Law / Frameworks / Crosswalk / ETSI EN 304 223 to NIST AI RMF

The ETSI EN 304 223, Baseline Cyber Security Requirements for AI Models and Systems, mapped to the NIST AI Risk Management Framework

19 of ETSI EN 304 223's provisions connect to 28 of NIST AI RMF's through 435 laws in 165 jurisdictions. Two provisions 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
ETSI EN 304 223, Baseline Cyber Security Requirements for AI Models and Systems, version 2.1.1, December 2025, European Telecommunications Standards Institute (ETSI)
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 ETSI EN 304 223, the other way · every pair in the crosswalk · law library as of

Download this mapping, with every law behind each connection: nist-ai-rmf--etsi-en-304-223.csv · nist-ai-rmf--etsi-en-304-223.json

ETSI EN 304 223NIST AI RMFLawsJurisdictionsWhere the laws stand
5.1.2-1Business need and security risks written down and assessed before deciding to build an... MAP 3.3Targeted application scope is specified and documented based on the system’s... 143 86 124 in force, 15 not yet in force, 1 blocked by a court, 3 proposed
The 143 laws behind 5.1.2-1 and MAP 3.3

and 133 more, every one in the free file.

MAP 5.1Likelihood and magnitude of each identified impact (both potentially beneficial and... 9 8 3 in force, 1 not yet in force, 5 proposed
The 9 laws behind 5.1.2-1 and MAP 5.1
MANAGE 1.3Responses to the AI risks deemed high priority, as identified by the MAP function, are... 6 6 1 in force, 5 proposed
The 6 laws behind 5.1.2-1 and MANAGE 1.3
MEASURE 2.10Privacy risk of the AI system – as identified in the MAP function – is examined and documented. 4 4 3 in force, 1 not yet in force
The 4 laws behind 5.1.2-1 and MEASURE 2.10
5.1.2-2System built to hold up against adversarial attacks, unexpected inputs and failures. 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 5.1.2-2 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 5.1.2-2 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 5.1.2-2 and MEASURE 2.7
5.1.2-6Access the AI system gets to other systems and data sources is minimal and risk assessed. MAP 4.1Approaches for mapping AI technology and legal risks of its components – including the... 145 107 142 in force, 3 not yet in force
The 145 laws behind 5.1.2-6 and MAP 4.1

and 135 more, every one in the free file.

5.1.2-7Due diligence on external providers, including whether they follow this standard. GOVERN 6.1Policies and procedures are in place that address AI risks associated with third-party... 2 2 1 in force, 1 not yet in force
The 2 laws behind 5.1.2-7 and GOVERN 6.1
5.1.3-1Threat modelling and risk management, reviewed regularly and covering AI-specific attacks. MAP 5.1Likelihood and magnitude of each identified impact (both potentially beneficial and... 9 8 3 in force, 1 not yet in force, 5 proposed
The 9 laws behind 5.1.3-1 and MAP 5.1
MANAGE 1.3Responses to the AI risks deemed high priority, as identified by the MAP function, are... 5 5 5 proposed
The 5 laws behind 5.1.3-1 and MANAGE 1.3
MEASURE 2.10Privacy risk of the AI system – as identified in the MAP function – is examined and documented. 4 4 3 in force, 1 not yet in force
The 4 laws behind 5.1.3-1 and MEASURE 2.10
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 5.1.3-1 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 5.1.3-1 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 5.1.3-1 and MEASURE 2.7
5.1.3-2Threats developers cannot resolve are passed to operators and on to end-users. MEASURE 2.8Risks associated with transparency and accountability – as identified in the MAP... 64 43 40 in force, 12 not yet in force, 12 proposed
The 64 laws behind 5.1.3-2 and MEASURE 2.8

and 54 more, every one in the free file.

