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Attack type：Prompt injection Attack type：Extraction and theft Attack surface / entry point：Distribution channels Layer：Model layer Layer：Application layer Clear all

Another 232papers do not have category tags yet and are not included in filtered results.

AttacksarXiv 2610.09264Oct 7
研究者提出 PackHallu：经规则文件提示注入对编码 Agent 发起包幻觉攻击
提出 PackHallu，经规则文件提示注入诱导编码 Agent 换用攻击者指定包
arXiv
2610.09264
Published
Oct 7
Layer
Application layer
Setting
coding agent
Evaluated models
Qwen2.5-Coder-7B, Qwen3-Coder-30B, Devstral-Small-2-24B and others19
- AttacksPrompt injection
- TechniqueAutomated search
AbstractPackHallu 诱导规则文件换包。
PackHallu 研究一种针对编程智能体规则文件的提示注入：让智能体在本应使用合法依赖时，改导入攻击者指定并控制的包。
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
Analysis and theoryarXiv 2610.06001Oct 5
AgentSpy: Observing AI agent behavior at the system call layer and detecting skill injection attacks
提出 AgentSpy，在系统调用层观测 Agent 行为并检测技能注入
arXiv
2610.06001
Published
Oct 5
Layer
Application layer
Setting
coding agent
Evaluated models
gpt-5.6-terra, deepseek-v4-flash, glm-5.3-flash and others4
- DefensesDetection and filtering
- AttacksPoisoning and backdoors
- ComponentMCP and skills
Abstract提出了系统级智能体监控框架 AgentSpy，揭示出通过测试背后的非预期行为与注入风险。
本研究提出了面向 AI 智能体的系统级外部监控与行为分析框架 AgentSpy。
Paper analysisRead analysis
AttacksarXiv 2610.03857Oct 3
研究者提出 EviLLM 攻击：通过被入侵账号向 AI 代码生成流程注入漏洞
提出 EviLLM，经账户指令或插件向代码生成流程注入漏洞
arXiv
2610.03857
Published
Oct 3
Layer
Application layer
Setting
coding agent
Evaluated models
GPT-4o, Llama 3.2 (3B)
- AttacksPrompt injection
- TechniqueDefense-targeted
Paper analysisRead analysis
DefensesarXiv 2610.02861Oct 2
论文提出在 Kubernetes 上保护 AI Agent 的七层纵深防御框架与参考架构
提出 Kubernetes 运维智能体的七层纵深防御框架与参考架构
arXiv
2610.02861
Published
Oct 2
Layer
Application layer
Setting
AI Agent
- DefensesPermissions and approval
- AttacksPrompt injection
- ComponentPermissions and sandboxing
Abstract把运维智能体当不可信租户，用七层控制在完全攻破假设下约束行动。
把 Kubernetes 上的运维智能体当作不可信租户，在假定提示注入已完全控制其工具选择的前提下，用基础设施重建数据面与控制面的边界。要解决的是：智能体读日志、注解、工单或 MCP 工具描述时，这些内容可以变成它带着自身凭据执行的命令。模型对齐和分类器只降低概率。
Paper analysisRead analysis
AttacksarXiv 2610.01564Oct 1
APEX 用跨技能链劫持 LLM Agent
提出 APEX，用跨技能进度记录夹带虚假授权劫持 Agent
arXiv
2610.01564
Published
Oct 1
Layer
Application layer
Setting
AI Agent
Evaluated models
Claude Sonnet 5, DeepSeek V4 Flash, GPT-5.4 and others6
- AttacksPrompt injection
- TechniqueAutomated search
- ComponentMCP and skills
Paper analysisRead analysis
DefensesarXiv 2609.39450Sep 30
ActionGuard：在工具调用执行前拦截被投毒技能
提出 ActionGuard 在执行前拦截被投毒技能诱发的未授权工具调用
arXiv
2609.39450
Published
Sep 30
Layer
Application layer
Setting
AI Agent
Evaluated models
Gemma 4 (gemma4:e4b-it-q4_K_M), Qwen 3.5 (qwen3.5:9b), Ministral 3 (ministral-3:8b-instruct-2512-q4_K_M) and others5
- DefensesInstruction–data separation
- AttacksPoisoning and backdoors
- ComponentMCP and skills
