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Oct 13 · Tuesday

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  1. DefensesarXiv 2610.03089

    COBRA: A Dual-LLM Architecture for Defending Computer-Using Agents Against Branch-Jumping Attacks

    提出 COBRA 双 LLM 架构,防御计算机使用 Agent 的分支转向攻击

    Published
    Evaluated models
    gpt-5, UI-TARS-1.5-7B, claude-sonnet-5 and others6

    Abstract提出分支转向防御架构 COBRA,通过事前能力约束与边界代理消除分支转向攻击并兼顾效用。

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  2. DIBench:面向移动 GUI 智能体多候选选择决策完整性的安全基准

    用 DIBench 评测移动 GUI 智能体被 UI 注入后的决策完整性

    Published
    Evaluated models
    Qwen2.5-VL(32B), Qwen3-VL(32B), GUI-Owl(32B) and others7

    Abstract论文提出移动智能体决策完整性基准 DIBench,发现欺诈 UI 注入诱导目标选择并推高完成率,通用防御收益不稳定。

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  3. AgentHazard:评估计算机使用智能体有害行为的基准

    提出 AgentHazard 基准,评测计算机使用智能体的执行层有害行为

    Published
    Evaluated models
    Qwen2.5-72B-Instruct, Qwen2.5-Coder-32B-Instruct, Qwen3-32B and others12
    AbstractAgentHazard 评估了计算机使用智能体的执行安全,作者认为模型层对齐无法可靠保障智能体层面的安全性。

    AgentHazard 是针对计算机使用智能体执行层安全构建的评估基准,重点探究多步工具调用下局部合理动作累积引发的危害。

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  4. DefensesarXiv 2602.10915

    Blind Gods and Broken Screens: Building a Secure, Intent-Centric Mobile Agent Operating System

    Proposes Aura, which uses a trusted kernel to mediate the identity, perception, and action control of mobile agents

    Published
    Evaluated models
    Gemini-3-Flash
    AbstractAura mediates structured interactions via the Agent Kernel.

    Aura uses kernel-mediated structured agent interaction, replacing screen-interface mobile assistants..

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  5. MobiRed 框架测评八款移动 LLM Agent 的第三方渠道提示注入攻击

    用 MobiRed 评测移动 LLM Agent 面对第三方渠道的提示注入

    Published
    Evaluated models
    Mobile-Agent-E, AppAgent, AutoGLM and others8

    Abstract论文评估了移动 LLM 智能体作为 confused deputy 的易受攻击性,作者称非应用控制通道可诱导智能体执行多步越权危害。

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