MEASURE 3.3Feedback processes for end users and impacted communities to report problems and... 9 9 2 in force, 1 not yet in force, 6 proposed
The 9 laws behind 5.1.3-2 and MEASURE 3.3
GOVERN 4.2Organizational teams document the risks and potential impacts of the AI technology... 8 6 4 in force, 3 not yet in force, 1 proposed
The 8 laws behind 5.1.3-2 and GOVERN 4.2
MAP 2.2Information about the AI system’s knowledge limits and how system output may be... 4 3 1 in force, 3 not yet in force
The 4 laws behind 5.1.3-2 and MAP 2.2
MAP 1.6System requirements (e.g., “the system shall respect the privacy of its users”) are... 3 3 2 in force, 1 not yet in force
The 3 laws behind 5.1.3-2 and MAP 1.6
MAP 3.3Targeted application scope is specified and documented based on the system’s... 2 2 1 in force, 1 not yet in force
The 2 laws behind 5.1.3-2 and MAP 3.3
MAP 3.5Processes for human oversight are defined, assessed, and documented in accordance with... 2 2 2 in force
The 2 laws behind 5.1.3-2 and MAP 3.5
MEASURE 2.6The AI system is evaluated regularly for safety risks – as identified in the MAP... 2 2 1 not yet in force, 1 proposed
The 2 laws behind 5.1.3-2 and MEASURE 2.6
5.1.4-1Capability for human oversight designed in and maintained. 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 5.1.4-1 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 5.1.4-1 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 5.1.4-1 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 5.1.4-1 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 5.1.4-1 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 5.1.4-1 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 5.1.4-1 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 5.1.4-1 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 5.1.4-1 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 5.1.4-1 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 5.1.4-1 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 5.1.4-1 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 5.1.4-1 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 5.1.4-1 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 5.1.4-1 and MEASURE 3.3
5.1.4-3Where oversight is a risk control, the technical measures behind it are built,... MAP 3.5Processes for human oversight are defined, assessed, and documented in accordance with... 4 2 2 in force, 2 not yet in force
The 4 laws behind 5.1.4-3 and MAP 3.5
MAP 3.3Targeted application scope is specified and documented based on the system’s... 2 1 2 in force
The 2 laws behind 5.1.4-3 and MAP 3.3
5.1.4-5End-users told which uses of the system are prohibited. MAP 3.3Targeted application scope is specified and documented based on the system’s... 143 86 124 in force, 15 not yet in force, 1 blocked by a court, 3 proposed
The 143 laws behind 5.1.4-5 and MAP 3.3

and 133 more, every one in the free file.

5.2.1-1Full inventory of assets, including their dependencies and connections. 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 5.2.1-1 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 5.2.1-1 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 5.2.1-1 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 5.2.1-1 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 5.2.1-1 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 5.2.1-1 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 5.2.1-1 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 5.2.1-1 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 5.2.1-1 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 5.2.1-1 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 5.2.1-1 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 5.2.1-1 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 5.2.1-1 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 5.2.1-1 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 5.2.1-1 and MEASURE 3.3
5.2.1-4Sensitive data such as training and test sets protected from unauthorised access. 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 5.2.1-4 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 5.2.1-4 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 5.2.1-4 and MEASURE 2.7
5.2.2-5AI-specific incident management and recovery plans that are created, tested and maintained. GOVERN 1.1Legal and regulatory requirements involving AI are understood, managed, and documented. 15 11 12 in force, 2 not yet in force, 1 proposed
The 15 laws behind 5.2.2-5 and GOVERN 1.1

and 5 more, every one in the free file.

MANAGE 4.3Incidents and errors are communicated to relevant AI actors, including affected... 9 7 5 in force, 3 not yet in force, 1 proposed
The 9 laws behind 5.2.2-5 and MANAGE 4.3
GOVERN 4.2Organizational teams document the risks and potential impacts of the AI technology... 8 6 5 in force, 3 not yet in force
The 8 laws behind 5.2.2-5 and GOVERN 4.2
MANAGE 4.1Post-deployment AI system monitoring plans are implemented, including mechanisms for... 6 6 6 in force
The 6 laws behind 5.2.2-5 and MANAGE 4.1
GOVERN 4.3Organizational practices are in place to enable AI testing, identification of... 2 2 1 in force, 1 not yet in force
The 2 laws behind 5.2.2-5 and GOVERN 4.3
5.2.2-6Contracts with cloud providers that back the requirements above. GOVERN 6.1Policies and procedures are in place that address AI risks associated with third-party... 2 2 1 in force, 1 not yet in force
The 2 laws behind 5.2.2-6 and GOVERN 6.1
5.2.4-1Developers keep an audit trail of system design and post-deployment maintenance plans... 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 5.2.4-1 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 5.2.4-1 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 5.2.4-1 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 5.2.4-1 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 5.2.4-1 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 5.2.4-1 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 5.2.4-1 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 5.2.4-1 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 5.2.4-1 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 5.2.4-1 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 5.2.4-1 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 5.2.4-1 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 5.2.4-1 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 5.2.4-1 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 5.2.4-1 and MEASURE 3.3
5.2.4-2.1Minimum record for training data: its source, such as a page URL, and when it was collected. MAP 4.1Approaches for mapping AI technology and legal risks of its components – including the... 18 16 17 in force, 1 not yet in force
The 18 laws behind 5.2.4-2.1 and MAP 4.1

and 8 more, every one in the free file.

