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Evaluation and benchmarksarXiv 2610.07939Oct 6
CCDF dataset: Grok Imagine, Veo 3.1, Sora 2 forge surveillance footage, ten deepfake detectors basically cannot recognize it
提出监控深伪基准 CCDF，在统一编码后评测检测器对伪造犯罪事故录像的识别
arXiv
2610.07939
Published
Oct 6
Layer
Prompt layer
Setting
Models and APIs
Evaluated models
C2P-CLIP, ForgeLens, D3-Im and others10
- DefensesDetection and filtering
- AttacksDetection evasion
- ComponentGuardrails and judges
Abstract提出消除格式捷径的监控深度伪造基准 CCDF，揭示现有检测器难以识别商用生成视频。
Paper analysisRead analysis
Evaluation and benchmarksarXiv 2610.06339Oct 5
BabelFake：面向多语言音视频 DeepFake 检测的基准数据集
构建多语言音视频 DeepFake 基准 BabelFake 并评测检测器
arXiv
2610.06339
Published
Oct 5
Layer
Model layer
Setting
Models and APIs
Evaluated models
SpeechForensics, AVH-Align, (B)RAVEn
- DefensesDetection and filtering
- AttacksDetection evasion
- ComponentAudio
AbstractBabelFake 为五语同意采集基准。
BabelFake 是经同意与 IRB 批准采集的多语音视频 DeepFake 检测基准，用来把视觉操纵和语音合成拆开比较。
Paper analysisRead analysis
Evaluation and benchmarksarXiv 2610.04589Oct 3
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
Oct 3
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。
Paper analysisRead analysis
Evaluation and benchmarksarXiv 2610.06898Sep 29
DIBench：面向移动 GUI 智能体多候选选择决策完整性的安全基准
用 DIBench 评测移动 GUI 智能体被 UI 注入后的决策完整性
arXiv
2610.06898
Published
Sep 29
Layer
Application layer
Setting
Browser and computer use
Evaluated models
Qwen2.5-VL(32B), Qwen3-VL(32B), GUI-Owl(32B) and others7
- AttacksPrompt injection
- ComponentVision
Abstract论文提出移动智能体决策完整性基准 DIBench，发现欺诈 UI 注入诱导目标选择并推高完成率，通用防御收益不稳定。
Paper analysisRead analysis
Evaluation and benchmarksarXiv 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
Evaluation and benchmarksarXiv 2609.34790Sep 28
CoSec：面向社区场景的 LLM Agent 安全基准
用 CoSec 评测社区 Agent 是否越界披露受保护信息
arXiv
2609.34790
Published
Sep 28
Layer
Application layer
Setting
AI Agent
Evaluated models
OpenClaw with Gemini 3.1 Pro, OpenClaw with Qwen 3.8 Max, OpenClaw with MiniMax M2.5 and others13
- AttacksPrompt injection
- ComponentMemory
Paper analysisRead analysis
Evaluation and benchmarksarXiv 2609.35912Sep 28
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
Sep 28
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。
Paper analysisRead analysis
Evaluation and benchmarksarXiv 2609.33481Sep 27
IDUnlearn-Bench：面向视觉语言模型的个体级遗忘基准
提出 IDUnlearn-Bench，评测 VLM 个体级遗忘后的身份残留
arXiv
2609.33481
Published
Sep 27
Layer
Training and data layer
Setting
Models and APIs
Evaluated models
Qwen3-VL-2B, Qwen3-VL-4B, Qwen3-VL-8B and others6
- DefensesModel hardening
- AttacksExtraction and theft
- ComponentVision
AbstractIDUnlearn-Bench 用四族探针显示：压低直接属性访问后，身份仍常能被反向查出、绑定或重构。
IDUnlearn-Bench 评测 VLM 是否忘掉一个可跨模态识别的人，而不只是答不出某条监督事实。
Paper analysisRead analysis
Evaluation and benchmarksarXiv 2609.32616Sep 26
Cave-Bench：虚假指控下 LLM 智能体最高 60.06% 的运行会破坏正确工作
提出 CAVE-BENCH，评测智能体在虚假指责下破坏已完成的正确工作
arXiv
2609.32616
Published
Sep 26
Layer
Application layer
Setting
coding agent
Evaluated models
Claude-Sonnet-5, Claude-Opus-5, GPT-5.6-Sol and others14
- AttacksPrompt injection
- RiskDangerous agent actions
Abstract论文提出了评估智能体在虚假指责下破坏已有正确成果的 CAVE-BENCH，发现强模型易推翻已知证据，提出了门控缓解方案。
Paper analysisRead analysis
Evaluation and benchmarksarXiv 2609.22818Sep 19
研究测量 LLM Agent 记忆投毒防御的良性场景开销
测量记忆投毒防御在良性对话上的效用与 token 开销
arXiv
2609.22818
Published
Sep 19
Layer
Application layer
Setting
AI Agent
- AttacksPoisoning and backdoors
- ComponentMemory
Abstract写时代价落在噪声内。
在没有攻击的对话上，给记忆投毒防御计价，而不是再测一轮攻击是否被挡住。
