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Oct 12 · Monday

All papers

Found 16 papers

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  1. DefensesarXiv 2610.13733

    KVeil: First-Place Solution for the ECCV 2026 LifeGenIP Unlearnable Video Challenge

    Propose KVeil, which adds perturbations to face videos to prevent unauthorized customization from reproducing identity

    Published
    Evaluated models
    Wan2.2-TI2V-5B, HunyuanVideo-1.5, Kling 3.0 and others4

    AbstractKVeil adapts LETHE's reference-reading disruption to the challenge's two stages, ranking first on the leaderboard in both Final columns.

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  2. 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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  3. DefensesarXiv 2610.10345

    SLDR:通过选择性层恢复与动态路由防御恶意微调

    提出 SLDR,用选择性层恢复与动态路由防御恶意微调

    Published
    Attacker
    Black-box
    Evaluated models
    Llama3.1-8B-Instruct, Llama3-8B-Instruct, Qwen2.5-7B-Instruct and others4
    Abstract作者称 SLDR 能压低有害输出并保持下游效用。

    SLDR 是针对恶意微调的微调后防御:在已对齐模型上做有符号层探测,只在敏感分数最大与最小的两层训练 LoRA,再用 lmax 的最后 token 表示决定是否启用适配器。

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  4. DefensesarXiv 2610.09793

    用时序逻辑监控工具 Agent

    提出 MFOTL 离线时序验证以监控工具 Agent 的危险动作链

    Published
    Setting
    AI Agent
    Attacker
    Black-box
    Abstract形式化验证可有效识别多步攻击,但其有效性高度依赖轨迹的可信历史记录。

    这篇论文对工具调用大语言模型智能体的安全监控进行了形式化时序验证研究。

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  5. AttacksarXiv 2610.03124

    研究提出 Untag 攻击框架,使开源大模型触发标签滥用检测机制失效

    提出 UNTAG,绕过开源权重模型的 trigger-tag 滥用检测

    Published
    Evaluated models
    Llama2 (7B), Llama3 (8B), Qwen2.5 (7B)
    Abstract作者用 UNTAG 评估 trigger-tag,认为其不能充当开放权重滥用检测的主要边界。

    UNTAG 是针对开放权重 LLM 上条件滥用检测 trigger-tag 的统一攻击评估:信号可以在解码期注入,也可以写进权重,但攻击者若能改输出或改已发布权重,检测可以失效。

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  6. AttacksarXiv 2609.33985

    研究:众包微调数据投毒可放大专有指令抽取

    提出主题锚点投毒,放大众包微调后的专有指令提取

    Published
    Attacker
    Black-box
    Evaluated models
    Qwen2.5-7B-Instruct, Qwen2.5-14B-Instruct, Llama-3.1-8B-Instruct and others4

    Abstract论文提出基于主题锚点的数据中毒攻击,证明低比例的中毒样本可在黑盒条件下隐蔽放大微调指令泄漏。

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  7. DefensesarXiv 2609.02293

    SEAL:通过共享专家对齐强化 MoE 全局安全

    提出 SEAL,在 MoE 共享专家上做 DPO-LoRA 对齐以抵御越狱与权重篡改

    Published
    Evaluated models
    Qwen1.5-MoE-A2.7B, DeepSeekMoE-16B, GLM-4.7-Flash and others4
    AbstractSEAL 把 DPO-LoRA 限制在混合 MoE 共享专家上,SEAL++再保护已有安全神经元方向。

    SEAL是面向混合 MoE 的训练时防御:只对齐始终执行的共享专家,使安全不依赖路由器是否把 token 送到安全专家。

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  8. AttacksarXiv 2608.07430

    研究者提出 SN-Guided Diffusion,利用扩散大模型安全神经元实现离线越狱

    提出 SN-Guided Diffusion,利用安全神经元实现离线越狱

    Published
    Evaluated models
    Qwen2.5-7B-Instruct, LLaDA-8B-Instruct, Dream-Instruct-7B and others15
    Abstract论文揭示了扩散语言模型对自回归安全神经元的继承性,并提出纯离线黑盒越狱框架 SN-Guided Diffusion。

    论文系统评估了扩散大语言模型(DLLM)在安全对齐中的双重角色——既作为白盒攻击目标,又作为黑盒越狱生成的对抗工具。

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  9. AttacksarXiv 2607.11698

    AHA 用自动研究循环发现生产 Agent 漏洞概念

    提出 AHA 自动科研循环,发现生产 Agent 的可复用漏洞概念

    Published
    Attacker
    Black-box
    Evaluated models
    Minimax-M2.7, Kimi-K2.6, Deepseek-V4-Pro and others5
    Abstract论文提出基于可证伪科研循环的 AHA 框架,从生产级智能体中挖掘并沉淀漏洞概念图,提升攻击复用率并指导防御加固。

    AHA 是一项针对生产级 LLM 智能体自动化红队测试的研究,旨在解决传统方法仅保留具体攻击载荷而缺乏成因解释、导致跨版本复用困难且无法指导修复的问题。

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  10. AttacksarXiv 2601.05466

    Jailbreaking large language models through reinforcement learning with iterative tool disguise attacks

    提出 iMIST,用工具伪装和 PPO 迭代越狱大语言模型

    Published
    Setting
    AI Agent
    Attacker
    Black-box
    Evaluated models
    DeepSeek-V3, Qwen3-32B, GPT-OSS-120B
    AbstractiMIST 用工具伪装和在线 PPO 做黑盒越狱,Table I 中 JADES 高于同格基线。

    iMIST是黑盒越狱方法:把恶意查询伪装成合法工具调用,再用在线强化学习把响应的有害性分数往上推。

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  11. AttacksarXiv 2509.22067

    论文:激活引导可破坏 LLM 安全对齐,20 个随机向量即可构造通用越狱攻击

    提出激活转向越狱,用随机向量在推理时绕过安全拒答

    Published
    Attacker
    Black-box
    Evaluated models
    Llama3.1-8B, Llama3.1-70B, Qwen2.5-3B and others8

    Abstract作者称激活转向会系统性破坏 LLM 对齐,良性特征与随机向量均能诱发有害合规,聚合随机向量可构建通用攻击。

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