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Oct 13 · Tuesday

All papers

Found 36 papers

Filter6

Attack type

Jailbreaks3 Prompt injection24 Poisoning and backdoors17

Attack technique

Gradient and representation optimization10 Automated search49 Multi-turn escalation8 Encoding and obfuscation16 Role-play and persuasion3 Reasoning-chain manipulation4 Cross-modal payloads9 Defense-targeted19 Dormant triggers33 Selection manipulation11

Impact

Harmful content3 Unauthorized actions15 Data and privacy leaks6 Output manipulation8 Availability and reliability3

System type

Models and APIs12 LLM applications16 AI Agent36 coding agent9 web agent4 Multi-agent systems3 Embodied systems and robotics3

Attack surface / entry point

User input9 Web pages and interfaces5 Tool responses7 Tool and skill descriptions14 Retrieval corpus3 Memory writes3 Inter-agent messages3 Images, audio and video7 Distribution channels14

Layer

Prompt layer3 Model layer1 Application layer35

System component

MCP and skills16 Memory4 RAG3 Vision7 Multimodal7

Select any value within a category; different categories must all match. Counts include the other filters you have selected.Another 201papers have no tags yet and are not included in filtered results.

Attack technique：Gradient and representation optimization Attack technique：Encoding and obfuscation Attack technique：Selection manipulation System type：AI Agent Layer：Model layer Layer：Application layer Clear all

Another 201papers do not have category tags yet and are not included in filtered results.

