1. ETSI
1.1. EN 304 223 - Securing Artificial Intelligence (SAI); Baseline Cyber Security Requirements for AI Models and Systems
1.1.1. Provision 5.3.1-1
1.1.2. Provision 5.3.1-2
1.1.3. Provision 5.3.1-2.1
1.1.4. Provision 5.3.1-2.2
1.1.5. Provision 5.3.1-3
1.2. TR 104 128 - Securing Artificial Intelligence (SAI); Guide to Cyber Security for AI Models and Systems
1.2.1. Provision 5.3.1-1
1.2.2. Provision 5.3.1-2
1.2.3. Provision 5.3.1-2.1
1.2.4. Provision 5.3.1-2.2
1.2.5. Provision 5.3.1-3
2. NIST
2.1. AI RMF 1.0
2.1.1. MAP 5.2
2.1.2. MEASURE 3.3
2.1.3. MEASURE 4.1
2.1.4. MANAGE 4.3
2.2. SP 800-218A
2.2.1. PO.1.3
2.3. AI 800-1
2.3.1. Practice 6.1: Monitor for evidence of misuse - 4
2.3.2. Practice 6.3: Establish misuse reporting mechanisms - 1
2.3.3. Practice 6.3: Establish misuse reporting mechanisms - 3
2.3.4. Practice 7.1: Publish transparency reports - 4
2.3.5. Practice 7.1: Publish transparency reports - 5
2.3.6. Practice 7.1: Publish transparency reports - 6
2.3.7. Practice 7.2: Disclose information about risk management practices - 1
2.3.8. Practice 7.2: Disclose information about risk management practices - 2
2.3.9. Practice 7.3: Report misuse incidents - 3
2.4. IR 8596: Cybersecurity Framework Profile for Artificial Intelligence (Cyber AI Profile): NIST Community Profile
2.4.1. ID.RA-08
2.4.2. DE.AE-08
2.4.3. RS.CO-02
2.4.4. RS.CO-03
2.4.5. RC.CO-03
2.4.6. RC.CO-04
3. OWASP
3.1. OWASP Top 10 for Agentic Applications for 2026
3.1.1. ASI09: Human-Agent Trust Exploitation - 4
3.1.2. ASI09: Human-Agent Trust Exploitation - 8
3.2. LLM Top 10
3.2.1. LLM02: Sensitive Information Disclosure - 7
3.2.2. LLM02: Sensitive Information Disclosure - 8
3.2.3. LLM02: Sensitive Information Disclosure - 9
3.2.4. LLM09: Misinformation - 3
3.2.5. LLM09: Misinformation - 5
3.2.6. LLM09: Misinformation - 7
3.2.7. LLM09: Misinformation - 8
3.3. AI Exchange
3.3.1. 1.3. Controls to limit the effects of unwanted behaviour - AI TRANSPARENCY
3.3.2. 1.3. Controls to limit the effects of unwanted behaviour - EXPLAINABILITY
4. Multi Agency
4.1. Guidelines for secure AI system development
4.1.1. Make it easy for users to do the right things
5. European Commission
5.1. Assessment List for Trustworthy Artificial Intelligence (ALTAI)
5.1.1. REQUIREMENT #4 Transparency
5.2. Ethics guidelines for trustworthy AI
5.2.1. 1.1.2 Human Agency
5.2.2. 1.4.3 Communication
6. Personal Data Protection Commission Singapore (PDPC)
6.1. Model Artificial Intelligence Governance Framework Second Edition
6.1.1. 1. Clear roles and responsibilities for the ethical deployment of AI - c) (iii)
6.1.2. Reproducibility - c)
6.1.3. Interacting with consumers - a)
6.1.4. Interacting with consumers - b)
6.1.5. Interacting with consumers - c)
6.1.6. Interacting with consumers - d)
7. Google
7.1. Secure AI Framework
7.1.1. User Data Management
7.1.2. User Transparency and Controls
7.1.3. User Policies and Education
8. CoSAI
8.1. AI Incident Response Framework
8.1.1. 3.3.2. Detection and Analysis Phase - Initial Triage - Priority Assignment
8.1.2. 3.3.3. Containment, Eradication, and Recovery Phase - Recovery Procedures - User Communication
8.2. Model Context Protocol (MCP) Security
8.2.1. 3.2.8 Secure Tool and UX Design
9. Microsoft
9.1. Responsible AI Standard
9.1.1. A3.7
9.1.2. A3.8
9.1.3. T1.2
9.1.4. T3.2
9.1.5. T3.3
9.1.6. F1.9
9.1.7. RS2.4
9.1.8. RS3.7
10. Cloud Security Alliance (CSA)
10.1. AI Controls Matrix
10.1.1. BCR-07
10.1.2. DSP-18
10.1.3. GRC-14
10.1.4. SEF-03
10.1.5. SEF-07
10.1.6. STA-04
11. OpenAI
11.1. Safety Best Practices
11.1.1. Allow users to report issues
12. CISA
12.1. Principles for the Secure Integration of Artificial Intelligence in Operational Technology
12.1.1. 1.3.3 Educate Personnel on AI - Leveraging explainable AI
12.1.2. 4.1.6 - Explore new AI explainability and transparency tools.
