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Oct 12 · Monday

All papers

Found 13 papers

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  1. AttacksarXiv 2609.29948

    ENDOPROMPT:用受害者侧伪参考学习降低模型任务效用的前缀

    提出 ENDOPROMPT,以受害者侧伪参考学习降低良性任务效用的前缀

    Published
    Evaluated models
    Qwen2.5-7B, Llama-3.1-8B, Mistral-7B-v0.3 and others4
    Abstract作者用受害模型续写监督良性效用攻击,并把行为位移、任务退化与请求匹配效果分开评测。

    ENDOPROMPT 是一种用受害模型自身续写监督前缀生成的 white-box 效用攻击方法。它针对良性任务失败,不要求产生有害内容或明确拒答。

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  2. AttacksarXiv 2609.28585

    论文提出持久计费状态概念,揭示工具调用 LLM Agent 的拒绝钱包攻击与防御

    定义工具调用 Agent 的持久计费状态,提出拒绝钱包攻击与防御

    Published
    Setting
    AI Agent
    Evaluated models
    GPT-4o, GPT-4o-mini, Mistral-Large and others7
    Abstract已准入工具返回的跨轮保留会重复计费。

    这篇工作把工具调用智能体里跨轮保留、并被提供商反复计费的外部工具返回定义为 persistent billable state,并把它的主机侧再次送入决定当作控制点。。

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  3. AttacksarXiv 2608.12273

    研究者提出 Convergent Detour Hijacking 攻击,可让技能型 LLM Agent 绕路并放大资源消耗

    提出 CDH 攻击,让技能型 Agent 绕路放大资源消耗

    Published
    Setting
    AI Agent
    Evaluated models
    Claude-Haiku-4.5, DeepSeek-V4-Pro, DeepSeek-V4-Flash and others6
    AbstractCDH 让静态技能在保持任务完成时拉高调用与 token,耗时则因后端而异。

    CDH 是针对渐进披露技能智能体的发布者侧、纯文本攻击:一个静态协调器把本可正确完成的任务,拐进有界但更耗资源的技能绕路,再交还原任务。

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  4. AttacksarXiv 2605.13338

    研究者提出层级遗传算法黑盒攻击,诱导推理模型过度思考

    提出层级遗传算法 HGA,扰动题目逻辑结构诱发推理模型过度思考

    Published
    Attacker
    Black-box
    Evaluated models
    DeepSeek-R1 (671B), Qwen3-Thinking, GPT-o3 and others5

    AbstractHGA 在黑盒推理模型上用逻辑扰动拉长输出,作者称可从小代理迁移,查询成本是其局限。

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  5. 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 red-teams three types of voice agents: query-based access eliminates authentication and leakage successes, but behavioral attacks remain.

    Aegis uses multi-turn red-teaming evaluation on ALLM voice agents already integrated into business systems. The authors call this the first systematic red-teaming framework in this setting.

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  6. AttacksarXiv 2505.23266

    AdvOF:用对抗物体融合攻击 VLM 驱动的视觉语言导航智能体

    提出 AdvOF,生成对抗物体误导视觉语言导航智能体的场景感知

    Published
    Attacker
    White-box
    Evaluated models
    Lseg, Clip, ViT-L/16 and others5
    AbstractAdvOF 以多视角融合生成对抗物体。

    AdvOF 是针对 VLM 驱动 VLN 服务导航的对抗物体攻击。

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