AI RESEARCH
Insider Attacks in Multi-Agent LLM Consensus Systems
arXiv CS.AI
•
ArXi:2605.08268v1 Announce Type: cross Large language models (LLMs) are increasingly deployed in multi-agent systems where agents communicate in natural language to solve tasks jointly. A key capability in such systems is consensus formation, where agents iteratively exchange messages and update decisions to reach a shared outcome. However, most existing multi-agent LLM frameworks assume that all participating agents are aligned with the system objective. In practice, a malicious insider may participate as a legitimate member of the group while pursuing a hidden adversarial goal.