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Oct 12 · Monday

All papers

Found 11 papers

Filter5

Attack type

Prompt injection11 Poisoning and backdoors6

Attack technique

Automated search20 Encoding and obfuscation4 Conversation structure manipulation1 Defense-targeted4 Dormant triggers6

Impact

Data and privacy leaks3 Output manipulation5

System type

AI Agent11

Attack surface / entry point

User input21 Web pages and interfaces5 Documents and messages10 Tool responses11 Tool and skill descriptions12 Code repositories and dependencies6 Retrieval corpus5 Memory writes17 Weights and gradients3 Distribution channels13

Layer

Application layer11

System component

Memory6

Select any value within a category; different categories must all match. Counts include the other filters you have selected.Another 240papers have no tags yet and are not included in filtered results.

Attack technique：Conversation structure manipulation Attack technique：Defense-targeted Attack technique：Dormant triggers Attack surface / entry point：Tool responses Layer：Application layer Clear all

Another 240papers do not have category tags yet and are not included in filtered results.

AttacksarXiv 2609.27542Sep 23
Researchers use control token injection to delete gpt-oss-20b's reasoning chain and bypass chain-of-thought monitoring
提出控制标记注入，清空工具 Agent 的思维链以绕过推理监控
arXiv
2609.27542
Published
Sep 23
Layer
Application layer
Setting
AI Agent
Evaluated models
openai/gpt-oss-20b, google/gemma-4-26B-A4B-it, deepseek-ai/DeepSeek-R1-Distill-Qwen-7B and others4
- AttacksPrompt injection
- TechniqueConversation structure manipulation
- ComponentReasoning chains
Abstract论文阐明控制标记注入可抑制 CoT 使监控失效并促成拒绝绕过，且工具执行受解析器宽容度影响。
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 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 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
AttacksarXiv 2607.05189Jul 6
Researchers propose MemGhost, achieving covert memory injection into persistent personal agents
提出 MEMGHOST，用单封邮件对持久个人 Agent 做跨会话隐蔽记忆注入
arXiv
2607.05189
Published
Jul 6
Layer
Application layer
Setting
AI Agent
Evaluated models
GPT-5.4, Claude Sonnet 4.6, Claude Sonnet 4.5 and others6
- AttacksPoisoning and backdoors
- TechniqueAutomated search
- ComponentMemory
Abstract总结了论文的研究背景、双代理优化方法 MEMGHOST、全周期实验结果以及作者对记忆信任边界的启示。
本文研究了持久化个人智能体面临的隐蔽记忆注入威胁，提出了一套兼顾写入、隐蔽与跨会话生效的自动化生成框架与全周期评测基准。
Paper analysisRead analysis
AttacksarXiv 2606.04329Jun 3
研究者系统研究 LLM 智能体记忆投毒攻击并提出 MPBench 基准
系统研究 LLM 智能体记忆投毒并构建基准 MPBench
arXiv
2606.04329
Published
Jun 3
Layer
Application layer
Setting
AI Agent
Evaluated models
Meta-Llama-3.1-70B-Instruct, Deberta-v3-base, Llama-3.1-8B-Instruct and others5
- AttacksPoisoning and backdoors
- TechniqueDormant triggers
- ComponentMemory
Abstract系统研究了智能体记忆投毒风险，揭示了写入渠道漏洞，构建了 MPBench 基准并指出提示注入防御的局限。
Paper analysisRead analysis
Evaluation and benchmarksarXiv 2605.01970May 4
Trojan Hippo Bench: A Dynamic Benchmark for Persistent Memory Attacks and Defenses on LLM Agents
构建 Trojan Hippo Bench，评测 Agent 持久记忆投毒与外泄
arXiv
2605.01970
Published
May 4
Layer
Application layer
Setting
AI Agent
Evaluated models
Gemini 3.1 Pro, GPT-5-mini, GPT-5
- AttacksPoisoning and backdoors
- TechniqueDormant triggers
- ComponentMemory
Abstract论文提出了评测智能体持久化记忆攻击与防御的 Trojan Hippo Bench，揭示了潜伏攻击威胁及内存防御的安全与效用权衡。
Paper analysisRead analysis
AttacksarXiv 2603.24203Mar 25
研究者提出 TIP：用树结构搜索为 MCP 生成隐蔽注入载荷
提出 TIP，用树搜索为 MCP 响应生成隐蔽注入载荷
arXiv
2603.24203
Published
Mar 25
Layer
Application layer
Setting
AI Agent
Evaluated models
Qwen2.5-7B-Instruct, Qwen2.5-72B-Instruct, Llama3.1-8B-Instruct and others8
- AttacksPrompt injection
- TechniqueAutomated search
AbstractTIP 在 MCP 工具响应上做黑盒注入。
TIP 是面向 MCP 工具响应的 black-box 间接提示注入，目标是在不改工具元数据的情况下生成语义连贯的 JSON 载荷。
Paper analysisRead analysis
AttacksarXiv 2510.09023Oct 10, 2025
Paper proposes adaptive attack framework that breaks through 12 LLM jailbreak and prompt injection defenses
提出自适应攻击框架，击穿越狱与提示注入防御
arXiv
2510.09023
Published
Oct 10, 2025
Layer
Application layer
Setting
AI Agent
Attacker
White-box, Black-box
Evaluated models
Gemini-2.5 Pro, GPT-5 Mini, Llama-3.3 70B and others15
- AttacksJailbreaks
- TechniqueDefense-targeted
Paper analysisRead analysis
AttacksarXiv 2510.04885Oct 6, 2025
RL-Hammer：用 GRPO 从头训练攻击模型
提出 RL-Hammer，从零训练攻击模型经工具输出实施提示注入
arXiv
2510.04885
Published
Oct 6, 2025
Layer
Application layer
Setting
AI Agent
Evaluated models
Llama-3.1-8B-Instruct, Meta-SecAlign-8B, Meta-SecAlign-70B and others10
- AttacksPrompt injection
- TechniqueAutomated search
Abstract作者称通过无热启动的强化学习可有效突破具备防御的商业模型，论文提出的 RL-Hammer 促使业界关注提示注入风险。
RL-Hammer 是一个无需热启动数据、基于 GRPO 算法从零训练的黑盒提示注入对抗攻击框架。现有针对大语言模型智能体的提示注入防御（如 Instruction Hierarchy 与 SecAlign）主要在静态或弱攻击下测试，在面对自动化强力攻击时的真实防御能力缺乏充分检验。方法的核心机制包括。
Paper analysisRead analysis
AttacksarXiv 2507.10457Jul 15, 2025
论文提出 LPCI：针对 Agent 逻辑层与持久记忆的提示控制注入攻击
提出 LPCI，把延迟条件载荷写入记忆与检索库以跨会话触发
arXiv
2507.10457
Published
Jul 15, 2025
Layer
Application layer
Setting
AI Agent
Evaluated models
ChatGPT, Claude, LLaMA3 and others8
- AttacksPoisoning and backdoors
- TechniqueDormant triggers
- ComponentMemory
Abstract作者定义 LPCI。
作者把LPCI定义为针对智能体逻辑执行、记忆留存和工具集成的跨阶段漏洞类，而不是单次输入上的提示改写。
Paper analysisRead analysis

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