The Austin-based startup broadly still sells what it used to in 2023, but Sestito told TechCrunch that the biggest change it's had to make was to extend its existing products discovery, runtime protection, attack simulation, and supply chain security to address prompt injection, agent manipulation, and malicious tool use. Sestito said inference is still inference, so whether it's on a traditional machine learning model, whether it's Gen AI, whether it's an agentic work stream, a lot of our technology still applied. So really, we haven't had to pivot, but we've had to grow our scope from traditional modeling to Gen AI to agentic. Sestito addressed that runtime security has especially become a priority as AI deployments grow common across businesses and likened it to traditional endpoint detection and response solutions, but specifically for AI.

OWASP testing guide right now AI pen testing large language models are the scope your rag pipe apps are the scope your AI co-pilots autonomous agents and machine learning models so similar attacker mindset but adaptive for AI so adaptive for AI so prompt injection testing model extraction and inversion attacks data poisoning and training and or embeddings adversarial input crafting agent tech tool abuse Now what are the common vulnerabilities Sensitive data data leakage Sensitive data leakage via prompt jail breaking guardrails Sensitive data leakage via prompt jail breaking guardrails Manipulating embeddings leading to false output Now next we have mapping threats to frameworks Right so we have few frameworks for The three which I have written Lindo Now very first one which we have Miter atlas Miter atlas Miter atlas Now Miter atlas is specifically for Miter atlas right so atlas is a