Paper analysisRead analysis
AttacksarXiv 2609.39065Sep 30
TrustProbe finds 104 skill trust chain vulnerabilities in 11 open-source agents
提出 TrustProbe，挖掘技能智能体中不可信 skill 到特权操作的信任链漏洞
arXiv
2609.39065
Published
Sep 30
Layer
Application layer
Setting
AI Agent
Evaluated models
OpenClaw, OpenCode, Hermes Agent and others11
- AttacksPoisoning and backdoors
- TechniqueDormant triggers
- ComponentMCP and skills
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
Evaluation and benchmarksarXiv 2609.28915Sep 24
研究提出 ACE 语料库，评估内核级证据对 Agent 安全检测的有效性
构建 ACE 语料，评测内核级证据对 Agent 攻击检测的有效性
arXiv
2609.28915
Published
Sep 24
Layer
Application layer
Setting
coding agent
Evaluated models
AdaBoost, XGBoost, TabPFN and others10
- AttacksPrompt injection
- ComponentMCP and skills
AbstractACE 用配对的内核与应用层证据表明，syscall 痕迹可判别智能体攻击，两层组合通常更好。
ACE 是一份把智能体会话的内核 syscall 痕迹与应用层清单、转录配对起来的检测语料和基准。。
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 2609.18217Sep 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
DefensesarXiv 2609.14079Sep 13
SkillSecurer：检测并修补 AI Agent 技能中的提示注入漏洞
提出 SkillSecurer，检测并修补 Agent 技能中的提示注入漏洞
arXiv
2609.14079
Published
Sep 13
Layer
Application layer
Setting
coding agent
Evaluated models
Claude Sonnet 5, Gemini 3.6 Flash, GPT-5.6 Sol and others10
- DefensesDetection and filtering
- AttacksPrompt injection
- 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
DefensesarXiv 2608.21101Aug 21
ClawSentry：面向自主 LLM Agent 的渐进式多层安全监控网关
提出 ClawSentry 多层监控网关，在技能准入和运行时拦截恶意技能与隐藏指令
arXiv
2608.21101
Published
Aug 21
Layer
Application layer
Setting
coding agent
Evaluated models
Codex/GPT-5.4, Codex/GPT-5.5, Claude Code/GLM-5.1 and others6
- DefensesMonitoring and auditing
- AttacksPoisoning and backdoors
- ComponentMCP and skills
AbstractClawSentry 用包准入、三级运行时门控和反绕过，压低 skill 攻击并保住干净任务。
ClawSentry 是挂在智能体运行时之外的安全监督网关，用来同时盖住 skill 执行的多个生命周期边界，并把已被拒绝的效果记到会话里。
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
DefensesarXiv 2607.25297Jul 28
MTGuard: Hybrid Analysis for Secure MCP Tool Calls in LLM Agents
Proposes MTGuard, which blocks unsafe tool calls by comparing MCP call declarations with execution traces.
arXiv
2607.25297
Published
Jul 28
Layer
Application layer
Setting
AI Agent
Evaluated models
DeepSeek-V4-Flash, DeepSeek-V4-Pro, GPT-5.6 Luna
- DefensesMonitoring and auditing
- AttacksPoisoning and backdoors
- ComponentMCP and skills
Paper analysisRead analysis
Evaluation and benchmarksarXiv 2607.20121Jul 22
OpenSkillRisk: Evaluating the safety of agents using real-world high-risk third-party skills
构建 OpenSkillRisk 评测编程 Agent 使用真实高风险第三方技能的安全性
arXiv
2607.20121
Published
Jul 22
Layer
Application layer
Setting
coding agent
Evaluated models
GPT-5.1 Codex Mini, GPT-5.3 Codex, GPT-5.4 and others13
- AttacksPoisoning and backdoors
- ComponentMCP and skills
Paper analysisRead analysis

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