adversarial-self-test

To test AI agent outputs for OWASP LLM vulnerabilities, run an adversarial self-test that evaluates code generation and tool invocation tasks against the Top 10 risks, producing structured findings and remediation guidance.

Adversarial testing for prompt injection is a security audit mechanism that identifies and mitigates malicious inputs attempting to hijack agentic AI outputs, tracing potential exfiltration paths and enforcing structured risk mitigation.

Check for insecure output handling in LLM code generation by running an adversarial self-test to assess tool invocation risks and command execution vulnerabilities, yielding actionable remediation notes for audit readiness.

Run a security audit on AI agent tool invocations after generating outputs that touch external systems or execute commands, ensuring data exfiltration tracing and prompt injection testing are completed before production deployment.

Yes, you can trace data exfiltration paths in production AI agent runs by applying a reproducible security testing workflow that evaluates data handling tasks against defined OWASP risk categories to generate audit-ready findings.