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Oct 12 · Monday

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Found 2 papers
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System type

Models and APIs71AI Agent2coding agent1

Attack surface / entry point

User input2Documents and messages0

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Prompt layer5Model layer2Application layer148
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System type：AI AgentSystem type：coding agentAttack surface / entry point：User inputAttack surface / entry point：Documents and messagesLayer：Model layerClear all

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  1. DefensesarXiv 2610.08678

    研究揭示投机解码的安全代价并提出 SecureSD 加固方法

    测量有损投机解码的安全代价，并提出 SecureSD 收紧早期验证

    arXiv
    2610.08678
    Published
    Layer
    Model layer
    Setting
    AI Agent
    Attacker
    Black-box
    Evaluated models
    Qwen3-8B, Qwen3-32B, Llama-3.1-8B-Instruct and others6
    Abstract有损推测解码的早期偏离更快抬高越狱与注入风险。

    作者研究有损推测解码在换取速度时，是否会比效用更快地损害越狱与提示注入防护，并给出按位置校正的 SecureSD。

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  2. 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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