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Oct 13 · Tuesday

All papers

Found 5 papers
Filter4

Attack type

Jailbreaks19Prompt injection81Poisoning and backdoors55Extraction and theft5Detection evasion7Denial of service5

Impact

Data and privacy leaks4

System type

Models and APIs29LLM applications7AI Agent5coding agent1Embodied systems and robotics0

Attack surface / entry point

User input4

Layer

Application layer4
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.
Attack type：Extraction and theftSystem type：AI AgentSystem type：coding agentSystem type：Embodied systems and roboticsClear all

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

  1. AttacksarXiv 2609.09865

    CGMIA：用成员推理攻击检测代码生成基准的数据泄漏

    提出 CGMIA，检测代码生成基准样本是否泄漏进训练集

    arXiv
    2609.09865
    Published
    Layer
    Model layer
    Setting
    coding agent
    Attacker
    Gray-box
    Evaluated models
    Qwen2.5-Coder (3B), CodeGemma (2B), DeepSeek-Coder (1.3B) and others5
    AbstractCGMIA 融合相似度、通过率、困惑度与 CodeBERT，在模拟泄漏上优于八个 MIA 基线。

    CGMIA 用成员推断检测代码生成基准是否泄入 LLM 训练集，使评测不依赖对训练语料的直接访问。

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  2. AttacksarXiv 2608.04192

    研究者提出 SkillClone，仅凭正常提问即可克隆 LLM Agent 隐藏技能功能

    提出 SkillClone，仅凭良性任务交互重构闭源 Agent 技能

    arXiv
    2608.04192
    Published
    Layer
    Application layer
    Setting
    AI Agent
    Attacker
    Black-box
    Evaluated models
    DeepSeek-Flash, DeepSeek-Pro, GLM-5.1 and others5
    Abstract论文揭示了仅靠良性任务交互即可重构闭源智能体技能隐藏功能的风险，表明功能保密需要限制累积信息泄露。

    论文从功能保密视角系统研究了大语言模型智能体技能的行为重构威胁。

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  3. AttacksarXiv 2607.25560

    SigLeak 可从执行轨迹推断专有 Agent 技能

    提出 SigLeak，从黑盒 Agent 执行轨迹推断专有技能

    arXiv
    2607.25560
    Published
    Layer
    Application layer
    Setting
    AI Agent
    Attacker
    Black-box
    Evaluated models
    GPT-5.4-mini, GPT-5.5, GLM-5.2 and others4

    Abstract提出了通过良性查询和对照轨迹推断黑盒专有技能的 SigLeak 框架，揭示了智能体执行可见性带来的行为侧信道泄露风险。

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  4. AttacksarXiv 2603.11132

    WebWeaver: Breaking the topology confidentiality of LLM multi-agent systems via covert context inference

    Propose WebWeaver, which compromises only a single agent and recovers the multi-agent communication topology from conversation context.

    arXiv
    2603.11132
    Published
    Layer
    Application layer
    Setting
    Multi-agent systems
    Evaluated models
    Llama 3.1 8B, Qwen 2.5 7B, Mistral NeMo 12B and others6
    AbstractWebWeaver infers topology from context.

    WebWeaver is an inference attack against the confidentiality of LLM-MAS communication topology: it controls only one arbitrary agent and recovers the full graph from dialogue context, rather than querying agent IDs.

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  5. AttacksarXiv 2602.07379

    Aegis: Governance, Integrity, and Security for AI Voice Agents

    Proposes the Aegis red-teaming framework for multi-turn attacks on high-risk voice agents.

    arXiv
    2602.07379
    Published
    Layer
    Application layer
    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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