5.3.1-1Users told where and how their data is used, accessed and stored, with developers... MEASURE 2.8Risks associated with transparency and accountability – as identified in the MAP... 64 43 40 in force, 12 not yet in force, 12 proposed
The 64 laws behind 5.3.1-1 and MEASURE 2.8

and 54 more, every one in the free file.

MEASURE 3.3Feedback processes for end users and impacted communities to report problems and... 9 9 2 in force, 1 not yet in force, 6 proposed
The 9 laws behind 5.3.1-1 and MEASURE 3.3
GOVERN 4.2Organizational teams document the risks and potential impacts of the AI technology... 8 6 4 in force, 3 not yet in force, 1 proposed
The 8 laws behind 5.3.1-1 and GOVERN 4.2
MAP 2.2Information about the AI system’s knowledge limits and how system output may be... 4 3 1 in force, 3 not yet in force
The 4 laws behind 5.3.1-1 and MAP 2.2
MAP 1.6System requirements (e.g., “the system shall respect the privacy of its users”) are... 3 3 2 in force, 1 not yet in force
The 3 laws behind 5.3.1-1 and MAP 1.6
MAP 3.3Targeted application scope is specified and documented based on the system’s... 2 2 1 in force, 1 not yet in force
The 2 laws behind 5.3.1-1 and MAP 3.3
MAP 3.5Processes for human oversight are defined, assessed, and documented in accordance with... 2 2 2 in force
The 2 laws behind 5.3.1-1 and MAP 3.5
MEASURE 2.6The AI system is evaluated regularly for safety risks – as identified in the MAP... 2 2 1 not yet in force, 1 proposed
The 2 laws behind 5.3.1-1 and MEASURE 2.6
5.3.1-2.1That guidance covers proper use, limits and likely failure modes. MEASURE 2.8Risks associated with transparency and accountability – as identified in the MAP... 64 43 40 in force, 12 not yet in force, 12 proposed
The 64 laws behind 5.3.1-2.1 and MEASURE 2.8

and 54 more, every one in the free file.

MEASURE 3.3Feedback processes for end users and impacted communities to report problems and... 9 9 2 in force, 1 not yet in force, 6 proposed
The 9 laws behind 5.3.1-2.1 and MEASURE 3.3
GOVERN 4.2Organizational teams document the risks and potential impacts of the AI technology... 8 6 4 in force, 3 not yet in force, 1 proposed
The 8 laws behind 5.3.1-2.1 and GOVERN 4.2
MAP 2.2Information about the AI system’s knowledge limits and how system output may be... 4 3 1 in force, 3 not yet in force
The 4 laws behind 5.3.1-2.1 and MAP 2.2
MAP 1.6System requirements (e.g., “the system shall respect the privacy of its users”) are... 3 3 2 in force, 1 not yet in force
The 3 laws behind 5.3.1-2.1 and MAP 1.6
MAP 3.3Targeted application scope is specified and documented based on the system’s... 2 2 1 in force, 1 not yet in force
The 2 laws behind 5.3.1-2.1 and MAP 3.3
MAP 3.5Processes for human oversight are defined, assessed, and documented in accordance with... 2 2 2 in force
The 2 laws behind 5.3.1-2.1 and MAP 3.5
MEASURE 2.6The AI system is evaluated regularly for safety risks – as identified in the MAP... 2 2 1 not yet in force, 1 proposed
The 2 laws behind 5.3.1-2.1 and MEASURE 2.6
5.4.2-1Operators log system and user actions. 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 5.4.2-1 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 5.4.2-1 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 5.4.2-1 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 5.4.2-1 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 5.4.2-1 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 5.4.2-1 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 5.4.2-1 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 5.4.2-1 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 5.4.2-1 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 5.4.2-1 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 5.4.2-1 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 5.4.2-1 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 5.4.2-1 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 5.4.2-1 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 5.4.2-1 and MEASURE 3.3
5.4.2-2Logs analysed for anomalies, breaches and effects of drift or 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 5.4.2-2 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 5.4.2-2 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 5.4.2-2 and MEASURE 2.7
Not connected to the NIST AI RMF: 53 of ETSI EN 304 223's provisions

Short of 2 laws

The same duties reach these and a NIST AI RMF control, in fewer than 2 of the laws we track.

No law we track reaches these

No duty in the laws we track reaches these provisions.

