Show HN: When your agent LLM judge become your enemy

Category: security

Tags: llm-security, multi-agent, prompt-injection, rag, red-teaming

Score: 7.0/10 (Innovation: 8, Technical: 7, Documentation: 7, Utility: 6)

This project systematically explores a novel security vulnerability in multi-agent LLM systems called 'cross-channel authority convergence', where defenses like structured metadata prefixes ironically make agents more exploitable. It provides a reproducible experimental framework for testing LLM agent security, revealing counterintuitive failure modes that challenge common assumptions about RAG safety.

Target audience: security researchers, ML engineers, AI safety engineers

Repository: https://dmitriibuchilin.substack.com/p/we-hardened-an-llm-agent-each-defense · Python

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