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Oct 13 · Tuesday

All papers

Found 14 papers

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  1. AttacksarXiv 2609.38253

    CollageAttack: Exploiting cross-modal alignment defects for spatial text composition jailbreaks against T2I models.

    提出 CollageAttack,用空间文本碎片重组越狱文生图模型

    Published
    Attacker
    Black-box
    Evaluated models
    GPT-Image-2, Doubao-Seedream-5.0-Lite, Wan2.7-Image-Pro and others5

    Abstract系统揭示 T2I 跨模态空间合成安全漏洞,证实离散无害元素可在图像层面重构有害意图并放大传播强度。

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  2. AttacksarXiv 2609.07216

    DIVA:利用视觉锚点对视频生成模型实施多模态越狱

    提出 DIVA,将有害意图拆成视觉锚点与运动文本以越狱视频生成模型

    Published
    Attacker
    Black-box
    Evaluated models
    Wan, CogVideoX, LTX-Video and others9
    AbstractDIVA 用视觉锚点抑制语义漂移做视频越狱,并给出多条件安全基准 TI2VSafetyBench。

    DIVA 是针对带参考图的视频生成模型的免训练 black-box 越狱:用一致性机制本身堵住语义漂移这条安全逃逸路径。。

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  3. AttacksarXiv 2606.11265

    论文提出 CRCP 投毒框架,揭示 RAG 分块与重排序下的投毒失效问题

    提出 CRCP 框架,优化分块与重排下的 RAG 语料投毒

    Published
    Evaluated models
    GPT-4o, DeepSeek-R1, Qwen3-Max and others11
    AbstractCRCP 把投毒做成多阶段一致性问题。

    CRCP 研究的是带分块和重排的 RAG 语料投毒,而不是只提高文档级检索分数。

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  4. AttacksarXiv 2606.01837

    论文提出 DSR 跨模态越狱框架:用良性输入诱导 MLLM 有害输出

    提出 DSR 跨模态越狱,用无害图文诱导 MLLM 生成有害图像

    Published
    Attacker
    Black-box
    Evaluated models
    gemini-2.5-flash-image, qwen-image-2.0, Tongyi Wanx 2.5
    AbstractDSR 用无害图文诱导商业 MLLM 输出有害图像,作者称组合能力会反过来扩大攻击面。

    DSR 是一种 black-box 跨模态越狱:输入侧不放显式有害内容,而让商业 MLLM 在推理中把无害图文重组成有害图像。

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  5. AttacksarXiv 2605.28074

    SilentRetrieval: Hijacking retrieval-augmented generation with semantically preserved adversarial data poisoning

    提出 SilentRetrieval,以语义保持对抗文档投毒劫持 RAG 检索与生成

    Published
    Evaluated models
    Llama-2-7B-Chat, Mistral-7B-Instruct-v0.2, Qwen-7B-Chat and others10
    Abstract两阶段投毒在单文档协议下兼顾检索劫持、生成操纵与近良性困惑度。

    SilentRetrieval 是针对 RAG 的两阶段语料投毒,在每查询一篇、合成目标答案的统一协议下,同时处理检索劫持、生成操纵和流畅度。

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  6. AttacksarXiv 2603.17239

    LAAF: A Systematic Red-Teaming Method and Automated Attack Framework for LPCI Vulnerabilities in Agentic LLM Systems

    Proposes LAAF, which automatically attacks LPCI vulnerabilities in agent systems in stages

    Published
    Setting
    AI Agent
    Evaluated models
    gemini-2.0-flash-001, claude-3-haiku-20240307, meta-llama/llama-3.1-70b-instruct and others5
    AbstractLAAF does LPCI red teaming with taxonomy plus stage seeding.

    The authors state that LAAF is an automated red-teaming framework built specifically for LPCI in agentic LLMs. The issue to address is that encoded, delayed, and conditionally triggered payloads can persist in memory or RAG and re-enter across sessions, whereas Garak and PyRIT do not use the previous round's breakthrough results to seed the next stage across the six stages.

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  7. AttacksarXiv 2603.07028

    Two frames suffice: a temporal attack for jailbreaking text-to-video models

    Propose TFM, using start and end frames and implicit substitution to jailbreak text-to-video models

    Published
    Attacker
    Black-box
    Evaluated models
    Pixverse V5, Hailuo 02, Kling 2.1 Master and others4
    AbstractTFM first extracts start and end frames and then performs implicit substitution.

    TFM is a strictly black-box prompt jailbreak for text-to-video that exploits the model's temporal infilling of unspecified intermediate processes.

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  8. AttacksarXiv 2602.00364

    "Someone hid it": Query-agnostic black-box attacks against LLM retrieval

    提出查询无关黑盒攻击 DQ-A,用可迁移文末后缀降低文档检索排名

    Published
    Evaluated models
    Qwen-1.5-7B-Instruct, SFR-Embedding-Mistral, E5-Mistral-7B-Instruct and others10
    AbstractDQ-A 以无查询黑盒后缀压低 LLM 检索排名,并在 BRIGHT 上比较三种基线。

    DQ-A 是一种 query-agnostic、complete black-box 的文档隐藏攻击,对象是用最后隐层相似度匹配的 LLM 检索。

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  9. AttacksarXiv 2601.15698

    Beyond Visual Safety: Jailbreaking Multimodal Large Language Models to Generate Harmful Images with Semantically Irrelevant Inputs

    提出 BVS 图文越狱,用中和拼接图和诱导提示词让模型生成有害图像

    Published
    Evaluated models
    GPT-5 (12 January 2026 release), Gemini 1.5 Flash (15 January 2026 release)
    AbstractBVS 以重建后再生成诱导有害图像。

    BVS 用图文对诱导 MLLM 生成有害图像。作者认为,相对文本越狱和单模态图像诱导,视觉生成的安全审查仍不充分。

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  10. AttacksarXiv 2507.10457

    论文提出 LPCI:针对 Agent 逻辑层与持久记忆的提示控制注入攻击

    提出 LPCI,把延迟条件载荷写入记忆与检索库以跨会话触发

    Published
    Setting
    AI Agent
    Evaluated models
    ChatGPT, Claude, LLaMA3 and others8
    Abstract作者定义 LPCI。

    作者把LPCI定义为针对智能体逻辑执行、记忆留存和工具集成的跨阶段漏洞类,而不是单次输入上的提示改写。

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