AttacksarXiv 2610.12524Oct 8
An exploration of attacks on AI agent systems
Retest and extend prompt injection against AI agents, and use Agent Card deception to manipulate A2A selection
arXiv
2610.12524
Published
Oct 8
Layer
Application layer
Setting
AI Agent
Evaluated models
Ollama Mistral 0.9.5, llama3-8b-8192, gemini-2.0-flash-lite and others5
- AttacksPrompt injection
- TechniqueEncoding and obfuscation
- ComponentMCP and skills
AbstractSingle-agent filtering and classification can be bypassed by format or wording, and A2A card selection is also biased toward names and descriptions.
The authors retested prompt injection on their own LangChain, AutoGen, and A2A systems, and modified the Agent Card to see if choices shifted. The abstract states the experiments mainly highlight single-agent weaknesses while extending attacks to multi-agent.
Paper analysisRead analysis
AttacksarXiv 2610.09973Oct 7
从期望危害到似然：LLM 智能体越狱的概率重构
提出 OPUR 攻击，用似然梯度优化对抗后缀越狱 LLM 智能体
arXiv
2610.09973
Published
Oct 7
Layer
Application layer
Setting
AI Agent
Attacker
White-box
Evaluated models
Llama-3.1-8B-Instruct, Ministral-8B-Instruct-2410
- AttacksJailbreaks
- TechniqueGradient and representation optimization
Paper analysisRead analysis
AttacksarXiv 2610.09240Oct 7
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
Oct 7
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。
Paper analysisRead analysis
AttacksarXiv 2610.08098Oct 6
CORSA：面向技能路由器的技能注入攻击可跨路由器与 LLM 迁移
提出 CORSA，按任务簇优化技能注入的检索与执行
arXiv
2610.08098
Published
Oct 6
Layer
Application layer
Setting
coding agent
Evaluated models
GPT-5.4, DeepSeek-V4-Pro, Qwen3.8-27B and others5
- AttacksPoisoning and backdoors
- TechniqueSelection manipulation
- ComponentMCP and skills
Paper analysisRead analysis
AttacksarXiv 2610.06083Oct 5
研究者提出面向深度强化学习的轨迹级可迁移黑盒对抗攻击
提出轨迹级可迁移对抗攻击，降低深度强化学习策略的期望回报
arXiv
2610.06083
Published
Oct 5
Layer
Model layer
Setting
Embodied systems and robotics
Evaluated models
DQN, Double DQN (DDQN)
- TechniqueGradient and representation optimization
Abstract轨迹级后退视界攻击在 CartPole 上比逐步 FGSM 类和 Sign 噪声更压低回报。
这项工作研究 DRL 上的迁移式黑盒观测攻击：受害参数不可访问时，在白盒代理上造扰动再迁移。
Paper analysisRead analysis
AttacksarXiv 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
AttacksarXiv 2609.39788Sep 30
研究：多智能体系统潜在通信链路可被训练用于提升有害顺从
提出只训练或篡改多智能体潜在通信链路来提高有害遵从
arXiv
2609.39788
Published
Sep 30
Layer
Application layer
Setting
Multi-agent systems
Evaluated models
Llama-3.2-3B-Instruct, Qwen2.5-3B-Instruct, Gemma-3-1B-IT and others7
- AttacksModel tampering
- TechniqueGradient and representation optimization
Abstract潜在链路本身即可改变冻结智能体系统的安全，奖励既能攻击也能修复。
学习得到的潜在通信链路会改变由冻结、对齐智能体组成的系统是否遵从有害请求。。作者研究三种拓扑：双智能体、三级顺序协作，以及双专家加汇总。
Paper analysisRead analysis
AttacksarXiv 2609.36576Sep 29
AdaLCPI: Making agents reconstruct indirect prompt injection from long-context fragments
提出 AdaLCPI，把恶意指令拆成碎片嵌入工具返回并诱导 Agent 越权执行
arXiv
2609.36576
Published
Sep 29
Layer
Application layer
Setting
AI Agent
Evaluated models
GPT-4.1, GPT-5.1, GPT-5.6-Luna and others7
- AttacksPrompt injection
- TechniqueEncoding and obfuscation
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
AttacksarXiv 2609.30383Sep 25
研究者提出技能级联攻击
提出技能级联攻击，把有害目标拆散到多个技能里绕过单技能扫描
arXiv
2609.30383
Published
Sep 25
Layer
Application layer
Setting
AI Agent
Evaluated models
GPT-5.4, GPT-5.4 Mini, Claude Opus 4.6 and others11
- AttacksPoisoning and backdoors
- TechniqueDefense-targeted
- ComponentMCP and skills
Abstract论文探讨了多技能智能体系统面临的技能级联攻击风险，提出自动化红队框架与基准集，指出跨技能交互存在安全防护盲区。
Paper analysisRead analysis
AttacksarXiv 2609.26761Sep 23
