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Oct 12 · Monday

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  1. AttacksarXiv 2610.12292

    The paper proposes an option channel attack: changing one option label can make an agent guardrail allow a prohibited operation

    Proposing an option channel attack that renames option labels so that agent guardrails allow prohibited operations

    Published
    Attacker
    Black-box
    Evaluated models
    LAYA-TD, LAYA-EN, LAYA-ML and others5

    AbstractThe authors' evaluation indicates that typed models should not serve as final safety arbiters; they are susceptible to off-policy text and option name manipulation, and confidence filtering cannot resist attacks.

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  2. DefensesarXiv 2610.02432

    论文提出 LLM 输入扰动鲁棒性度量,并发布 ASA 攻击与 AttestMCP 防护

    提出 ASA 与 AttestMCP,度量并降低 LLM 对输入序列扰动的敏感

    Published
    Attacker
    Black-box
    Evaluated models
    Gemma-3-27B-Instruct, Gemma-3-4B-Instruct, Llama-3.2-3B-Instruct and others12
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  3. DefensesarXiv 2608.12361

    基于搜索增强 LLM 的中文新词毒性共识检测框架 SeTox

    提出 SeTox 检索增强框架,检测中文新词的隐性毒性

    Published
    Evaluated models
    SeTox-Qwen2.5-7B
    AbstractSeTox 用检索把公共共识接入静态 LLM,以检测中文毒性新词。

    SeTox 研究中文新词上的隐性毒性检测:词表加检索增强,使静态 LLM 在不重训练的情况下利用公开网页上下文。

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  4. AttacksarXiv 2606.09700

    研究者提出 HPAA 攻击:用排版视觉线索绕过 13 个内容审核系统

    提出 HPAA 攻击,用排版视觉线索绕过内容审核系统

    Published
    Attacker
    Black-box
    Evaluated models
    Llama-Guard-3-8B, Perspective API, ShieldGemma-2B and others13
    Abstract揭示了排版视觉线索与分词差异带来的审核盲区,HPAA 以极低查询实现近乎完全规避。

    这篇论文研究了人类视觉感知与大模型分词处理机制之间的差异所导致的内容审核漏洞。

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  5. AttacksarXiv 2605.26156

    BITE:用上下文赌博机操纵风格偏置攻击 LLM 评委

    提出 BITE,用上下文赌博机选择风格修改抬高 LLM 评委打分

    Published
    Attacker
    Black-box
    Evaluated models
    o3-mini, Gemini-2.5-Flash, Llama-3.3-70B-Instruct and others8
    AbstractBITE 用黑盒赌博机利用风格偏差抬分,作者称这对 LLM-as-a-judge 构成威胁。

    BITE 是黑盒风格操纵:在保持答案语义的同时,抬高 LLM 评审给出的分数。

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  6. DefensesarXiv 2601.19051

    用 HASTE 主动加固 LLM 防御

    提出 HASTE,挖掘 hard negative 再训练恶意提示检测器

    Published
    Evaluated models
    protectai/deberta-v3-base-prompt-injection
    AbstractHASTE 用 hard negative 再训练检测器。

    HASTE 是检测器侧的闭环硬化框架:持续构造能绕过当前检测的对抗提示,再用来更新恶意提示分类器。

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