1. ETSI
1.1. EN 304 223 - Securing Artificial Intelligence (SAI); Baseline Cyber Security Requirements for AI Models and Systems
1.1.1. Provision 5.1.3-1
1.1.2. Provision 5.1.3-1.1
1.1.3. Provision 5.1.3-1.2
1.1.4. Provision 5.1.3-1.3
1.1.5. Provision 5.1.3-2
1.1.6. Provision 5.1.3-3
1.1.7. Provision 5.1.3-4
1.2. TR 104 128 - Securing Artificial Intelligence (SAI); Guide to Cyber Security for AI Models and Systems
1.2.1. Provision 5.1.3-1
1.2.2. Provision 5.1.3-1.1
1.2.3. Provision 5.1.3-1.2
1.2.4. Provision 5.1.3-1.3
1.2.5. Provision 5.1.3-2
1.2.6. Provision 5.1.3-3
1.2.7. Provision 5.1.3-4
1.3. TR 104 048 - Securing Artificial Intelligence (SAI); Data Supply Chain Security
1.3.1. 6.5 Analysis - Hash checks
1.4. SAI 002 - Securing Artificial Intelligence (SAI); Data Supply Chain Security
1.4.1. 6.1.3 Supply chain security - 1
1.4.2. 6.5 - Following standard cybersecurity supply chain guidance
2. NIST
2.1. AI RMF 1.0
2.1.1. GOVERN 1.3
2.1.2. GOVERN 1.4
2.1.3. GOVERN 1.5
2.1.4. GOVERN 2.1
2.1.5. GOVERN 3.1
2.1.6. GOVERN 4.2
2.1.7. MAP 1.5
2.1.8. MAP 3.2
2.1.9. MAP 4.2
2.1.10. MAP 5.1
2.1.11. MEASURE 1.1
2.1.12. MEASURE 2.8
2.1.13. MEASURE 2.10
2.1.14. MEASURE 3.1
2.1.15. MEASURE 3.2
2.1.16. MANAGE 1.2
2.1.17. MANAGE 1.3
2.1.18. MANAGE 1.4
2.1.19. MANAGE 2.3
2.2. SP 800-218A
2.2.1. PW.1.1
2.2.2. RV.2.2
2.3. AI 800-1
2.3.1. Practice 1.1: Anticipate model capabilities - 5
2.3.2. Practice 1.1: Anticipate model capabilities - 7
2.3.3. Practice 1.2 Create threat profiles - 3
2.3.4. Practice 1.2 Create threat profiles - 4
2.3.5. Practice 1.3: Conduct risk assessments - 1
2.3.6. Practice 1.3: Conduct risk assessments - 2
2.3.7. Practice 1.3: Conduct risk assessments - 3
2.3.8. Practice 1.3: Conduct risk assessments - 4
2.3.9. Practice 1.3: Conduct risk assessments - 5
2.3.10. Practice 1.3: Conduct risk assessments - 6
2.3.11. Practice 1.3: Conduct risk assessments - 7
2.3.12. Practice 1.3: Conduct risk assessments - 8
2.3.13. Practice 2.1. Map anticipated model capabilities to appropriate risk mitigations to manage misuse risk - 1
2.3.14. Practice 2.1. Map anticipated model capabilities to appropriate risk mitigations to manage misuse risk - 2
2.3.15. Practice 2.1. Map anticipated model capabilities to appropriate risk mitigations to manage misuse risk - 3
2.3.16. Practice 2.1. Map anticipated model capabilities to appropriate risk mitigations to manage misuse risk - 4
2.3.17. Practice 2.1. Map anticipated model capabilities to appropriate risk mitigations to manage misuse risk - 5
2.3.18. Practice 2.2 Establish an organizational plan to manage misuse risk - 4
2.3.19. Practice 3.1: Assess misuse risk from threat actors gaining unauthorized access to the model - 1
2.3.20. Practice 3.1: Assess misuse risk from threat actors gaining unauthorized access to the model - 3
2.3.21. Practice 3.2: Maintain security practices sufficient to prevent unauthorized access - 4
2.3.22. Practice 5.2: Assess misuse risk based on implemented safeguards - 2
2.3.23. Practice 5.3: Adopt appropriate deployment strategies based on misuse risk assessments - 1
2.3.24. Practice 5.3: Adopt appropriate deployment strategies based on misuse risk assessments - 3
2.3.25. Practice 5.3: Adopt appropriate deployment strategies based on misuse risk assessments - 4
2.4. IR 8596: Cybersecurity Framework Profile for Artificial Intelligence (Cyber AI Profile): NIST Community Profile
2.4.1. GV.RM-01
2.4.2. GV.RM-02
2.4.3. GV.RM-03
2.4.4. GV.RM-04
2.4.5. GV.RM-05
2.4.6. GV.RM-06
2.4.7. GV.RM-07
2.4.8. GV.PO-01
2.4.9. GV.PO-02
2.4.10. GV.OV-01
2.4.11. GV.OV-02
