AI Red Teaming: Applying Software TEVV for AI Evaluations
governmentCredibility Rating
High quality. Established institution or organization with editorial oversight and accountability.
Rating inherited from publication venue: CISA
Official CISA guidance applying traditional software testing frameworks to AI red teaming; relevant for practitioners in government, critical infrastructure, and organizations seeking authoritative federal guidance on AI security evaluation practices.
Metadata
Summary
A CISA publication exploring how traditional software Testing, Evaluation, Verification, and Validation (TEVV) methodologies can be adapted and applied to AI red teaming exercises, helping organizations systematically evaluate AI system safety and security. The resource bridges established cybersecurity practices with emerging AI evaluation needs for government and critical infrastructure contexts.
Key Points
- •Adapts established software TEVV frameworks to address the unique challenges of evaluating AI systems for safety and security vulnerabilities.
- •Red teaming for AI requires expanded scope beyond traditional software testing, including adversarial prompting, model behavior analysis, and failure mode identification.
- •CISA positions AI red teaming as essential for critical infrastructure operators deploying AI in high-stakes environments.
- •Provides practical guidance for organizations seeking to integrate AI evaluations into existing cybersecurity assessment programs.
- •Emphasizes collaboration between AI developers, security professionals, and government stakeholders in evaluation processes.
Cited by 3 pages
| Page | Type | Quality |
|---|---|---|
| AI Evaluations | Research Area | 72.0 |
| Third-Party Model Auditing | Approach | 64.0 |
| Red Teaming | Research Area | 65.0 |
6f1d4fd3b52c7cb7 | Stable ID: MjQ5NjkyYz