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Oct 12 · Monday

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  1. AttacksarXiv 2604.01039

    评估与加固 LLM 系统指令以抵御编码攻击提取

    用编码与结构化请求抽取系统指令,并用 CoT 改写加固

    Published
    Attacker
    Black-box
    Evaluated models
    GPT-4.1-mini, GPT-3.5-turbo, Gemini-2.5-flash and others7
    Abstract编码式请求可在直接拒答后引出系统指令。

    这项工作评测并加固 LLM 系统指令在编码式抽取下的保密性。作者关心的是:直接抽取已被拒绝时,把同一请求改写成格式化或编码任务,模型是否仍交出受保护内容。

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  2. AttacksarXiv 2602.07379

    Aegis: Governance, Integrity, and Security for AI Voice Agents

    提出 Aegis 红队框架,多轮攻击高风险语音 Agent

    Published
    Setting
    AI Agent
    Evaluated models
    GPT-4o, GPT-4o-mini, Gemini-1.5 Pro and others7
    AbstractAegis 红队评测三类语音智能体:查询式访问消掉认证与泄密成功,行为类攻击仍在。

    Aegis 用多轮红队评测已接入业务系统的 ALLM 语音智能体。作者称这是该设定下的 the first systematic red-teaming framework。

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