2.4.12. GV.OV-03
2.4.13. GV.SC-01
2.4.14. ID.RA-02
2.4.15. ID.RA-03
2.4.16. ID.RA-04
2.4.17. ID.RA-05
2.4.18. ID.RA-06
2.4.19. ID.RA-07
2.4.20. RC.RP-04
3. MITRE
3.1. SAFE-AI
3.1.1. Vulnerability exploit
4. Multi Agency
4.1. Guidelines for secure AI system development
4.1.1. Model the threats to your system
5. European Commission
5.1. Ethics guidelines for trustworthy AI
5.1.1. 1.2.1 Resilience to attack and security
5.1.2. 1.7.2 Minimisation and Reporting of Negative Impacts
5.1.3. 2.1.2 Ethics and Rule of Law by Design
6. Personal Data Protection Commission Singapore (PDPC)
6.1. Model Artificial Intelligence Governance Framework Second Edition
6.1.1. 2. Risk management and internal controls - a)
6.1.2. 2. Risk management and internal controls - b) (i)
6.1.3. 2. Risk management and internal controls - b) (iv)
6.1.4. 2. Risk management and internal controls - b) (v)
7. Google
7.1. Secure AI Framework
7.1.1. Risk Governance
8. CoSAI
8.1. AI Incident Response Framework
8.1.1. 3.3.1. Preparation Phase - Risk Assessment & Threat Modeling
9. Microsoft
9.1. Cloud Adoption Framework - Secure AI
9.1.1. Discover AI security risks 4 - Conduct periodic risk assessments
9.2. Responsible AI Standard
9.2.1. A2.1
9.2.2. A2.2
9.2.3. A2.3
9.2.4. A5.7
9.2.5. T3.1
9.2.6. F3.7
9.2.7. RS2.1
9.2.8. RS2.2
9.2.9. RS3.3
9.2.10. RS3.4
9.2.11. RS3.6
10. Cloud Security Alliance (CSA)
10.1. AI Controls Matrix
10.1.1. A&A-06
10.1.2. AIS-01
10.1.3. BCR-01
10.1.4. BCR-02
10.1.5. CEK-06
10.1.6. CEK-07
10.1.7. CEK-20
10.1.8. DCS-05
10.1.9. DSP-09
10.1.10. DSP-21
10.1.11. GRC-02
10.1.12. GRC-03
10.1.13. GRC-09
10.1.14. GRC-10
10.1.15. IAM-08
10.1.16. I&S-08
10.1.17. MDS-01
10.1.18. MDS-06
10.1.19. MDS-11
10.1.20. MDS-12
10.1.21. STA-15
10.1.22. TVM-08
10.1.23. TVM-11
10.1.24. TVM-12
10.1.25. TVM-13
11. CISA
11.1. Principles for the Secure Integration of Artificial Intelligence in Operational Technology
11.1.1. 2.2.3 - Exposure of Sensitive Information
11.1.2. 4.1.2 - Understand the correctness of AI system results to support continued safe operation of systems in an OT environment.
11.1.3. 4.2.1 - Establish failsafe mechanisms that enable AI systems to fail gracefully without disrupting critical operations.
11.1.4. 4.2.3 - Incorporate AI considerations into the cybersecurity incident response plan.
12. NCSC/NSA/CISA etc
12.1. AI Data Security
12.1.1. 1.10 Conduct ongoing data security risk assessments
13. SANS
13.1. Critical AI Security Guidelines
13.1.1. 4.5 Modality
13.1.2. 4.6 Languages and Character Sets
14. OECD
14.1. Due Diligence Guidance for Responsible AI
14.1.1. Step 2.1 – Initial scoping of risks
14.1.2. Step 2.2 – In-depth assessment of most significant risks
14.1.3. Step 2.3 – Assess involvement with the actual or potential impact (cause, contribute, directly linked)
14.1.4. Step 2.4 – Prioritise the most significant (i.e., most salient) risks
14.1.5. Step 3.1 – Addressing risks that the enterprise causes or contributes to
15. IMDA
15.1. Model AI Governance Framework for Agentic AI
15.1.1. 2.1.1 Determine suitable use cases for agent deployment
16. SDAIA (Saudi Arabia)
16.1. AI Ethics Principles
16.1.1. Principle 5 – Reliability & Safety - Plan and Design - 2
16.1.2. Principle 7 – Accountability & Responsibility - Plan and Design - 2
16.2. Generative AI Guidelines
16.2.1. 4.5 Privacy & Security - 3
16.2.2. 4.5 Privacy & Security - 5
17. Cyber Security Council (UAE)
17.1. National Cyber Security Policy for Artificial Intelligence
17.1.1. 2.1.2
17.1.2. 2.2.4
17.1.3. 2.3.3
17.1.4. 3.1.2 Cyber Risk Management for AI/ML - 1
