SOURCE-LINKED INTELLIGENCE
SoK: When Safe Agents Fail Together: The Security of Multi Agent LLM Systems
Safe agents can fail together. Multi-agent LLM systems (MAS) move information, state, decisions, and authority across principal boundaries, creating failures that local checks may miss. Without an execution-level view, a multi-agent setting can easily be mistaken for evidence of a genuinely multi-agent security effect. We thus systematize MAS security through an execution-centered analysis of 197 works, covering six interaction interfaces, four adversary positions, seven system-level risks, and eight recurring attack paths. We introduce an A-I-R framework that organizes attacks by adversary po
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-01T02:34:44.000Z
First collected: 2026-09-21T06:21:59.299Z. This is not the publication date.