws stand
LLM01:2026Prompt Injection MEASURE 2.6The AI system is evaluated regularly for safety risks – as identified in the MAP... 3 2 2 in force, 1 not yet in force
The 3 laws behind LLM01:2026 and MEASURE 2.6
MEASURE 2.5The AI system to be deployed is demonstrated to be valid and reliable. Limitations of... 2 1 1 in force, 1 not yet in force
The 2 laws behind LLM01:2026 and MEASURE 2.5
MEASURE 2.7AI system security and resilience – as identified in the MAP function – are evaluated... 2 1 1 in force, 1 not yet in force
The 2 laws behind LLM01:2026 and MEASURE 2.7
LLM02:2026Sensitive Information Disclosure MEASURE 2.6The AI system is evaluated regularly for safety risks – as identified in the MAP... 3 2 2 in force, 1 not yet in force
The 3 laws behind LLM02:2026 and MEASURE 2.6
MEASURE 2.5The AI system to be deployed is demonstrated to be valid and reliable. Limitations of... 2 1 1 in force, 1 not yet in force
The 2 laws behind LLM02:2026 and MEASURE 2.5
MEASURE 2.7AI system security and resilience – as identified in the MAP function – are evaluated... 2 1 1 in force, 1 not yet in force
The 2 laws behind LLM02:2026 and MEASURE 2.7
LLM03:2026Excessive Agency MAP 4.1Approaches for mapping AI technology and legal risks of its components – including the... 146 107 143 in force, 3 not yet in force
The 146 laws behind LLM03:2026 and MAP 4.1

and 136 more, every one in the free file.

GOVERN 1.1Legal and regulatory requirements involving AI are understood, managed, and documented. 38 20 28 in force, 9 not yet in force, 1 proposed
The 38 laws behind LLM03:2026 and GOVERN 1.1

and 28 more, every one in the free file.

MAP 3.5Processes for human oversight are defined, assessed, and documented in accordance with... 25 18 17 in force, 8 not yet in force
The 25 laws behind LLM03:2026 and MAP 3.5

and 15 more, every one in the free file.

MEASURE 2.4The functionality and behavior of the AI system and its components – as identified in... 22 11 12 in force, 10 not yet in force
The 22 laws behind LLM03:2026 and MEASURE 2.4

and 12 more, every one in the free file.

GOVERN 1.4The risk management process and its outcomes are established through transparent... 17 12 11 in force, 6 not yet in force
The 17 laws behind LLM03:2026 and GOVERN 1.4

and 7 more, every one in the free file.

MAP 2.3Scientific integrity and TEVV considerations are identified and documented, including... 12 9 8 in force, 4 not yet in force
The 12 laws behind LLM03:2026 and MAP 2.3

and 2 more, every one in the free file.

GOVERN 1.6Mechanisms are in place to inventory AI systems and are resourced according to... 7 6 6 in force, 1 not yet in force
The 7 laws behind LLM03:2026 and GOVERN 1.6
GOVERN 2.1Roles and responsibilities and lines of communication related to mapping, measuring,... 7 6 7 in force
The 7 laws behind LLM03:2026 and GOVERN 2.1
MEASURE 2.11Fairness and bias – as identified in the MAP function – are evaluated and results are... 6 5 4 in force, 2 not yet in force
The 6 laws behind LLM03:2026 and MEASURE 2.11
GOVERN 2.3Executive leadership of the organization takes responsibility for decisions about... 4 4 4 in force
The 4 laws behind LLM03:2026 and GOVERN 2.3
MEASURE 2.9The AI model is explained, validated, and documented, and AI system output is... 4 4 4 in force
The 4 laws behind LLM03:2026 and MEASURE 2.9
MANAGE 2.4Mechanisms are in place and applied, and responsibilities are assigned and understood,... 4 3 4 in force
The 4 laws behind LLM03:2026 and MANAGE 2.4
MAP 5.1Likelihood and magnitude of each identified impact (both potentially beneficial and... 3 3 3 in force
The 3 laws behind LLM03:2026 and MAP 5.1
MAP 3.3Targeted application scope is specified and documented based on the system’s... 3 2 3 in force
The 3 laws behind LLM03:2026 and MAP 3.3
MEASURE 2.7AI system security and resilience – as identified in the MAP function – are evaluated... 2 2 1 in force, 1 not yet in force
The 2 laws behind LLM03:2026 and MEASURE 2.7
MEASURE 3.3Feedback processes for end users and impacted communities to report problems and... 2 2 2 in force
The 2 laws behind LLM03:2026 and MEASURE 3.3
LLM04:2026Supply Chain MEASURE 2.6The AI system is evaluated regularly for safety risks – as identified in the MAP... 3 2 2 in force, 1 not yet in force
The 3 laws behind LLM04:2026 and MEASURE 2.6
MEASURE 2.5The AI system to be deployed is demonstrated to be valid and reliable. Limitations of... 2 1 1 in force, 1 not yet in force
The 2 laws behind LLM04:2026 and MEASURE 2.5
MEASURE 2.7AI system security and resilience – as identified in the MAP function – are evaluated... 2 1 1 in force, 1 not yet in force
The 2 laws behind LLM04:2026 and MEASURE 2.7
LLM05:2026Data and Model Poisoning MEASURE 2.6The AI system is evaluated regularly for safety risks – as identified in the MAP... 3 2 2 in force, 1 not yet in force
The 3 laws behind LLM05:2026 and MEASURE 2.6
MEASURE 2.5The AI system to be deployed is demonstrated to be valid and reliable. Limitations of... 2 1 1 in force, 1 not yet in force
The 2 laws behind LLM05:2026 and MEASURE 2.5
MEASURE 2.7AI system security and resilience – as identified in the MAP function – are evaluated... 2 1 1 in force, 1 not yet in force
The 2 laws behind LLM05:2026 and MEASURE 2.7
Not connected to the NIST AI RMF: 5 of OWASP LLM Top 10's controls

No law we track reaches these

No duty in the laws we track reaches these controls.

How these connections are drawn

Each requirement line in the laws we track is read against the framework for its subject (the AI, scraping and news aggregation laws against the NIST AI RMF, the privacy, communications and age assurance laws against the NIST Privacy Framework, the cybersecurity laws against the NIST CSF 2.0); laws on liability and content moderation are not read against any framework yet. A line reaches the OWASP LLM Top 10 through a kind of duty its law carries, and only where that kind of duty also reaches, on that same line, the NIST framework for the line's own subject. Two controls connect when lines in at least 2 laws reach both. That says the same duties reach both; it does not say the two are alike, or that running either one does what a law asks.

Every duty line in the AI, scraping and news aggregation laws we track has been read against the framework for its subject.

Sources and licenses

OWASP GenAI Security Project, OWASP Top 10 for LLM Applications 2026, licensed CC BY-SA 4.0. Excerpted: only the first paragraph of each entry's Description is reproduced, verbatim.