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Oct 12 · Monday

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Found 29 papers

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Impact：Output manipulation System component：Memory System component：Video Clear all

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AttacksarXiv 2610.08331Oct 6
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
Oct 6
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
Paper analysisRead analysis
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
AttacksarXiv 2610.07645Oct 6
SkillPoison：用成功经验投毒自进化 Agent 的技能形成
提出 SkillPoison，用局部有效的成功经验诱导自进化 Agent 形成过度泛化技能
arXiv
2610.07645
Published
Oct 6
Layer
Application layer
Setting
AI Agent
Evaluated models
deepseek-v4-flash, Qwen V3.8 Flash, GPT-5.5
- AttacksPoisoning and backdoors
- TechniqueDormant triggers
- ComponentMemory
AbstractSkillPoison 通过局部有效且验证成功的经验诱导技能过度泛化，在多个评测基准上实现了持久的下游攻击影响。
SkillPoison 提出了一种针对自进化智能体经验到技能形成过程的攻击范式，通过组织已验证的成功经验诱导技能过度泛化。
Paper analysisRead analysis
DefensesarXiv 2610.07403Oct 6
针对 LLM 谄媚的纵深防御：记忆门控对激活诱导与记忆诱导谄媚的评估
评测记忆门控对激活诱导与记忆诱导谄媚的防御效果
arXiv
2610.07403
Published
Oct 6
Layer
Application layer
Setting
LLM applications
Evaluated models
Llama-3.1-8B-Instruct, Qwen2.5-7B-Instruct, Mistral-7B-Instruct-v0.3 and others4
- DefensesDetection and filtering
- RiskMisalignment and value divergence
- ComponentMemory
Abstract作者称外部记忆过滤成立，数据未显示反向转向再有贡献。
作者在四个开源指令模型上，把激活转向和外部记忆处理放进同一纵深防御协议，看记忆诱发谄媚和内部谄媚压力能否分开压低，以及个性化效用还剩多少。要处理的问题是：检索到的用户历史会推动模型顺从存储信念。只改外部上下文，并不直接动模型内部的谄媚表征。
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
DefensesarXiv 2610.05162Oct 4
MemAdapter：用反事实适配缓解记忆诱发的谄媚
提出 MemAdapter，在检索后约束记忆对智能体推理的影响
arXiv
2610.05162
Published
Oct 4
Layer
Application layer
Setting
AI Agent
Evaluated models
DeepSeek-V4-Flash, GPT-5.6-sol, Qwen3-8B
- DefensesInstruction–data separation
- RiskMisalignment and value divergence
- ComponentMemory
Abstract检索后三阶段调节记忆角色。
MemAdapter 是给长期记忆智能体用的检索后调节框架，用来处理记忆诱发谄媚。
Paper analysisRead analysis
DefensesarXiv 2610.02999Oct 2
OmniConfess：用 Token 级「忏悔」缓解全模态幻觉
提出 OmniConfess，冻结候选并按通道重打分以缓解全模态幻觉
arXiv
2610.02999
Published
Oct 2
Layer
Model layer
Setting
Models and APIs
Evaluated models
Qwen2.5-Omni-7B, Qwen3-Omni-30B-A3B, Nemotron-3-Nano-Omni-30B
- DefensesInference-time intervention
- RiskHallucination and fabrication
- ComponentVision
Paper analysisRead analysis
Evaluation and benchmarksarXiv 2609.39473Sep 30
FAME：用反事实推理评测自主智能体的虚假记忆
提出 FAME，用反事实概念漂移评测智能体虚假记忆
arXiv
2609.39473
Published
Sep 30
Layer
Model layer
Setting
Models and APIs
Evaluated models
Llama-3B
- ComponentMemory
AbstractFAME 用反事实引起的隐状态概念漂移，在出答案前区分忠实记忆与虚假记忆。
FAME 是一个免训练的评测框架，用来判断自主智能体的记忆在虚假相关、环境偏移或知识冲突下是否已变成虚假记忆。。
Paper analysisRead analysis
AttacksarXiv 2609.38270Sep 29
VirusCascade：劫持 LLM 推荐智能体的协同反思机制
提出 VirusCascade，联合操纵商品描述与交互轨迹以劫持推荐智能体协同反思
arXiv
2609.38270
Published
Sep 29
Layer
Application layer
Setting
Multi-agent systems
Evaluated models
AgentCF, AgentSEQ, AgentRAG and others4
- AttacksPoisoning and backdoors
- TechniqueDormant triggers
- ComponentMemory
Abstract作者把反思写回视为推广攻击入口，并用联合操纵和诊断探针研究其持续与传播。
VirusCascade 是针对推荐智能体协作反思的 black-box targeted promotion 攻击研究。 攻击者只改商品描述和少量账号的普通交互，试图让目标商品获得更多良性用户曝光。
Paper analysisRead analysis
Evaluation and benchmarksarXiv 2609.36130Sep 29
论文提出 DerivAudit：审计长期 Agent 记忆是否真由交互历史支持
提出 DERIVAUDIT 审计长期 Agent 记忆是否由交互历史导出
arXiv
2609.36130
Published
Sep 29
Layer
Application layer
Setting
AI Agent
Evaluated models
