security-review-owasp-secure-ai-model-ops

To review AI agents for prompt injection and unsafe tool use, trace untrusted input paths across trust boundaries to verify whether user content can override model instructions or trigger privileged downstream actions.

Trust boundary analysis in secure AI model ops traces how untrusted input influences model instructions, tool calls, and downstream actions to identify context leakage and excessive agent autonomy.

Prevent context leakage in AI agent retrieval and memory workflows by reviewing code, configuration, and architecture to validate output execution paths and separate confirmed weaknesses from review gaps.

Yes, you can assess excessive agent autonomy and runtime controls by reviewing logging, monitoring, governance, and deployment paths to ensure operational security checks validate unsafe automation.

The best way to perform an evidence-based security review of AI plugin architectures is to apply explicit trust-boundary tracing and validate output execution paths across agent, prompt, and plugin paths.