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Oct 13 · Tuesday

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  1. Attention sees, MLP refuses: tracing the safety pathway from attention to MLP in LLMs

    Trace attention to identify harmfulness to the MLP refusal write pathway and propose Sentinel

    Published
    Evaluated models
    Llama-3.1-8B-Instruct, Qwen2.5-7B-Instruct, Qwen3-8B-Instruct and others18
    AbstractAttention updates are more readable for harmfulness, MLP updates write refusal, and Sentinel routes alerts using two-path signals.

    The authors reframe jailbreaking and excessive refusal of aligned models as a pathway problem on the residual stream from recognition to writing, and accordingly provide conditional reminders before decoding.

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  2. Study: legal reasoning models citing legal provisions does not equal relying on legal provisions.

    Uses premise permutation and hidden-layer tracing to audit whether legal chain-of-thought truly relies on the cited legal provisions.

    Published
    Evaluated models
    Qwen3-8B, Qwen3-14B, Llama-3.1-8B and others7
    AbstractUsing counterfactual substitution of authorities and internal commitment tracing, the authors find that legal CoT rulings depend on authorities only to a limited extent and are vulnerable to prompt injection manipulation.

    This study conducts an empirical audit of the causal truthfulness of legal citations in chain-of-thought reasoning of large language models in the legal domain.

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  3. 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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  4. PatchBench 提出激活补丁局部评测协议,揭示越狱修复的附带损伤

    提出 PatchBench-Local 协议,评测激活补丁修复越狱的局部附带损伤

    Published
    Evaluated models
    Qwen2.5-3B-Instruct, Qwen2.5-14B-Instruct, gemma-3-4b-it and others8

    Abstract论文提出 PatchBench 与局部评估协议,揭示了激活补丁在全局能力无损下仍存局部良性退化。

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  5. DefensesarXiv 2610.09703

    研究揭示 Token-Pruning 对 VLM 安全性的影响并提出 SAP 缓解机制

    提出 Safety-Aware Pruning,缓解视觉 token 剪枝放大的多模态越狱

    Published
    Attacker
    Black-box
    Evaluated models
    LLaVA-1.5-7B
    Abstract剪枝去掉背景 token 后注意力塌向恶意前景。

    这篇工作评估视觉 token 剪枝如何改变 VLM 在多模态越狱下的行为,并给出推理时防御 SAP。

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  6. DefensesarXiv 2610.09167

    Persist-3 用顺序检验识别未见越狱来源,提升 MTK 与 Prompt Guard 2 防御效果

    提出 Persist-3 序贯检验,从隐藏表示识别未见越狱源

    Published
    Evaluated models
    Llama2-7B-chat, Qwen2.5-7B-Instruct, Gemma-2-9B-it and others4
    AbstractPersist-3 用有限窗口检验攻击流是否超出已知越狱源,检出率低于全历史 SR-DKW,但决策只依赖最近观测。

    Persist-3 是一个有限记忆的序贯检测器,用来判断攻击表示流是否已经不能由任何一个已知越狱源解释。。

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  7. DefensesarXiv 2610.08316

    MARCO:面向蛋白质生成模型的放射性水印框架

    提出 MARCO 放射性水印,冻结蛋白质生成模型并在去噪时嵌入签名

    Published
    Attacker
    Black-box
    Evaluated models
    RFdiffusion, ESMFold, Chroma and others6
    AbstractMARCO 在冻结的 PGM 上去噪时嵌构象水印,作者称能兼顾保真与抗扰动,并使盗版模型继承水印。

    MARCO 是加在蛋白质生成模型推理过程上的构象水印,用来标记知识产权,并为可能的生物安全滥用保留可追溯信号。作者还把它说成数字权利管理工具,以及符合生物武器公约的数字监管链。问题在于:专有 PGM 的三维输出可能被拿去训练盗版模型,也可能在来源被抹掉后绕过筛查。

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  8. DefensesarXiv 2610.07276

    SAFESHIELD:小语言模型部署时安全的决策组织框架

    提出 SAFESHIELD,组织小语言模型部署时的安全决策

    Published
    Evaluated models
    Qwen3-4B-Instruct
    AbstractSAFESHIELD 用可审计决策轨迹组织 SLM 部署时的四项安全决策,并报告协调依赖影响端到端结果。

    SAFESHIELD 是面向小语言模型的部署时安全框架,把运行时安全从单项审核改写成可检查的决策过程。

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  9. AttacksarXiv 2610.06670

    研究者提出 Reward Stealing Attack,从对齐模型行为反推安全奖励实施攻击

    提出 ReSA,从对齐模型行为恢复安全奖励并在解码时反转

    Published
    Evaluated models
    Llama3.1-8B-Instruct, Gemma-7B-Instruct, Qwen2.5-7B-Instruct and others9
    AbstractReSA 用最大熵 IRL 从对齐模型行为恢复代理安全奖励,并在解码时反转以诱导有害输出。

    ReSA 是一种对抗攻击:从对齐模型的可观察行为恢复代理安全奖励,再在解码时把该奖励反过来用。。

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  10. AttacksarXiv 2610.04985

    研究揭示 Jev 作为应用决策层的安全与隐私风险

    评估应用决策层的输入注入与隐私推断风险

    Published
    Evaluated models
    Jev, NanoJev
    AbstractJev 的类型化决策可被输入与训练操纵,也会泄露信息,并同时支持检测与滥用。

    Jev 是 TypeSafe 的 System One 模型,把应用 state 和固定问题变成 Choice、Noul 或 Score 的类型化决策与概率。作者用官方 API 和可改训练的 NanoJev,考察它作为决策层时的操纵、泄露与双重用途。

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  11. DefensesarXiv 2610.04412

    论文研究 LLM 数字孪生参与增强民主时的提示注入脆弱性

    提出检测、结构化与 GSPO 流程,降低共识生成的提示注入错位

    Published
    Evaluated models
    LLaMA-2 7B, LLaMA-3 8B, GPT 3.5 Turbo and others14
    Abstract三章依次做个体偏好预测、政党知识图谱审议,以及共识生成对提示注入的脆弱性与一条防御流程。

    这是一篇把 LLM 数字孪生放进增强民主的博士论文,分个体表示、政党聚合和共识生成的提示注入三章。

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  12. DefensesarXiv 2610.03502

    研究者提出可认证机制编辑:在连续输入区域上证明技能移除与保留

    提出机理编辑形式化认证,证明连续输入区域上的技能移除与保留

    Published
    Evaluated models
    Toy MLP (separated), Toy MLP (entangled), Deep MLP (3-12-8-2) and others6

    Abstract提出机理编辑形式化认证框架,证明编辑在连续区域生效且黑盒测试无法保证移除,为安全编辑提供数学证明。

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  13. 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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  14. DefensesarXiv 2610.02413

    研究:分类后缀可提升激活探针的分布外恶意输入检测

    用分类后缀提升激活探针对分布外恶意输入的检测

    Published
    Evaluated models
    Llama-3.1-8B, Qwen3.5-9B, Gemma-4-12B
    Abstract作者称排序增益来自分类格式,低 FPR 精度来自点名准则。

    用户轮后的分类后缀,被作者用作激活探针的分布外检测干预:排序看格式,低 FPR 精度看是否点名恶意/良性。

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