AI Agent Security Testing Platform

A tool that automatically tests and breaks AI agents to find vulnerabilities before attackers do. Teams building AI agents need to validate their systems are secure and resilient. This could be a SaaS platform offering automated security audits and penetration testing specifically for AI systems.

Enterprises deploying agentic AI systems are now encountering prompt injection, tool misuse, and privilege escalation vectors that traditional AppSec tools don't cover — OWASP published its LLM Top 10 specifically because existing scanners miss these attack classes entirely. The closest reference point is Garak (open-source LLM vulnerability scanner) or HiddenLayer on the ML model security side, but neither focuses on multi-step agent behavior and tool-chain exploitation specifically. The $5k–$25k/mo revenue band is plausible given security buyers are accustomed to paying for compliance and audit tooling, and even a small number of enterprise or mid-market contracts gets you there. The biggest risk is that this space is moving fast enough that cloud providers and agent frameworks (LangChain, AutoGen) bundle basic security testing natively, commoditizing the core audit function before a standalone product achieves sufficient differentiation.