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Oct 13 · Tuesday

All papers

Found 8 papers
Filter5

Attack type

Jailbreaks3Prompt injection82Poisoning and backdoors20Extraction and theft1Detection evasion4Malicious use3

Impact

Unauthorized actions4

System type

AI Agent5coding agent3

Attacker access

Black-box3

Attack surface / entry point

User input102Web pages and interfaces4Documents and messages14Tool responses6Tool and skill descriptions6Code repositories and dependencies4Retrieval corpus3Inter-agent messages4Images, audio and video36Training data12Weights and gradients16Distribution channels3Inference services and hardware11

Layer

Application layer7
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Attack type：Extraction and theftAttack type：Detection evasionAttack type：Malicious useAttack surface / entry point：Web pages and interfacesAttack surface / entry point：Code repositories and dependenciesClear all

Another 215papers do not have category tags yet and are not included in filtered results.

  1. DefensesarXiv 2610.09793

    用时序逻辑监控工具 Agent

    提出 MFOTL 离线时序验证以监控工具 Agent 的危险动作链

    arXiv
    2610.09793
    Published
    Layer
    Application layer
    Setting
    AI Agent
    Attacker
    Black-box
    Abstract形式化验证可有效识别多步攻击，但其有效性高度依赖轨迹的可信历史记录。

    这篇论文对工具调用大语言模型智能体的安全监控进行了形式化时序验证研究。

    Paper analysisRead analysis
  3. AttacksarXiv 2610.01768

    LLMLeak：借 LLM 合法网页抓取实施隐蔽数据外泄

    提出 LLMLeak，借合法网页抓取把 URL 中的秘密隐蔽外传

    arXiv
    2610.01768
    Published
    Layer
    Application layer
    Setting
    coding agent
    Evaluated models
    Meta-Llama-3.3-70B-Instruct, Meta-Llama-4-Scout-17B-16E-Instruct, Meta-Llama-3.1-8B-Instruct and others18
    Abstract作者称第三方外传可发生于正常网页获取，防护需考虑工具请求而不只考虑提示注入。

    LLMLeak 是利用网页获取请求携带预先编码秘密的隐蔽通道攻击。它关注恶意软件已能读取数据、却因网络限制或监控无法直接外传的情形。

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  4. AttacksarXiv 2608.09867

    Researchers steal proprietary LLM inference chains via cross-model compatibility of encrypted inference blocks

    利用加密思维块的跨模型重放，诱导弱模型逐字转写专有推理链

    arXiv
    2608.09867
    Published
    Layer
    Prompt layer
    Setting
    Models and APIs
    Attacker
    Black-box
    Evaluated models
    Claude Opus 4.8, Claude Sonnet 4.6, Claude Haiku 4.5 and others13

    Abstract论文揭示了客户端加密思维块跨模型互换漏洞，提出了低成本提取方法并给出防御方案。

    Paper analysisRead analysis
  5. DefensesarXiv 2608.06422

    CMU 研究：分片判断可避免 LLM 监督失效并抵御对抗利用

    提出分片监督，将评判标准分配给独立调用以抵御展示攻击

    arXiv
    2608.06422
    Published
    Layer
    Application layer
    Setting
    LLM applications
    Attacker
    Black-box
    Evaluated models
    Claude Opus 4.8, Claude Sonnet 4.6, Claude Opus 4.6 and others4
    Abstract论文揭示决策负载是大模型监督的独立瓶颈，提出分片与辩论机制有效分离注意力与平衡证据，在多项高难度基准上实现稳健评判。

    本文系统研究了大语言模型在执行多标准监督与评判时的决策负载瓶颈及其安全风险。

    Paper analysisRead analysis
  6. DefensesarXiv 2607.13716

    CAVA：面向智能体 AI 运行时治理的规范动作验证与证明

    提出 CAVA，将异构智能体运行时事件规范为可哈希动作并绑定审批与回执

    arXiv
    2607.13716
    Published
    Layer
    Application layer
    Setting
    AI Agent
    AbstractCAVA 用规范动作指纹承接异构运行时治理。

    CAVA 是给异构智能体运行时用的动作语义层，用来回答“被批准和被审计的到底是哪一个动作”。

    Paper analysisRead analysis
  7. Evaluation and benchmarksarXiv 2604.02947

    AgentHazard：评估计算机使用智能体有害行为的基准

    提出 AgentHazard 基准，评测计算机使用智能体的执行层有害行为

    arXiv
    2604.02947
    Published
    Layer
    Application layer
    Setting
    Browser and computer use, coding agent
    Evaluated models
    Qwen2.5-72B-Instruct, Qwen2.5-Coder-32B-Instruct, Qwen3-32B and others12
    AbstractAgentHazard 评估了计算机使用智能体的执行安全，作者认为模型层对齐无法可靠保障智能体层面的安全性。

    AgentHazard 是针对计算机使用智能体执行层安全构建的评估基准，重点探究多步工具调用下局部合理动作累积引发的危害。

    Paper analysisRead analysis
  8. AttacksarXiv 2602.05484

    Masked Mirror: Covert Prompt Injection Attacks Against LLM-Based Phishing Detection

    提出隐蔽提示注入攻击 LLM 钓鱼检测器，并给出防御 InjectDefuser

    arXiv
    2602.05484
    Published
    Layer
    Application layer
    Setting
    LLM applications
    Evaluated models
    OpenAI GPT-5, xAI Grok 4 Fast (Non-Reasoning), Meta Llama 4 Maverick and others4
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