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Oct 12 · Monday

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Found 3 papers
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System type

Models and APIs5AI Agent15coding agent5Multi-agent systems3

Attack surface / entry point

User input5Documents and messages3Tool and skill descriptions2Inter-agent messages7Training data1

Layer

Application layer3
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System type：Multi-agent systemsAttack surface / entry point：Tool and skill descriptionsAttack surface / entry point：Training dataClear all

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  1. Evaluation and benchmarksarXiv 2609.32635

    TrustFork：显示身份如何劫持 LLM 智能体编排的权限

    提出 TRUSTFORK 基准，评测展示身份劫持多智能体编排权限

    arXiv
    2609.32635
    Published
    Layer
    Application layer
    Setting
    Multi-agent systems, coding agent
    Evaluated models
    GPT-5.6-Sol, GPT-5.6-Luna, Kimi-K3 and others8

    Abstract论文提出了多智能体安全基准 TRUSTFORK，揭示展示身份如何劫持操作权威，并证明事后验证无法弥补已发生的执行破坏。

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  2. Evaluation and benchmarksarXiv 2609.24662

    DUMA-Bench：评估 LLM Agent 安全的双控多智能体基准

    提出双控多智能体基准 DUMA-Bench，测量对抗环境下的策略违反

    arXiv
    2609.24662
    Published
    Layer
    Application layer
    Setting
    Multi-agent systems
    Evaluated models
    GPT-5, GPT-5-mini, GPT-5-nano and others14
    AbstractDUMA-Bench 用双控交互评测智能体安全。

    DUMA-Bench 把 τ²-bench 的双控交互做成智能体安全评测，用来看策略违反如何随用户、模型和环境一起出现。

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