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Oct 13 · Tuesday

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Found 2 papers
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Attack surface / entry point

User input110Web pages and interfaces19Documents and messages16Tool responses19Tool and skill descriptions8Code repositories and dependencies2Retrieval corpus27Memory writes4Images, audio and video119Training data15Weights and gradients12Distribution channels12

System component

Memory3RAG1Guardrails and judges4Monitors1Reasoning chains3Permissions and sandboxing6Multimodal0
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Attack surface / entry point：Code repositories and dependenciesSystem component：RAGSystem component：MonitorsSystem component：MultimodalClear all

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  1. DefensesarXiv 2609.35659

    Tracekit: A tamper-proof intent-reasoning-action audit system for autonomous coding agents

    提出 Tracekit，审计编码 Agent 的意图、推理与动作并检测账本篡改

    arXiv
    2609.35659
    Published
    Layer
    Application layer
    Setting
    coding agent
    Evaluated models
    Claude Code (claude -p, version 2.1), 独立评审（同一 CLI，无工具）
    AbstractTracekit 把意图、自述和动作写入可锚定的哈希链。

    Tracekit 是无第三方依赖的编码智能体审计层：把人类请求、模型自述和已执行动作并排写入可外部锚定的哈希链，执行前用正则门，事后用规则和独立模型互查。

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  2. AttacksarXiv 2609.02774

    CodePoisonRAG：针对检索增强代码生成的知识投毒攻击

    提出 CodePoisonRAG，对检索增强代码生成的知识库投毒以植入漏洞

    arXiv
    2609.02774
    Published
    Layer
    Application layer
    Setting
    LLM applications
    Evaluated models
    Qwen 3.5 9B, Code Llama 13B, DeepSeek-Coder-V2 16B

    AbstractCodePoisonRAG 展示了 RACG 外部知识库的新攻击面，在较低投毒率下可定向诱发指定漏洞并部分抵御防御。

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