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Oct 13 · Tuesday

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  1. AttacksarXiv 2610.05943

    CRIME 框架利用良性 Agent 技能组合诱发恶意行为

    提出 CRIME 框架,组合良性 Agent 技能诱发恶意行为

    Published
    Setting
    AI Agent
    Evaluated models
    DeepSeek-V4-Flash, GPT-4o-mini, GPT-4o and others6
    Abstract良性技能经 DCA 或 ACA 组合后可产生恶意环境后果,单独审查对不上。

    CRIME 把公共技能库中各自通过审查的技能配成两两组合,看联合执行能否实现指定恶意任务。。

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  2. AttacksarXiv 2609.15383

    微软团队提出 capability laundering 攻击:弱模型拆分任务向对齐前沿模型套取能力

    提出能力洗钱攻击,拆分任务向对齐模型套取能力

    Published
    Setting
    AI Agent
    Attacker
    Black-box
    Evaluated models
    GPT-5.5, Claude Opus 4.8, Grok-4.3 and others7

    Abstract作者提出了能力洗钱攻击,发现未对齐编排器分解咨询对齐模型可恢复能力差距,指出需建立跨会话防御。

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  3. AttacksarXiv 2607.03968

    The study reveals workflow-level jailbreaks in IDE programming agents: GitHub Copilot generated harmful content across four backends at 816/816

    提出工作流级越狱,让编程 Agent 在开发任务中写入有害示例

    Published
    Evaluated models
    Claude Sonnet 4.6, Claude Haiku 4.5, Gemini 3.1 Pro and others4
    Abstract作者报告 Copilot 后端会在编码工作流中生成其在单轮条件下通常拒绝的有害答案。

    这是一项生产 IDE 编码智能体的工作流越狱研究,受测对象是 Copilot 的四个模型后端,而非评测流水线中的名义目标。

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  4. AttacksarXiv 2606.09084

    研究者提出 Context-Fractured Decomposition 攻击

    提出 CFD 跨会话分解攻击,利用工件来源缺口绕过工具型 Agent 的本地检查

    Published
    Setting
    AI Agent
    Evaluated models
    GPT-4.1, GPT-5-nano, Claude-3.5-Sonnet and others6
    AbstractCFD 用无指令 artifact 把越狱拆到跨会话。

    CFD针对工具型 LLM 智能体:利用 artifact 来源不被跟踪这一部署失败模式,把有害目标拆开后延迟组合。

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  5. AttacksarXiv 2603.01414

    Jailbreaking embodied LLMs via action-level manipulation

    Propose Blindfold, jailbreaking embodied LLMs with action-level manipulation

    Published
    Evaluated models
    Llama-3.1-8B, DeepSeek-R1-14B, Gemma-3-27B and others8
    AbstractBlindfold jailbreaks embodied LLMs with action-level proxy planning, and the authors claim it can bypass semantic checks and is effective in both simulation and real-world settings.

    Blindfold is a no-box attack against embodied LLM planning modules, rewriting malicious intent into seemingly benign action sequences.

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  6. AttacksarXiv 2601.05466

    Jailbreaking large language models through reinforcement learning with iterative tool disguise attacks

    提出 iMIST,用工具伪装和 PPO 迭代越狱大语言模型

    Published
    Setting
    AI Agent
    Attacker
    Black-box
    Evaluated models
    DeepSeek-V3, Qwen3-32B, GPT-OSS-120B
    AbstractiMIST 用工具伪装和在线 PPO 做黑盒越狱,Table I 中 JADES 高于同格基线。

    iMIST是黑盒越狱方法:把恶意查询伪装成合法工具调用,再用在线强化学习把响应的有害性分数往上推。

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  7. AttacksarXiv 2509.25624

    STAC:看似无害的工具调用链如何攻破 LLM Agent

    提出 STAC 框架,把恶意目标拆成多轮看似无害的工具调用链

    Published
    Setting
    AI Agent
    Attacker
    Black-box
    Evaluated models
    GPT-4.1-2025-04-14, GPT-4.1-mini-2025-04-14, Qwen3-32B and others8

    Abstract作者提出并验证了智能体在序列化工具攻击下的普遍脆弱性,指出针对累积动作序列防御的必要性。

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