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Oct 12 · Monday

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Found 2 papers
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Attack technique

Gradient and representation optimization2Side channels0Dormant triggers3

System type

Models and APIs50LLM applications8AI Agent14web agent4Multi-agent systems2Embodied systems and robotics6
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Attack technique：Gradient and representation optimizationAttack technique：Side channelsSystem type：Multi-agent systemsClear all

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  1. AttacksarXiv 2609.39788

    研究：多智能体系统潜在通信链路可被训练用于提升有害顺从

    提出只训练或篡改多智能体潜在通信链路来提高有害遵从

    arXiv
    2609.39788
    Published
    Layer
    Application layer
    Setting
    Multi-agent systems
    Evaluated models
    Llama-3.2-3B-Instruct, Qwen2.5-3B-Instruct, Gemma-3-1B-IT and others7
    Abstract潜在链路本身即可改变冻结智能体系统的安全，奖励既能攻击也能修复。

    学习得到的潜在通信链路会改变由冻结、对齐智能体组成的系统是否遵从有害请求。。作者研究三种拓扑：双智能体、三级顺序协作，以及双专家加汇总。

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  2. AttacksarXiv 2603.11132

    WebWeaver：以隐蔽的上下文推断攻破 LLM 多智能体系统拓扑机密性

    提出 WebWeaver ，只攻陷单个智能体并从对话上下文恢复多智能体通信拓扑

    arXiv
    2603.11132
    Published
    Layer
    Application layer
    Setting
    Multi-agent systems
    Evaluated models
    Llama 3.1 8B, Qwen 2.5 7B, Mistral NeMo 12B and others6
    AbstractWebWeaver 用上下文推断拓扑。

    WebWeaver 是针对 LLM-MAS 通信拓扑机密性的推断攻击：只控制一个任意智能体，从对话上下文恢复全图，而不是查询智能体 ID。

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