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Oct 12 · Monday

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  1. AttacksarXiv 2610.11112

    EpiReal-Bench:商用图像生成模型虚假声明红队基准

    构建 EpiReal-Bench,评测图像生成器将虚假主张渲染为可信证据

    Published
    Attacker
    Black-box
    Evaluated models
    GPT-Image-2, Nano Banana 2, Grok Imagen 2.0 and others4
    Abstract四款商用图像模型能把假主张画成可信证据。

    EpiReal-Bench 用来量商用图像生成器会不会把虚假现实主张画成可信视觉证据。

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  2. 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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  3. 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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  4. AttacksarXiv 2609.01168

    CRACK:用多智能体辩论越狱多层安全过滤的 T2I 模型

    提出 CRACK,用多智能体辩论在黑盒下越狱文生图多层安全过滤

    Published
    Attacker
    Black-box
    Evaluated models
    Stable Diffusion v1.4, SDXL, DALL·E 3 and others4
    AbstractCRACK 以分层诊断的多智能体辩论搜索多层 T2I 过滤器的联合规避区域。

    CRACK 是面向文本生成图像模型多层安全栈的黑盒越狱框架,用几何上的 Detection Surface 解释为何粗粒度反馈不够。

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  5. 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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  6. AttacksarXiv 2603.07028

    两帧即可:针对文本到视频模型越狱的时序攻击

    提出 TFM,用起止帧与隐式替换越狱文生视频模型

    Published
    Attacker
    Black-box
    Evaluated models
    Pixverse V5, Hailuo 02, Kling 2.1 Master and others4
    AbstractTFM 先抽起止帧再做隐式替换。

    TFM 是面向文生视频的严格黑盒提示越狱,利用模型对未写明中间过程的时间补全。

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  7. 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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  8. AttacksarXiv 2503.01839

    研究者用微调大语言模型越狱带安全护栏的文生图模型

    提出 PromptTune,微调 LLM 改写提示以越狱文生图护栏

    Published
    Evaluated models
    SDXL-Turbo, MACE, SafeGen
    AbstractLLM 改写可提高过滤器绕过率。

    PromptTune 用微调 LLM 改写提示词,攻击带安全过滤器或对齐的文生图模型。

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