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Oct 13 · Tuesday

All papers

Found 5 papers
Filter4

Attack type

Prompt injection3

Impact

Harmful content8Unauthorized actions103Data and privacy leaks21Output manipulation52Availability and reliability5Oversight failure6

System type

AI Agent5

Attack surface / entry point

User input9Web pages and interfaces3Documents and messages1Tool responses2Tool and skill descriptions3Images, audio and video5Training data7Weights and gradients3Distribution channels4

Layer

Application layer5
Select any value within a category; different categories must all match. Counts include the other filters you have selected.Another 213papers have no tags yet and are not included in filtered results.
Impact：Availability and reliabilityAttack surface / entry point：Web pages and interfacesAttack surface / entry point：Documents and messagesAttack surface / entry point：Tool responsesClear all

Another 213papers do not have category tags yet and are not included in filtered results.

  2. Evaluation and benchmarksarXiv 2610.03448

    Study retests 15 prompt injection detectors: benchmark scores poorly predict agent deployment performance

    重测提示注入检测器在 Agent 工具输出上的检出与任务阻断

    arXiv
    2610.03448
    Published
    Layer
    Application layer
    Setting
    AI Agent
    Evaluated models
    Horizon-Labs, Wolf Defender, Prismor-1.5B and others15

    Abstract论文揭示公开基准无法反映智能体检测器表现，检测能力源于输入格式相似而非通用防御，建议基于工具输出与低误报评测。

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  3. 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

    arXiv
    2609.28585
    Published
    Layer
    Application layer
    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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  4. Evaluation and benchmarksarXiv 2609.19140

    AgentLSD：在对抗性任务污染下评测 AI 安全 Agent

    评测安全 Agent 在对抗性任务污染下的解题成功与开销

    arXiv
    2609.19140
    Published
    Layer
    Application layer
    Setting
    web agent
    Evaluated models
    Gemma-4 31B, DeepSeek-V4 Flash, GPT-OSS 120B and others6
    AbstractAgentLSD 用配对 web CTF 表明，欺骗性环境证据会改变安全智能体的解题率与工作量。

    AgentLSD 是一个对照框架，用来测量安全智能体在任务本身不变时，对对抗性任务污染的反应。

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