When most people think about AI security, they think about testing a language model.
Can it resist prompt injection?
Can it resist jailbreaks?
Can it avoid hallucinations?
Those questions matter—but they're only part of the picture.
Modern AI applications are no longer just models.
They're agents.
Agents call tools.
They access APIs.
They maintain memory.
They connect to enterprise systems.
They interact with MCP servers.
They execute workflows.
Every one of those capabilities introduces new security boundaries that a model-only evaluation can miss.
That's why Crucible was built around deployed HTTP-accessible AI agents rather than raw LLMs. It evaluates the system the way users experience it in production: as a complete application with tools, permissions, memory, and behavior—not just a text generator.
The future of AI security isn't just testing what models say.
It's testing what agents do.
Pytest for AI Agents.
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