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While these capabilities improve automation and scalability, they also pose new security risks in multi-agent networks.\n  Existing research has studied how individual LLM-based agents can be compromised through prompt injection, jailbreaking, poisoned retrieval data, or malicious extensions. Less is known about what happens after one agent is compromised inside a multi-agent network. In particular, inherited memory from parent agents can carry malicious instructions, outdated states, or unintended behavioral rules into newly created subagents, allowing a local compromise to spread across agent boundaries.\n  In this paper, we model contemporary multi-agent networks through the lens of subagent inheritance. 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