AttacksarXiv 2610.09708
研究者提出利用祖先 VLM 的黑盒对抗补丁攻击，可降低 VLA 任务成功率
提出利用祖先 VLM 优化对抗补丁，使已部署 VLA 任务失败
- arXiv
- 2610.09708
- Published
- Layer
- Prompt layer
- Evaluated models
- OpenVLA, UniVLA, π0.5
- TechniqueGradient and representation optimization
- ComponentVision
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- AttacksarXiv 2610.09240
WebMirage hijacks visual web agents' browser operations with adversarial images
提出 WebMirage，用局部对抗图像劫持视觉网页 Agent 的浏览器操作
- arXiv
- 2610.09240
- Published
- Layer
- Application layer
- Setting
- web agent
- Evaluated models
- LLaVA-v1.5-13B, LLaVA-v1.6-34B, MiniCPM-o-8B and others6
- AttacksPrompt injection
- TechniqueGradient and representation optimization
- ComponentVision
Abstract论文提出了针对网络智能体的端到端视觉红队框架 WebMirage，揭示了从视觉定位到浏览器执行的安全脆弱性。
WebMirage 是一个面向视觉定位网络智能体的流水线感知端到端红队攻击框架。
- AttacksarXiv 2610.09027
P-VMI：对抗图像经 KV cache 持续影响多轮对话
提出持久视觉记忆注入，使对抗图像经缓存在触发时操控输出
- arXiv
- 2610.09027
- Published
- Layer
- Infrastructure layer
- Setting
- Models and APIs
- Evaluated models
- Qwen3-8B, Qwen3-VL-8B-Instruct, Gemma-4-12B
- AttacksPrompt injection
- TechniqueDormant triggers
- ComponentVision
Abstract论文提出 P-VMI，证实对抗输入被掩蔽后仍可经 KV 缓存持久控制模型，强调了保留状态的安全风险。
- AttacksarXiv 2610.08331
STCA：研究者提出针对自动驾驶视频 VLM 的时空一致性对抗攻击
提出 STCA，对驾驶视频 VLM 构造可迁移的时空对抗扰动
- arXiv
- 2610.08331
- Published
- Layer
- Prompt layer
- Setting
- Models and APIs
- Attacker
- No-box (offline transfer)
- Evaluated models
- Video-LLaVA-7B, Qwen2.5-VL-7B, Dolphins
- AttacksDetection evasion
- TechniqueGradient and representation optimization
- ComponentVideo
- AttacksarXiv 2610.06814
TAPDreamer：可跨任务迁移的世界动作模型对抗补丁
TAPDreamer 用公开编码器做固定补丁。
- arXiv
- 2610.06814
- Published
- Layer
- Prompt layer
- Evaluated models
- FastWAM, DreamWAM-uncond, DreamWAM-joint and others4
- TechniqueGradient and representation optimization
- ComponentVision
- AttacksarXiv 2610.06977
IAU-FOA：面向闭源多模态大模型的可迁移对抗攻击方法
提出 IAU-FOA，构造可迁移图像扰动以诱导多模态模型输出目标语义
- arXiv
- 2610.06977
- Published
- Layer
- Prompt layer
- Setting
- Models and APIs
- Evaluated models
- Qwen2.5-VL-7B, Qwen2.5-VL-72B, InternVL3-14B and others17
- TechniqueGradient and representation optimization
- ComponentVision
- AttacksarXiv 2610.04589
StegoMemory red team testing: agent persistent memory can be used as a cross-session covert channel
提出 StegoMemory，评测智能体持久记忆作为跨会话隐写信道
- arXiv
- 2610.04589
- Published
- Layer
- Application layer
- Setting
- AI Agent
- Evaluated models
- Llama 3.1 405B, Claude 3.5 Sonnet, GPT-4o and others13
- AttacksPoisoning and backdoors
- TechniqueEncoding and obfuscation
- ComponentMemory
Abstract研究揭示智能体持久记忆可作为隐蔽信道跨会话传输机密，写入持久化是主要防御瓶颈，呼吁建立记忆完整性防御。
- 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
- arXiv
- 2609.38253
- Published
- 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。
MMSkillRisk：多模态技能图像中的隐藏指令可诱导 Agent 执行未授权操作
提出 MMSkillRisk 基准，评测多模态技能图像中的隐藏指令诱导 Agent 越权操作
- arXiv
- 2609.35912
- Published
- Layer
- Application layer
- Setting
- coding agent
- Evaluated models
- GPT-5.6-sol, Kimi-K2.6, Kimi-K3 and others6
- AttacksPrompt injection
- TechniqueCross-modal payloads
- ComponentMCP and skills
Abstract论文提出 MMSkillRisk 基准与 NCVA 攻击，揭示多模态技能中教学图像潜藏指令可引发未授权操作并与良性任务共存。
研究用 XAI 归因分析 Prompt Guard 2，同义词替换可翻转其提示注入判定
用词级归因指导同义词替换，翻转提示注入检测并验证越狱
- arXiv
- 2609.24801
- Published
- Layer
- Prompt layer
- Setting
- Models and APIs
- Evaluated models
