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Attack surface / entry point：User input Layer：Prompt layer System component：Multimodal Clear all

Another 265papers do not have category tags yet and are not included in filtered results.

Evaluation and benchmarksarXiv 2610.11112Oct 8
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
arXiv
2610.11112
Published
Oct 8
Layer
Prompt layer
Setting
Models and APIs
Attacker
Black-box
Evaluated models
GPT-Image-2, Nano Banana 2, Grok Imagen 2.0 and others4
- AttacksJailbreaks
- ComponentImage generation
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。
Paper analysisRead analysis
Analysis and theoryarXiv 2610.07009Oct 4
研究受控拆解图像到文本越狱中图像属性的作用
固定有害指令，单轴归因图像到文本越狱的图像属性
arXiv
2610.07009
Published
Oct 4
Layer
Prompt layer
Setting
Models and APIs
Evaluated models
GPT-4o, Claude Sonnet 4.5, Qwen3-VL-8B-Instruct and others6
- AttacksJailbreaks
- ComponentVision
Abstract固定文本的图像越狱拆解，只在 Qwen 上给出一条有界相关性归因。
Paper analysisRead analysis
AttacksarXiv 2609.38899Sep 30
SceneJail: Jailbreaking multimodal large models using video scene context
提出 SceneJail，利用视频情境上下文越狱视频多模态模型
arXiv
2609.38899
Published
Sep 30
Layer
Prompt layer
Setting
Models and APIs
Attacker
Black-box
Evaluated models
Qwen2.5-VL-7B-Instruct, Qwen2.5-VL-32B-Instruct, Qwen3-VL-8B-Instruct and others8
- AttacksJailbreaks
- TechniqueCross-modal payloads
- ComponentVideo
Paper analysisRead analysis
AttacksarXiv 2609.38253Sep 29
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
arXiv
2609.38253
Published
Sep 29
Layer
Prompt layer
Setting
Models and APIs
Attacker
Black-box
Evaluated models
GPT-Image-2, Doubao-Seedream-5.0-Lite, Wan2.7-Image-Pro and others5
- AttacksJailbreaks
- TechniqueEncoding and obfuscation
- ComponentImage generation
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。
Paper analysisRead analysis
DefensesarXiv 2609.36562Sep 29
ThinkingGuard：通过逐步风险归因解码多模态大语言模型中的隐式危害
构建 TriggerBench 并训练 ThinkingGuard，检测图文隐式风险
arXiv
2609.36562
Published
Sep 29
Layer
Prompt layer
Setting
Models and APIs
Evaluated models
ThinkingGuard（Qwen3-VL-8B-Instruct）
- DefensesDetection and filtering
- AttacksJailbreaks
- ComponentGuardrails and judges
AbstractTriggerBench 隔离触发条件，ThinkingGuard 用分步归因在隐式风险检测上取得作者报告的较高平均分。
这篇工作研究多模态隐式风险检测：图文各自良性，风险只在关键元素与触发元素交互时出现。
Paper analysisRead analysis
AttacksarXiv 2609.34920Sep 28
RISE：用迭代策略演化对现代文生图模型做红队测试
提出 RISE，迭代演化可复用策略对文生图模型做红队
arXiv
2609.34920
Published
Sep 28
Layer
Prompt layer
Setting
Models and APIs
Attacker
Black-box
Evaluated models
DALL·E 3, Nano Banana 2, GPT-Image-2 and others7
- AttacksJailbreaks
- TechniqueAutomated search
- ComponentImage generation
Paper analysisRead analysis
AttacksarXiv 2609.31032Sep 25
TempQ-Jail：面向文生视频越狱的查询受限候选排序方法