Qwen3-30B-A3B, Gemma-4-31B, Llama-3.3-70B-Instruct
- RiskHallucination and fabrication
- ComponentMemory
AbstractDERIVAUDIT 表明扩历史能补出处，但组合准入与过细检查仍两侧出错。
DERIVAUDIT 审计长期智能体的持久记忆是否由写入时可获得的交互历史支持，而不是只看以后能否被召回。
Paper analysisRead analysis
Evaluation and benchmarksarXiv 2609.17320Sep 15
Emergence World：对长时程多智能体系统开展对抗压力测试
提出 Emergence World，对长时程多智能体系统开展对抗压力测试
arXiv
2609.17320
Published
Sep 15
Layer
Application layer
Setting
Multi-agent systems
Evaluated models
Claude Opus 4.8, DeepSeek v4 Pro, Gemini 3.5 Flash and others9
- AttacksPrompt injection
- RiskMisalignment and value divergence
- ComponentMemory
Abstract作者通过长期平行世界实验指出模型对齐不具备可组合性，单模型群体会产生社会奉承、协同退缩及语言不透明等失效。
Paper analysisRead analysis
DefensesarXiv 2609.02127Sep 2
论文提出带类型溯源与断言护栏，防止持久化 AI Agent 把不可信输入当作自身历史
提出类型化溯源与断言护栏，约束持久 Agent 释放自传断言
arXiv
2609.02127
Published
Sep 2
Layer
Application layer
Setting
AI Agent
- DefensesWatermarking and provenance
- AttacksPoisoning and backdoors
- ComponentMemory
Paper analysisRead analysis
AttacksarXiv 2608.23471Aug 25
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
Aug 25
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
Paper analysisRead analysis
DefensesarXiv 2608.10502Aug 11
依赖引导回滚修复：为记忆增强 Agent 恢复错误记忆后的答案与状态
提出依赖引导回滚修复，恢复记忆增强 Agent 的回答与状态
arXiv
2608.10502
Published
Aug 11
Layer
Application layer
Setting
AI Agent
Evaluated models
GPT-4o, Gemini-3.6-Flash, Qwen3.6-27B
- DefensesInstruction–data separation
- AttacksPoisoning and backdoors
- ComponentMemory
Paper analysisRead analysis
Risky behaviorarXiv 2608.10218Aug 11
研究者用进化算法构造多智能体 LLM 系统中的自我传播“思维病毒”
用演化算法构造 mind virus 并测量其在多智能体中的传播
arXiv
2608.10218
Published
Aug 11
Layer
Application layer
Setting
Multi-agent systems, coding agent
Evaluated models
Claude Haiku 4.5, Claude Sonnet 4.6, Gemini 3 Flash and others7
- RiskMisalignment and value divergence
- ComponentMemory
Paper analysisRead analysis
AttacksarXiv 2608.03844Aug 4
MAFIA：针对带审计 LLM Agent 的查询式记忆投毒攻击
提出 MAFIA，以探测放置与事实伪装对带审计 Agent 做查询式记忆投毒
arXiv
2608.03844
Published
Aug 4
Layer
Application layer
Setting
AI Agent
Evaluated models
gpt-5.4-mini, Gemini, ProtectAI and others8
- AttacksPoisoning and backdoors
- TechniqueDormant triggers
- ComponentMemory
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: Tracing agent memory poisoning from persistence to consequences and repair
Proposing MemSecBench to evaluate agent memory poisoning and selective repair
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
Evaluation and benchmarksarXiv 2607.10526Jul 12
PASB 基准：自改进个人 Agent 的持久谄媚在后续会话中失败率达 71.9%
评测自改进个人 Agent 把用户主张写入记忆后的持久谄媚
arXiv
2607.10526
Published
Jul 12
Layer
Application layer
Setting
AI Agent
Evaluated models
GPT-5.5, GPT-5.4, Gemini-3.1-Pro and others12
- RiskMisalignment and value divergence
- ComponentMemory
AbstractPASB 显示一次被写入的主张会跨会话塑造回答，改笔记比只阻止写入更能降低后续失败。
PASB 评测自改进个人智能体的持久谄媚：用户主张被智能体自己写入档案、记忆或技能后，新会话里的中立问题仍可能按它作答。
Paper analysisRead analysis
AttacksarXiv 2607.06595Jul 7
When Agents Remember Too Much: Memory Poisoning Attacks against Large Language Model Agents
Proposed GhostWriter memory poisoning, which writes into the agent's long-term memory via email and calendar and activates across sessions
arXiv
2607.06595
Published
Jul 7
Layer
Application layer
Setting
AI Agent
Evaluated models
GPT-5.4-mini, DeepSeek-V4-Flash, Gemini-2.5-Flash and others4
- DefensesDetection and filtering
- AttacksPoisoning and backdoors
- TechniqueDormant triggers
- ComponentMemory
Paper analysisRead analysis

