CISO AI Security Provider Evidence Checklist
A vendor-neutral record for testing AI-security claims against governance, architecture, controls, monitoring, and incident evidence.
Audience: CISO, CIO, CTO, Security leadership, Risk committee · Updated: 2026-08-11
Define the protected system and decision boundary
Record the AI system, data, identities, tools, deployment context, and business process in scope before comparing providers. A broad AI-security claim is not evidence of coverage for a specific system.
- System and model inventory
- Human and machine identities
- Data classifications
- Permitted tools and actions
- Business owner and security owner
Map controls to documented risks
Require each proposed control to identify the risk it addresses, where it is enforced, what evidence it produces, and which residual risks remain.
- Preventive and detective controls
- Policy-enforcement location
- Identity and permission model
- Logging and evidence retention
- Residual-risk owner
Test operational evidence
Evaluate integrations, deployment prerequisites, alert quality, failure behavior, administrator controls, and response workflows using the organization’s own representative scenarios.
Set monitoring and reassessment triggers
Document changes that require reassessment, including new models, agents, tools, data sources, permissions, integrations, attack methods, incidents, and material changes in vendor architecture.
Primary sources
- The NIST Cybersecurity Framework 2.0National Institute of Standards and Technology
- AI Risk Management FrameworkNational Institute of Standards and Technology
This guide is educational and does not replace accounting, legal, security, employment, regulatory, or audit advice.