Paper analysisRead analysis
Evaluation and benchmarksarXiv 2609.19705Sep 17
SoK 论文提出 FARSIGHT 框架，评测 15 个学术金融 LLM 交易 Agent 的鲁棒性与安全失败
用 FARSIGHT 方案级评测金融 LLM 交易 Agent 的稳健性与安全失败
arXiv
2609.19705
Published
Sep 17
Layer
Application layer
Setting
AI Agent
Evaluated models
ChatGPT Deep Research
- AttacksPrompt injection
- RiskDangerous agent actions
- ComponentMemory
Paper analysisRead analysis
Evaluation and benchmarksarXiv 2609.09404Sep 9
MMPIBench：多模态提示注入对六种 Agent 框架的跨框架评测
用 MMPIBench 评测多模态提示注入对 Agent 框架的影响
arXiv
2609.09404
Published
Sep 9
Layer
Application layer
Setting
AI Agent
Evaluated models
Claude Opus 4.8, GPT-5.4, Gemini 3.1 Pro and others6
- AttacksPrompt injection
- TechniqueCross-modal payloads
- ComponentVision
Abstract论文提出 MMPIBench 评测多模态提示注入对智能体的影响，发现模型主导行为、尝试远超完成，音频通道缺乏防护。
Paper analysisRead analysis
Evaluation and benchmarksarXiv 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
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
Evaluation and benchmarksarXiv 2609.04859Sep 4
MM-IFEval-Pro：面向视觉语言模型的多语言抗攻击指令遵循基准
提出抗攻击多语言视觉指令遵循基准 MM-IFEval-Pro
arXiv
2609.04859
Published
Sep 4
Layer
Prompt layer
Setting
Models and APIs
Evaluated models
Qwen3-VL-8B-Instruct, InternVL3.5-8B, MiniCPM-V4.5 and others5
- AttacksPrompt injection
- ComponentVision
AbstractMM-IFEval-Pro 以规则验证评测中英指令遵循与视觉劫持，GRPO 提高两基座平均分。
MM-IFEval-Pro 是面向 VLM 的中英多模态指令遵循基准，并配有可用规则计算奖励的 GRPO 训练集。
Paper analysisRead analysis
Evaluation and benchmarksarXiv 2609.05535Sep 2
Mind2Web-Injection：面向网页 Agent 视觉提示注入护栏的证据对齐评测
提出 Mind2Web-Injection 评测网页 Agent 视觉注入护栏
arXiv
2609.05535
Published
Sep 2
Layer
Application layer
Setting
LLM applications
Evaluated models
GPT-5.6-luna, Qwen3-VL-32B, Qwen3-VL-8B and others6
- DefensesDetection and filtering
- AttacksPrompt injection
- ComponentGuardrails and judges
Abstract作者称检测、定位和反事实响应在六个 VLM 上可分开。
Mind2Web-Injection 用来检查网页截图护栏的判决是否对齐到该用的画面证据。。
Paper analysisRead analysis
Evaluation and benchmarksarXiv 2608.12851Aug 13
研究者提出 SkillMisevo-Bench，量化自改进 Agent 的技能误演化风险
提出 SkillMisevo-Bench，量化自改进 Agent 的技能误演化
arXiv
2608.12851
Published
Aug 13
Layer
Application layer
Setting
coding agent
Evaluated models
Claude Code, Codex, Hermes and others4
- AttacksPoisoning and backdoors
- TechniqueDormant triggers
- ComponentMemory
Paper analysisRead analysis
Evaluation and benchmarksarXiv 2608.09476Aug 10
ActBench：面向协作智能体行为安全的自演化基准
构建自演化基准 ActBench，评测协作智能体的行为安全
arXiv
2608.09476
Published
Aug 10
Layer
Application layer
Setting
AI Agent
Evaluated models
Claude-Opus-4.8, Claude-Sonnet-4.6, GPT-5.5 and others15
- AttacksPrompt injection
- ComponentPermissions and sandboxing
AbstractActBench 通过自演化搜索与双证据重构评测轨迹行为安全，揭示基础模型决策差异主导了协同智能体的操作风险。
Paper analysisRead analysis
Evaluation and benchmarksarXiv 2608.03272Aug 4
多智能体协同过滤系统的连接性攻击与防御研究
复现 AgentCF 上的多智能体攻防并刻画连通性作用
arXiv
2608.03272
Published
Aug 4
Layer
Application layer
Setting
Multi-agent systems
Evaluated models
Qwen3-235B-A22B, Claude Haiku 4.5, Mixtral 8×7B and others4
- AttacksPoisoning and backdoors
- ComponentMemory
Abstract连通性沿 k 与ρ改变攻防，且用户/物品与早期/稳态需要分开看。
作者在 AgentCF 上研究连通性如何改变多智能体协同过滤的攻防，复现已有方法而不是提出新载荷。
Paper analysisRead analysis
Evaluation and benchmarksarXiv 2607.27080Jul 30
MemSecBench：追踪 Agent 记忆投毒从持久化到后果与修复
提出 MemSecBench 评测 Agent 记忆投毒与选择性修复
arXiv
2607.27080
Published
Jul 30
Layer
Application layer
Setting
AI Agent
Evaluated models
DeepSeek-V4-Pro, MiniMax-M3, GPT-5.5
- AttacksPoisoning and backdoors
- ComponentMemory
Paper analysisRead analysis

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