提出 TempQ-Jail，以查询受限候选排序越狱文生视频模型
arXiv
2609.31032
Published
Sep 25
Layer
Prompt layer
Setting
Models and APIs
- AttacksJailbreaks
- ComponentImage generation
Abstract待补读全文。
待补读全文。
Paper analysisRead analysis
DefensesarXiv 2609.10613Sep 8
后验重加权框架解释并缓解多模态大模型上下文越狱
用后验重加权解释多模态上下文越狱，并提出风险门控的良性示例注入防御
arXiv
2609.10613
Published
Sep 8
Layer
Prompt layer
Setting
Models and APIs
Evaluated models
Qwen3-VL-2B, Qwen3-VL-4B, Qwen3-VL-8B and others8
- DefensesInstruction–data separation
- AttacksJailbreaks
- ComponentVision
Abstract后验重加权解释上下文越狱的缩放，并支持风险门控的良性示例防御。
Zhang 等把多模态 ICL 越狱写成对齐模型在安全与有害隐模式之间的推理时后验漂移，并据此做风险门控防御。
Paper analysisRead analysis
AttacksarXiv 2609.07216Sep 7
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
arXiv
2609.07216
Published
Sep 7
Layer
Prompt layer
Setting
Models and APIs
Attacker
Black-box
Evaluated models
Wan, CogVideoX, LTX-Video and others9
- AttacksJailbreaks
- TechniqueCross-modal payloads
- ComponentImage generation
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。。
Paper analysisRead analysis
AttacksarXiv 2609.06094Sep 5
AdvPIE：面向文生图模型隐式漏洞的自动红队框架
提出 AdvPIE，在黑盒下搜索表面无害却生成有害图像的提示
arXiv
2609.06094
Published
Sep 5
Layer
Prompt layer
Setting
Models and APIs
Attacker
Black-box
Evaluated models
Stable Diffusion 3.5 Large, FLUX.1-schnell, Safe-StableDiffusion 1.5 and others5
- AttacksJailbreaks
- TechniqueAutomated search
- ComponentImage generation
Paper analysisRead analysis
Evaluation and benchmarksarXiv 2609.05843Sep 5
SinoGlyphBench：中文字形混淆下语言模型审核的诊断基准
提出 SinoGlyphBench，用配对字形混淆诊断中文审核稳定性
arXiv
2609.05843
Published
Sep 5
Layer
Prompt layer
Setting
Models and APIs
Evaluated models
GPT-5.4 mini, GPT-5.5, DeepSeek V4 Flash and others12
- AttacksDetection evasion
- TechniqueEncoding and obfuscation
- ComponentGuardrails and judges
AbstractSinoGlyphBench 显示中文字形混淆会同时增加有害漏报和误报，全文扰动最重。
SinoGlyphBench是一个配对诊断基准，用来看内容审核在可还原的中文字形混淆下是否还保持原决定。
Paper analysisRead analysis
AttacksarXiv 2609.05525Sep 2
DIVA：针对离散扩散视觉语言模型的跨步条件传播视觉越狱
提出 DIVA，利用跨步条件传播对离散扩散视觉语言模型实施视觉越狱
arXiv
2609.05525
Published
Sep 2
Layer
Prompt layer
Setting
Models and APIs
Attacker
White-box
Evaluated models
LLaDA-V, MMaDA, LLaDA2.0-Uni
- AttacksJailbreaks
- TechniqueGradient and representation optimization
- ComponentVision
Paper analysisRead analysis
AttacksarXiv 2609.01168Sep 1
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
arXiv
2609.01168
Published
Sep 1
Layer
Prompt layer
Setting
Models and APIs
Attacker
Black-box
Evaluated models
Stable Diffusion v1.4, SDXL, DALL·E 3 and others4
- AttacksJailbreaks
- TechniqueAutomated search
- ComponentImage generation
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。
Paper analysisRead analysis
AttacksarXiv 2608.27531Aug 27
MAMJ：面向视觉语言模型的元自适应多模态越狱攻击
