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Oct 12 · Monday

All papers

Found 5 papers
Filter3

Attack type

Prompt injection3

Impact

Harmful content7Unauthorized actions10Data and privacy leaks5Output manipulation21Availability and reliability5

System type

AI Agent3

Attack surface / entry point

User input31Web pages and interfaces3Documents and messages5Tool responses3Tool and skill descriptions5Code repositories and dependencies3Memory writes4Images, audio and video3Training data2Weights and gradients10Distribution channels6Inference services and hardware6

Layer

Application layer3
Select any value within a category; different categories must all match. Counts include the other filters you have selected.Another 233papers have no tags yet and are not included in filtered results.
Impact：Data and privacy leaksAttack surface / entry point：Web pages and interfacesAttack surface / entry point：Training dataClear all

Another 233papers do not have category tags yet and are not included in filtered results.

  1. AttacksarXiv 2610.12524

    An exploration of attacks on AI agent systems

    重测并扩展对 AI Agent 的提示注入，并用 Agent Card 欺骗操纵 A2A 选择

    arXiv
    2610.12524
    Published
    Layer
    Application layer
    Setting
    AI Agent
    Evaluated models
    Ollama Mistral 0.9.5, llama3-8b-8192, gemini-2.0-flash-lite and others5
    Abstract单智能体过滤与分类可被格式或措辞绕过，A2A 选卡还会偏向名称和描述。

    作者在自建的 LangChain、AutoGen 和 A2A 系统上重测提示注入，并改 Agent Card 看选择是否偏移。摘要称试验主要凸显单智能体弱点，同时把攻击扩到多智能体。

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  2. AttacksarXiv 2610.01365

    ReGap：无需真实隐私数据即可通过微调重新提取模型隐私关联

    提出 ReGap，用自生成伪监督微调恢复模型中的隐私关联

    arXiv
    2610.01365
    Published
    Layer
    Training and data layer
    Setting
    Models and APIs
    Attacker
    White-box, Gray-box
    Evaluated models
    GPT-2 Small, GPT-2 Medium, GPT-2 Large and others6

    Abstract提出无真实私有监督的恢复攻击 ReGap，实验显示微调可通过自生成数据唤醒模型潜在隐私关联，突显后适应隐私风险。

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  3. AttacksarXiv 2609.33985

    研究：众包微调数据投毒可放大专有指令抽取

    提出主题锚点投毒，放大众包微调后的专有指令提取

    arXiv
    2609.33985
    Published
    Layer
    Training and data layer
    Setting
    Models and APIs
    Attacker
    Black-box
    Evaluated models
    Qwen2.5-7B-Instruct, Qwen2.5-14B-Instruct, Llama-3.1-8B-Instruct and others4

    Abstract论文提出基于主题锚点的数据中毒攻击，证明低比例的中毒样本可在黑盒条件下隐蔽放大微调指令泄漏。

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  4. AttacksarXiv 2608.04741

    LoginTrap：针对 LLM Web Agent 的任务无关钓鱼式间接提示注入攻击

    提出 LoginTrap，以网页弹窗诱导 Web Agent 提交敏感信息

    arXiv
    2608.04741
    Published
    Layer
    Application layer
    Setting
    web agent
    Evaluated models
    GPT-4o, Gemini 3 Flash, Claude Sonnet 4 and others7

    Abstract揭示网络智能体在黑盒网页下的登录诱导风险，利用模糊测试生成话术并跨骨干和架构验证了隐私泄露威胁。

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  5. AttacksarXiv 2605.05509

    研究者提出面向 Agent 浏览器的 Web 威胁模型，梳理 20 类攻击并在 4 个模型上复现

    提出面向智能体浏览器的 Web 威胁模型并复现混淆攻击

    arXiv
    2605.05509
    Published
    Layer
    Application layer
    Setting
    web agent
    Evaluated models
    GPT-5, Claude-Sonnet-4.6, Kimi-k2p5 and others8
    Abstract作者提出面向智能体浏览器的 Web 威胁模型与攻击分类，测试显示传统混淆攻击可复现且能绕过现有防御。

    这篇论文研究了智能体浏览器在面临传统 Web 攻击者时的安全性问题，指出当前针对提示词注入的安全假设无法抵御基于正常 Web 交互模式的混淆攻击。

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