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arXiv AI By Elias Hossain, Md Mehedi Hasan Nipu, Fatema Tuj Johora Faria, Shubhashis Roy Dipta, Maleeha Sheikh, Tasfia Nuzhat Ornee, Niloofar Yousefi

ChannelGuard: From Borrowed Safety to Application-Controlled Defenses in Multi-Agent LLMs

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ChannelGuard introduces an application‑controlled defense that inspects information at every handoff between models in multi‑agent LLM systems, eliminating the need for extra training or model calls. In over 5,700 test runs across five agent models, it stopped all attacks hidden in tool outputs, and on two open models it reduced successful prompt attacks from 80% to 3% and from 77% to 10%, without affecting accuracy on 30 math problems. The study shows that safety scores can mask very different underlying protections, and that relying solely on model or provider filters may be risky if either changes.

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