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Oct 13 · Tuesday

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Attack surface / entry point

User input98Web pages and interfaces19Documents and messages26Tool responses24Tool and skill descriptions14Code repositories and dependencies7Retrieval corpus8Memory writes11Inter-agent messages8Images, audio and video23Training data6Weights and gradients3Distribution channels9
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Attack surface / entry point：Weights and gradientsClear all

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  1. Evaluation and benchmarksarXiv 2609.08901

    论文揭示 BatchNorm 架构下机器遗忘评测的归一化伪影

    诊断 BatchNorm 架构下机器遗忘评测的归一化伪影

    arXiv
    2609.08901
    Published
    Layer
    Model layer
    Setting
    Models and APIs
    Evaluated models
    ResNet-18, ResNet-50, ViT-S/16 and others4
    Abstract一次不改权重的 BN 重校准能翻转多数方法的表面遗忘，但不改变权重里的编码器泄露。

    BN illusion 是作者对近似机器遗忘评测中一种 BatchNorm 测量伪影的命名：不改权重、只用 retain 数据重算运行统计，就可以把表面遗忘准确率翻过来。

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  2. Evaluation and benchmarksarXiv 2608.06862

    SynChain：诱导计算机使用 Agent 自建攻击链并跨任务持久化

    提出 SYNCHAIN，诱导计算机使用 Agent 自建跨任务持久攻击链

    arXiv
    2608.06862
    Published
    Layer
    Application layer
    Setting
    Browser and computer use, coding agent
    Evaluated models
    Qwen3.5-9B, Llama-3.1-8B, Ministral-3-8B

    Abstract论文揭示了 CUA 自合成工件带来的内部供应链威胁，验证了潜伏载荷的跨任务传播能力与防御局限。

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  3. Evaluation and benchmarksarXiv 2605.14605

    Study: malicious fine-tuning defenses fail under continued training, harmfulness rises across all 72 defense trajectories

    用代价曲线评估恶意微调防御在持续训练下的衰减

    arXiv
    2605.14605
    Published
    Layer
    Training and data layer
    Setting
    Models and APIs
    Evaluated models
    Llama-2-7B-chat, Qwen3-8B, Llama-3.1-8B-Instruct and others8

    Abstract论文指出恶意微调防御在持续训练下均会衰减，表明基于有限攻击者假设的防御无法为开源模型提供持久保护。

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