  • 5.1.1-1 AI security content in the regular staff training programme, kept current.
  • 5.1.1-1.1 That training is adjusted to each person's role.
  • 5.1.1-2 All staff kept aware of current AI-related threats and the mitigations that exist.
  • 5.1.1-2.1 Threat updates circulated through several internal channels.
  • 5.1.1-2.2 Developers trained in secure coding and system design for AI work.
  • 5.1.2-1.1 Data custodians inside the developer's own organisation join the requirements discussion.
  • 5.1.2-3 Audit trail covering models, datasets and prompts through their lifecycle.
  • 5.1.2-4 Security risk assessment and due diligence before using an external component.
  • 5.1.2-5 Data custodians check that the intended use suits how sensitive the training data is.
  • 5.1.2-5.1 Staff encouraged to raise AI security concerns, with safeguards in place for doing so.
  • 5.1.3-1.1 Threat modelling repeated whenever a setting or configuration option is added or changed.
  • 5.1.3-1.2 Developers manage the risk from model capabilities the system does not need.
  • 5.1.3-1.3 Operators apply controls to the risks found, weighed against cost and their risk tolerance.
  • 5.1.3-3 Operators seek assurance from outside parties who hold responsibility for identified risks.
  • 5.1.3-4 Continuous monitoring and review of infrastructure against the organisation's risk appetite.
  • 5.1.4-2 Systems designed so people can judge the outputs they answer for.
  • 5.1.4-4 Developers verify that the data custodian's security controls made it into the build.
  • 5.2.1-2 Tooling and processes to track, authenticate, version and secure AI assets.
  • 5.2.1-3 Disaster recovery plans adapted to attacks aimed at AI systems.
  • 5.2.1-3.1 A known good state can be restored.
  • 5.2.1-4.1 Checks and sanitisation applied to data and inputs, and repeated when the model is revised.
  • 5.2.1-4.2 Proportionate protection where training data or model weights may be confidential.
  • 5.2.2-1 Access-control review, and measures to secure APIs, models, data and pipelines.
  • 5.2.2-2 Controls, such as rate limits, on any API offered to outside parties.
  • 5.2.2-3 Separate environments for development and tuning, with least privilege enforced technically.
  • 5.2.2-4 A published, easy-to-find vulnerability disclosure policy.
  • 5.2.3-1 Secure software supply-chain practice for developing models and systems.
  • 5.2.3-2 Written justification when using models or components that are poorly documented or secured.
  • 5.2.3-2.1 Mitigating controls and a risk assessment for those components.
  • 5.2.3-2.2 That justification shared with end-users in an accessible way.
  • 5.2.3-3 Evaluations run again on released models before they are adopted.
  • 5.2.3-4 End-users told before a model is updated.
  • 5.2.4-1.1 That documentation records security-relevant facts such as data sources, scope,...
  • 5.2.4-1.2 Cryptographic hashes published for model components handed to others.
  • 5.2.4-2 Records of how publicly sourced training data was obtained, where it came from and how...
  • 5.2.4-3 Audit log of changes to system prompts and other configuration that alter behaviour.
  • 5.2.5-1 Every model, application and system is security-assessed before release.
  • 5.2.5-2 Operators test before deployment, with developer support.
  • 5.2.5-2.1 Independent testers with relevant AI skills used for security testing.
  • 5.2.5-3 Developers pass their test findings to operators.
  • 5.2.5-4 Outputs evaluated so that non-public details of the model or its training data cannot...
  • 5.2.5-4.1 Outputs evaluated so users cannot gain unintended influence over the system.
  • 5.3.1-2 Accessible guidance on using, managing, integrating and configuring the system.
  • 5.3.1-2.2 Users proactively told about security-relevant updates.
  • 5.4.1-1 Developers issue security patches and notify operators, who pass them to users.
  • 5.4.1-1.1 Contingency mechanisms for cases where an update cannot be issued.
  • 5.4.1-2 A major update is treated as a new model version and re-tested.
  • 5.4.1-3 Operators helped to evaluate model changes, for example with preview access and versioned APIs.
  • 5.4.2-3 Internal system states monitored where that helps address security threats.
  • 5.4.2-4 Model and system performance tracked over time for shifts in behaviour that touch security.
  • 5.5.1-1 Data custodians involved and assets securely disposed of when training data or a model...
  • 5.5.1-2 Data custodians involved and data and configuration securely deleted when a model or...

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 ETSI EN 304 223 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 provisions 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

Identifiers refer to ETSI EN 304 223 V2.1.1 (2025-12), © ETSI 2025, all rights reserved. ETSI owns the standard; no ETSI text (titles or sentences) is reproduced here. The standard is free to download from ETSI.