owasp-ai-testing

OWASP AI testing is a structured framework using the AI Testing Guide v1 to evaluate AI system trustworthiness. It applies 44 test cases across four layers—Application, Model, Infrastructure, and Data—to identify weaknesses during audits and red-team exercises.

Run AI red-team exercises by collecting inputs like system architecture, model details, and risk context, then applying the 44 OWASP AGT test cases. This generates repeatable test plans, observable indicators, and audit-ready reports for governance compliance.

Yes, you can use OWASP AI testing for pre-release validation. It systematically assesses robustness, alignment, privacy, and security across the Application, Model, Infrastructure, and Data layers to identify weaknesses before deployment.

You need to provide inputs including ai_system_description, system_architecture, testing_scope, model_details, data_details, existing_controls, and risk_context to generate repeatable test plans and remediation guidance.

The best way is applying the OWASP AI Testing Guide v1 framework, which provides 44 structured test cases across four layers with clear objectives, observable indicators, and remediation guidance for automated test suite generation.

The OWASP AI Testing Guide requires comprehensive inputs like system architecture and data details to be effective. Without complete existing controls and risk context information, the generated test plans and audit-ready reports may lack full coverage of trustworthiness indicators.