13. OECD
13.1. Due Diligence Guidance for Responsible AI
13.1.1. Step 5 - Communicate actions to address impacts
14. IMDA
14.1. Model AI Governance Framework for Agentic AI
14.1.1. 2.2.1 End Users
14.1.2. 2.4 Enable end-user responsibility
14.1.3. 2.4.1 Different users, different needs
14.1.4. 2.4.2 Users who interact with agents
15. SDAIA (Saudi Arabia)
15.1. AI Ethics Principles
15.1.1. Principle 6 – Transparency & Explainability - Plan and Design - 1
15.1.2. Principle 6 – Transparency & Explainability - Plan and Design - 2
15.1.3. Principle 6 – Transparency & Explainability - Build and Validate - 2
15.1.4. Principle 6 – Transparency & Explainability - Deploy and Monitor - 1
15.1.5. Principle 6 – Transparency & Explainability - Deploy and Monitor - 2
16. Cyber Security Council (UAE)
16.1. National Cyber Security Policy for Artificial Intelligence
16.1.1. 3.6.2 Incident Reporting and Management for AI/ML - 2
16.1.2. 3.6.2 Incident Reporting and Management for AI/ML - 3
17. Smart Dubai (UAE)
17.1. AI Ethics Principles & Guidelines
17.1.1. 1.2.3.2
17.1.2. 1.2.4.3
17.1.3. 1.2.5.1
17.1.4. 1.2.7.2
17.1.5. 1.3.2.1
17.1.6. 1.3.2.2
17.1.7. 1.4.1.1
17.1.8. 1.4.1.3
17.1.9. 1.4.2.1
18. UAE Ministry of Cabinet Affairs
18.1. The UAE Charter for the Development and Use of Artificial Intelligence
18.1.1. 5. Transparancy
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. 4. Transparency and Explain ability - a
19.1.2. 4. Transparency and Explain ability - d
20. Qatar Central Bank
20.1. Artificial Intelligence Guidelines
20.1.1. 14.2.2
20.1.2. 15.2
20.1.3. 19.5
20.1.4. 20.1
20.1.5. 20.2
20.1.6. 20.4
20.1.7. 20.5
20.1.8. 20.6
20.1.9. 20.8
20.1.10. 21.3
21. MIC/METI (Japan)
21.1. AI Guidelines for Business
21.1.1. Human-Centric - 4
21.1.2. Human-Centric - 5
21.1.3. Transparency - 2 (a)
21.1.4. Transparency - 2 (b)
21.1.5. Transparency - 2 (c)
21.1.6. Transparency - 3 (a)
21.1.7. Transparency - 4
21.1.8. Accountability - 5 (b)
21.1.9. Accountability - 5 (c)
21.1.10. Education/literacy - 3
21.1.11. Innovation - 3
22. METI (Japan)
22.1. Governance Guidelines for Implementation of AI Principles
22.1.1. Action Target 3-1-2
22.1.2. Action Target 3-3
23. EU
23.1. EU AI Act
23.1.1. 13.2 Transparency and Provision of Information to Deployers
23.1.2. 13.3 Transparency and Provision of Information to Deployers
23.1.3. 15.3 Accuracy, Robustness and Cybersecurity
23.1.4. 26.7 Obligations of deployers of high-risk AI systems
23.1.5. 26.8 Obligations of deployers of high-risk AI systems
23.1.6. 26.11 Obligations of deployers of high-risk AI systems
23.1.7. 50.2 Transparency obligations for providers and deployers of certain AI systems
23.1.8. 50.4 Transparency obligations for providers and deployers of certain AI systems
23.1.9. 50.5 Transparency obligations for providers and deployers of certain AI systems
23.1.10. 53.1 Obligations for providers of general purpose AI models
23.1.11. 53.2 Obligations for providers of general purpose AI models
24. ENISA
24.1. Multilayer Framework for Good Cybersecurity Practices for AI
24.1.1. From the lab to the market 7
24.1.2. Networking 2
24.1.3. Networking 5
25. U.S. Department of Health & Human Services
25.1. Trustworthy AI (TAI) Playbook: Executive Summary
25.1.1. Transparent / Explainable
26. ICO
26.1. Guidance on the AI Auditing Framework - Draft guidance for consultation
26.1.1. What steps should we take to manage the risks of privacy attacks on AI models? - 3
27. ISO
27.1. 42001:2023 - Information technology — Artificial intelligence — Management system
27.1.1. 7.3
27.1.2. 7.4