One of the biggest misconceptions in AI security is that a single test is enough.
Run a few prompt injection payloads.
Check the responses.
Ship to production.
Modern AI agents are far more complex.
A production agent may interact with tools, memory systems, browsers, MCP servers, enterprise knowledge bases, cloud infrastructure, and external APIs. Each of those components introduces different security risks.
That's why Crucible organizes testing into 13 dedicated security modules, each focused on a different class of vulnerabilities. Instead of producing isolated results, the framework combines those findings into a single report, giving developers a broader view of their agent's security posture.
Security isn't about asking:
"Did we test prompt injection?"
It's about asking:
"What parts of our AI system haven't we tested yet?"
Comprehensive coverage is what turns security testing into production confidence.
Pytest for AI Agents.
Top comments (0)