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We saw this exact failure mode at AgenticQA. Our screening agent was 'obedient' to a fault—under basic social engineering pressure (e.g., 'URGENT AUDIT'), it wo
by Saurabh_Kumar_ 11mo ago
We saw this exact failure mode at AgenticQA. Our screening agent was 'obedient' to a fault—under basic social engineering pressure (e.g., 'URGENT AUDIT'), it would override its system prompt and leak PII logs.
The issue isn't the prompt; it's the lack of a runtime guardrail. An LLM cannot be trusted to police itself when the context window gets messy.
I built a middleware API to act as an external circuit breaker for this. It runs adversarial simulations (PII extraction, infinite loops) against the agent logic before deployment. It catches the drift that unit tests miss.
Open sourced the core logic here: [https://github.com/Saurabh0377/agentic-qa-api https://github.com/Saurabh0377/agentic-qa-api] Live demo of it blocking a PII leak: [https://agentic-qa-api.onrender.com/docs https://agentic-qa-api.onrender.com/docs]"
- samarthr1 11mo agoI remember reading another comment a while ago about being able to only trust an llm with sensitive info only if you can guarantee that the output will only be viewed by people who already had access to the sensitive info already, or cannot control any of the inputs to the llm.
- undefeated 11mo agoUhm... duh? > or cannot control any of the inputs to the llm Seeing as LLMs are non-deterministic, I think even this is not enough of a restriction.