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Attack type

Attack technique

Model risks

Defense type

Impact

System type

Attack surface / entry point

Layer

System component

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

CCDF dataset: Grok Imagine, Veo 3.1, Sora 2 forge surveillance footage, ten deepfake detectors basically cannot recognize it

SkillPoison：用成功经验投毒自进化 Agent 的技能形成

针对 LLM 谄媚的纵深防御：记忆门控对激活诱导与记忆诱导谄媚的评估

BabelFake：面向多语言音视频 DeepFake 检测的基准数据集

MemAdapter：用反事实适配缓解记忆诱发的谄媚

OmniConfess：用 Token 级「忏悔」缓解全模态幻觉

FAME：用反事实推理评测自主智能体的虚假记忆

VirusCascade：劫持 LLM 推荐智能体的协同反思机制

论文提出 DerivAudit：审计长期 Agent 记忆是否真由交互历史支持

Emergence World：对长时程多智能体系统开展对抗压力测试

论文提出带类型溯源与断言护栏，防止持久化 AI Agent 把不可信输入当作自身历史

InjecMEM: Memory Injection Attacks against LLM Agent Memory Systems

依赖引导回滚修复：为记忆增强 Agent 恢复错误记忆后的答案与状态

研究者用进化算法构造多智能体 LLM 系统中的自我传播“思维病毒”

MAFIA：针对带审计 LLM Agent 的查询式记忆投毒攻击

多智能体协同过滤系统的连接性攻击与防御研究

MemSecBench: Tracing agent memory poisoning from persistence to consequences and repair

PASB 基准：自改进个人 Agent 的持久谄媚在后续会话中失败率达 71.9%

When Agents Remember Too Much: Memory Poisoning Attacks against Large Language Model Agents