17.1.5. 3.1.2 Cyber Risk Management for AI/ML - 2
17.1.6. 3.1.2 Cyber Risk Management for AI/ML - 3
17.1.7. 3.1.2 Cyber Risk Management for AI/ML - 4
17.1.8. 3.1.2 Cyber Risk Management for AI/ML - 5
17.1.9. 3.1.4 Change Management and Reporting - 2
17.1.10. 3.2.2 Security Configuration Management - 2
17.1.11. 3.3.1 Security by Design for AI/ML Models - 2
17.1.12. 3.6.2 Incident Reporting and Management for AI/ML - 6
17.1.13. 3.6.3 Digital Forensics for AI/ML Security Incidents - 3
18. Smart Dubai (UAE)
18.1. AI Ethics Principles & Guidelines
18.1.1. 1.2.2.2
18.1.2. 1.2.2.3
19. Central Bank of the UAE
19.1. Guidance Note on the Consumer Protection and Responsible Adoption and Use of Artificial Intelligence and Machine Learning by Licensed Financial Institutions in the U.A.E
19.1.1. 2. Governance and Accountability - c
19.1.2. 2. Governance and Accountability - d
19.1.3. 2. Governance and Accountability - e
19.1.4. 8. Integration with Existing Frameworks - a
19.1.5. 8. Integration with Existing Frameworks - d
20. Qatar Central Bank
20.1. Artificial Intelligence Guidelines
20.1.1. 6.1
20.1.2. 6.2
20.1.3. 7.2
20.1.4. 7.6
20.1.5. 8.2.1
20.1.6. 9.1
20.1.7. 9.3
20.1.8. 9.4
20.1.9. 9.5
20.1.10. 9.5.1
20.1.11. 9.5.2
20.1.12. 9.6
20.1.13. 9.7
20.1.14. 9.8
20.1.15. 10.4
20.1.16. 12.3
20.1.17. 20.3
20.1.18. 20.9
20.1.19. 23.3
20.1.20. 23.5
21. MIC/METI (Japan)
21.1. AI Guidelines for Business
21.1.1. Human-Centric - 2 (b)
21.1.2. Safety - 1 (d)
21.1.3. Safety - 1 (e)
21.1.4. Ensuring security - 1 (c)
21.1.5. Ensuring security - 2
21.1.6. Accountability - 2
21.1.7. Accountability - 5 (a)
22. METI (Japan)
22.1. Governance Guidelines for Implementation of AI Principles
22.1.1. Action Target 1-3
22.1.2. Action Target 3-1
22.1.3. Action Target 3-1-1
22.1.4. Action Target 3-4-2
23. EU
23.1. EU AI Act
23.1.1. 9.1 Risk Management System
23.1.2. 9.2 Risk Management System
23.1.3. 9.3 Risk Management System
23.1.4. 9.4 Risk Management System
23.1.5. 9.5 Risk Management System
23.1.6. 9.6 Risk Management System
23.1.7. 9.9 Risk Management System
23.1.8. 9.10 Risk Management System
23.1.9. 55.8 Obligations of Providors of General-Purpose AI models with Systemic Risk
23.1.10. 55.9 Obligations of Providors of General-Purpose AI models with Systemic Risk
24. ISO/IEC
24.1. DIS 27090
24.1.1. 7.4
24.2. TR 27563:2023
24.2.1. 7.3
24.2.2. 7.4
24.2.3. 7.5
24.2.4. 7.6
24.2.5. 7.7
24.3. TR 27091
24.3.1. 6.3
24.4. TS 42119-2:2025
24.4.1. 6
25. CEN/CENELEC
25.1. prEN 40000-1-1
25.1.1. acceptable risk
25.1.2. residual cybersecurity risk
25.2. prEN 40000-1-2: Cybersecurity requirements for products with digital elements - Part 1-2: Principles for cyber resilience
25.2.1. 5.2
25.2.2. 6.3
25.2.3. 6.4
25.2.4. 6.6
25.2.5. 6.7
26. ENISA
26.1. Multilayer Framework for Good Cybersecurity Practices for AI
26.1.1. Networking 8
27. U.S. Department of Health & Human Services
27.1. Trustworthy AI (TAI) Playbook: Executive Summary
27.1.1. Safe / Secure
28. ICO
28.1. Guidance on the AI Auditing Framework - Draft guidance for consultation
28.1.1. How should we set a meaningful risk appetite?
28.1.2. What do we need to consider when undertaking data protection impact assessments for AI?
28.1.3. How do we identify and assess risks?
28.1.4. How do we identify mitigating measures?
28.1.5. How do we conclude our DPIA?
28.1.6. What’s different about security in AI compared to ‘traditional’ technologies?
28.1.7. Preventative Controls - 13
29. ISO
29.1. 42001:2023 - Information technology — Artificial intelligence — Management system
29.1.1. 6.1
29.1.2. 8.1
29.1.3. 8.2
29.1.4. 8.3
29.1.5. 8.4