Agent skill risk detection that isn't 99.9% false positives
60/100 commercial intent80/100 confidenceLLM agent skill security
The problem, as people describe it
Security teams building LLM agents currently rely on lexical analysis for skill risk detection, leading to an overwhelming number of false positives. This broken workflow wastes significant time triaging benign code and creates a false sense of security, as the primary attack surface (LLM instructions) is largely unaddressed.
- Corroboration
- 1×
- Sources
- 1
- Category
- Security / Compliance
- Found on
- github
The dossier for this gap
The source complaints and their links, the MVP scope, suggested pricing, the competitors already in this space, the risks, and a validation playbook you can run in an afternoon. Create a free account to open it.
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