A2M: A two-stage agent hijacking framework targeting the MCP ecosystem
提出两阶段框架 A2M，优化 MCP 工具元数据与返回载荷以劫持 Agent
arXiv
2609.26761
Published
Sep 23
Layer
Application layer
Setting
AI Agent
Evaluated models
GLM-4.6, Qwen3-Max, DeepSeek-V3.1 and others5
- AttacksPrompt injection
- TechniqueAutomated search
- ComponentMCP and skills
Paper analysisRead analysis
AttacksarXiv 2609.24994Sep 22
BAM 反馈编码实现推理时隐蔽的智能体通信
提出 BAM 反馈编码，在 LLM 生成文本中实现隐蔽通信
arXiv
2609.24994
Published
Sep 22
Layer
Application layer
Setting
AI Agent
Evaluated models
Llama-3.1-8B, Qwen-3.5-9B-Base, Mistral-7B-v0.3 and others6
- TechniqueEncoding and obfuscation
Paper analysisRead analysis
AttacksarXiv 2609.18217Sep 16
研究：跨通道碎片化攻击可绕过 MCP 单通道防御
提出跨通道分段攻击，利用 MCP 隐式信任外发敏感文件
arXiv
2609.18217
Published
Sep 16
Layer
Application layer
Setting
coding agent
Evaluated models
GPT-4o, GPT-4o-mini, GPT-5.4 and others15
- AttacksPrompt injection
- TechniqueEncoding and obfuscation
- ComponentMCP and skills
Abstract论文揭示了 MCP 多通道隐式信任层级，通过跨通道分段与协议级利用突破现有防御，展示了严重的凭证外发风险。
Paper analysisRead analysis
AttacksarXiv 2609.03884Sep 3
HookPry：利用插件生命周期钩子更新劫持 AI Agent 框架
提出 HOOKPRY，用插件钩子版本更新供应链劫持 Agent 框架
arXiv
2609.03884
Published
Sep 3
Layer
Application layer
Setting
AI Agent
- AttacksPoisoning and backdoors
- TechniqueDormant triggers
- ComponentMCP and skills
Paper analysisRead analysis
AttacksarXiv 2609.02035Sep 2
ISM：通过语义匹配隐式操纵 LLM Agent 的技能选择
提出 ISM，用语义匹配隐式操纵 Agent 技能选择
arXiv
2609.02035
Published
Sep 2
Layer
Application layer
Setting
AI Agent
Evaluated models
Llama-2-7B, Llama-3-8B, Llama-3.1-8B and others8
- AttacksPoisoning and backdoors
- TechniqueSelection manipulation
- ComponentMCP and skills
Paper analysisRead analysis
AttacksarXiv 2608.27800Aug 28
ContextLeak：通过恶意工具窃取 LLM Agent 运行时上下文
提出 ContextLeak，用强化学习优化恶意工具描述，诱导 Agent 外泄运行时上下文
arXiv
2608.27800
Published
Aug 28
Layer
Application layer
Setting
AI Agent
Evaluated models
Qwen-3-8B, GPT-OSS-20B, Gemma-4-E4B-it and others11
- AttacksPrompt injection
- TechniqueSelection manipulation
- ComponentMCP and skills
Paper analysisRead analysis
AttacksarXiv 2608.25776Aug 26
EvoMal attack uses self-poisoning of self-evolving coding agents to achieve worm-like propagation
提出 EVOMAL，诱导自演化编码 Agent 在创建技能时自我投毒并蠕虫传播
arXiv
2608.25776
Published
Aug 26
Layer
Application layer
Setting
coding agent
Evaluated models
Devstral-Small-2, Gemma-4-31B-IT, Qwen3-Coder-Next and others7
- AttacksPoisoning and backdoors
- TechniqueDormant triggers
- ComponentMCP and skills
Abstract论文指出了自演化智能体模仿检索代码的自我毒化漏洞，提出 EVOMAL 攻击与防御，阐明了供应链新风险。
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
AttacksarXiv 2608.12273Aug 13
研究者提出 Convergent Detour Hijacking 攻击，可让技能型 LLM Agent 绕路并放大资源消耗
提出 CDH 攻击，让技能型 Agent 绕路放大资源消耗
arXiv
2608.12273
Published
Aug 13
Layer
Application layer
Setting
AI Agent
Evaluated models
Claude-Haiku-4.5, DeepSeek-V4-Pro, DeepSeek-V4-Flash and others6
- AttacksPrompt injection
- TechniqueSelection manipulation
- ComponentMCP and skills
AbstractCDH 让静态技能在保持任务完成时拉高调用与 token，耗时则因后端而异。
CDH 是针对渐进披露技能智能体的发布者侧、纯文本攻击：一个静态协调器把本可正确完成的任务，拐进有界但更耗资源的技能绕路，再交还原任务。
Paper analysisRead analysis
AttacksarXiv 2608.06862Aug 7
SynChain：诱导计算机使用 Agent 自建攻击链并跨任务持久化
提出 SYNCHAIN，诱导计算机使用 Agent 自建跨任务持久攻击链
arXiv
2608.06862
Published
Aug 7
Layer
Application layer
Setting
Browser and computer use, coding agent
Evaluated models
Qwen3.5-9B, Llama-3.1-8B, Ministral-3-8B
- AttacksPoisoning and backdoors
- TechniqueDormant triggers
- ComponentMCP and skills
Abstract论文揭示了 CUA 自合成工件带来的内部供应链威胁，验证了潜伏载荷的跨任务传播能力与防御局限。
Paper analysisRead analysis

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