提出 MAMJ，在元层面交替优化多模态越狱的策略提示与攻击者权重
arXiv
2608.27531
Published
Aug 27
Layer
Prompt layer
Setting
Models and APIs
Attacker
Black-box
Evaluated models
GPT-4o, Gemini-3-Pro-Preview, Seed 2.0
- AttacksJailbreaks
- TechniqueAutomated search
- ComponentVision
Paper analysisRead analysis
AttacksarXiv 2608.15578Aug 16
ARENA：面向大型音频语言模型的自动化红队框架
提出 ARENA 音频红队框架，自动构造文本安全且音频接地的越狱输入
arXiv
2608.15578
Published
Aug 16
Layer
Prompt layer
Setting
Models and APIs
Attacker
Black-box
Evaluated models
Audio Flamingo 3, Qwen2-Audio-7B-Instruct, MiMo-Audio-7B-Instruct and others4
- AttacksJailbreaks
- TechniqueAutomated search
- ComponentAudio
Paper analysisRead analysis
AttacksarXiv 2608.04034Aug 3
HACA：原子越狱策略解耦组合的多模态自动红队方法
提出 HACA，将图文越狱拆为原子策略并自动组合以诱导有害输出
arXiv
2608.04034
Published
Aug 3
Layer
Prompt layer
Setting
Models and APIs
Evaluated models
LLaVA-1.6-Mistral-7B, InternVL-3.5-8B, VLGuard (LLaVA-v1.5-7B-Mixed) and others5
- AttacksJailbreaks
- TechniqueCross-modal payloads
- ComponentVision
Paper analysisRead analysis
AttacksarXiv 2607.02961Jul 3
研究者提出信息过载方法越狱大型视觉语言模型
提出 INFER+ 信息过载方法，越狱大型视觉语言模型
arXiv
2607.02961
Published
Jul 3
Layer
Prompt layer
Setting
Models and APIs
Attacker
Black-box, Gray-box
Evaluated models
Qwen3-VL-8B, Qwen2-VL-7B, InternVL3.5-8B and others8
- AttacksJailbreaks
- TechniqueCross-modal payloads
- ComponentVision
Abstract用图文过载越狱 LVLM。
这篇工作用信息过载越狱 LVLM，而不是靠 OOD 变换隐藏意图。
Paper analysisRead analysis
Evaluation and benchmarksarXiv 2606.07706Jun 5
MLingualFC：评估多语言视觉语言模型的越狱漏洞
提出 MLingualFC，用多语言流程图图像评测视觉语言模型越狱漏洞
arXiv
2606.07706
Published
Jun 5
Layer
Prompt layer
Setting
Models and APIs
Evaluated models
Qwen2.5-VL-3B-Instruct, Gemma-4-E4B-it, Pangea-7B
- AttacksJailbreaks
- TechniqueCross-modal payloads
- ComponentVision
Paper analysisRead analysis
Evaluation and benchmarksarXiv 2606.06037Jun 4
SpeechJBB：语码转换语音下大型音频语言模型的越狱基准
提出 SpeechJBB，评测语码转换语音下音频语言模型的越狱稳健性
arXiv
2606.06037
Published
Jun 4
Layer
Prompt layer
Setting
Models and APIs
Evaluated models
Qwen2.5-Omni-7B, Qwen3-Omni-30B-A3B-Instruct, Voxtral-Small-24B and others9
- AttacksJailbreaks
- TechniqueEncoding and obfuscation
- ComponentAudio
AbstractSpeechJBB 用五语语码转换语音和伪词探针评测九个 LALM，作者将越狱归为对齐失败而非听不懂。
SpeechJBB 用合成语音测量 LALM 在五语、语码转换和局部伪词混淆下的安全对齐，并另设口语理解对照。
Paper analysisRead analysis
AttacksarXiv 2606.01837Jun 1
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
arXiv
2606.01837
Published
Jun 1
Layer
Prompt layer
Setting
Models and APIs
Attacker
Black-box
Evaluated models
gemini-2.5-flash-image, qwen-image-2.0, Tongyi Wanx 2.5
- AttacksJailbreaks
- TechniqueCross-modal payloads
- ComponentImage generation
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。
Paper analysisRead analysis

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