- Prompt Guard 2 (86M), Llama 3.1 8B
- DefensesDetection and filtering
- AttacksDetection evasion
- TechniqueGradient and representation optimization
- ComponentGuardrails and judges
Abstract作者称检测靠分散的词法线索。
- AttacksarXiv 2609.09553
研究：任意密文攻击前沿大模型无需微调即可越狱
提出任意字母置换密码越狱，无需微调即可诱导有害输出
- arXiv
- 2609.09553
- Published
- Layer
- Prompt layer
- Setting
- Models and APIs
- Attacker
- Black-box
- Evaluated models
- Claude Sonnet 4, Claude Sonnet 4.5, Gemini 3 Flash (preview) and others7
- AttacksJailbreaks
- TechniqueEncoding and obfuscation
- ComponentGuardrails and judges
Abstract前沿大模型无需微调即可通过提示词学会字母置换密码，进而绕过分类器与对齐，作者呼吁关注能力提升带来的安全风险。
- 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
- arXiv
- 2609.07216
- Published
- 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。。
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
- 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。
- AttacksarXiv 2609.05525
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
- Layer
- Prompt layer
- Setting
- Models and APIs
- Attacker
- White-box
- Evaluated models
- LLaDA-V, MMaDA, LLaDA2.0-Uni
- AttacksJailbreaks
- TechniqueGradient and representation optimization
- ComponentVision
- AttacksarXiv 2608.23471
InjecMEM: Memory Injection Attacks against LLM Agent Memory Systems
提出 InjecMEM，一次注入 Agent 记忆使后续查询输出预设内容
- arXiv
- 2608.23471
- Published
- Layer
- Application layer
- Setting
- AI Agent
- Evaluated models
- Qwen2.5-7B-Instruct, Llama-3.1-8B-Instruct, Mistral-7B-Instruct-v0.3 and others6
- AttacksPoisoning and backdoors
- TechniqueGradient and representation optimization
- ComponentMemory
- AttacksarXiv 2608.10393
DURA：用扩散模型生成自然对抗补丁攻击 VLA 机器人模型
提出 DURA，用扩散模型生成自然对抗补丁操控 VLA 机器人动作
- arXiv
- 2608.10393
- Published
- Layer
- Prompt layer
- Evaluated models
- OpenVLA-7B, π0-FAST, openvla-7B
- TechniqueCross-modal payloads
- ComponentVision
AbstractDURA 用扩散潜空间轨迹生成自然补丁，白盒与黑盒都能把 VLA 导向指定动作。
DURA 是针对 VLA 的扩散式、补丁内容不受限的机器人攻击，同时支持白盒梯度和只看动作输出的黑盒。
- AttacksarXiv 2608.04034
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
- 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
- AttacksarXiv 2607.27373
RoguePrompt 用双层编码绕过 LLM 审核
提出 RoguePrompt 双层编码自重构越狱，绕过 LLM 审核
- arXiv
- 2607.27373
- Published
- Layer
- Prompt layer
- Setting
- Models and APIs
- Attacker
- Black-box
- Evaluated models
- OpenAI GPT-4o (gpt-4o-2024-11-20), Anthropic Claude 3 Opus (claude-3-opus-20240229), Google Gemini 1.5 Pro (gemini-1.5-pro-002)
- AttacksJailbreaks
- TechniqueEncoding and obfuscation
- ComponentGuardrails and judges
- AttacksarXiv 2607.14493
LogInject 框架披露 LLM 日志分析中的被动提示注入
提出 LogInject 框架，评测日志分析中的被动提示注入及缓解
- arXiv
- 2607.14493
- Published
- Layer
- Application layer
- Setting
- LLM applications
- Evaluated models
- GPT-4o, Claude 3.5 Sonnet, Llama-3-70B-Instruct
- AttacksPrompt injection
- TechniqueEncoding and obfuscation
- ComponentGuardrails and judges
Abstract论文评估了 LLM 日志分析中的上下文污染风险，提出分片拼接等攻击与三层防御，指出必须结合架构隔离与人工介入。
- AttacksarXiv 2606.21077
OTTER：仅替换五个 token 即可绕过 GPT 系列毒性审核
提出 OTTER 词元替换越狱，绕过表面毒性审核诱导有害回答
- arXiv
- 2606.21077
- Published
- Layer
- Prompt layer
- Setting
- Models and APIs
- Attacker
- Black-box
- Evaluated models
- gpt-4-turbo, gpt-4o, gpt-4o-mini and others4
- AttacksJailbreaks
- TechniqueEncoding and obfuscation
- ComponentGuardrails and judges
Abstract论文展示了表面毒性与恶意意图的解耦现象，通过标准 API 实现黑盒越狱测试，并提出闭环分类器加固建议。