AI Security Vendor Evaluation Master Framework
Purpose: Provide vendor-neutral scoring criteria and evidence requirements for AI security product evaluation and PoC execution.
Audience: Procurement, security architecture, vendor evaluation teams, AI governance, audit, management.
Evaluation Domains
| Domain | What to Evaluate |
|---|---|
| Browser AI Security | AI discovery, prompt monitoring, upload protection, policy enforcement, auditability |
| IDE Security | Source code protection, secret detection, IDE assistant visibility, developer governance |
| Runtime AI Security | Prompt injection, output inspection, AI API protection, RAG security, custom AI application monitoring |
| Agentic AI Governance | Agent inventory, tool governance, action traceability, approval workflows, MCP visibility |
| Sovereignty | Data residency, retention, training exclusion, administrative access, deployment model |
| Auditability | Prompt/response logging, user/device attribution, event export, forensic reconstruction |
| Integration | Identity, DLP, CASB, endpoint, DevSecOps, SIEM/SOC, API security integration |
| Operational Complexity | Deployment effort, user impact, tuning, administration, scalability and support model |
Scoring Model
| Score | Meaning |
|---|---|
| 5 | Strong capability demonstrated with evidence |
| 4 | Good capability with minor validation required |
| 3 | Medium capability; PoC evidence required |
| 2 | Limited capability; complementary control likely required |
| 1 | Not suitable for this domain |
| 0 | Not available or not demonstrated |
Evaluation Checklist
Apply the same checklist to every supplier under evaluation, and score each domain with the scoring model above.
| Domain | What to Validate | Evidence Required |
|---|---|---|
| Browser AI Security | Validate AI discovery, prompt monitoring, upload protection and policy enforcement. | Browser PoC results, platform support matrix |
| IDE Security | Validate source code protection, secret detection and AI assistant visibility. | IDE PoC results, supported IDE list |
| Runtime AI Security | Validate prompt injection, output filtering, AI API protection and RAG support. | Runtime test results, architecture diagram |
| Agentic AI Governance | Validate agent inventory, tool monitoring, approval workflow and MCP support. | Agent PoC results, tool/API matrix |
| Sovereignty | Validate residency, retention, training exclusion, admin access and deployment model. | Vendor documentation, contractual evidence |
| Auditability | Validate logs, attribution, export, retention and SIEM forwarding. | Audit export samples, SIEM event IDs |
| Integration | Validate identity, DLP, CASB, endpoint, DevSecOps, SIEM/SOC and API security integration. | Integration test results, supported integration list |
| Operational Complexity | Validate deployment, endpoint impact, tuning requirements and support model. | Deployment plan, admin guide |
Required Vendor Evidence
- Product architecture.
- Deployment options.
- Data flow and processing locations.
- Supported browsers, operating systems, IDEs and AI platforms.
- Prompt/file inspection method.
- Logging and retention model.
- SIEM/SOC integration approach.
- Access control and administrative audit model.
- PoC test results mapped to control objectives.
- Security documentation and contractual commitments.
PoC Decision Notes Template
Proceed to PoC:
PoC Scope:
Required Test Cases:
Required Integrations:
Risk Areas Covered:
Known Gaps:
Complementary Controls Required:
Final Recommendation Template
Vendor Name:
Primary Strengths:
Key Limitations:
Best-Fit Use Cases:
Complementary Controls Required:
Sovereignty Validation Status:
Operational Complexity:
Overall Recommendation:
Proceed / Proceed with Conditions / Do Not Proceed: