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System type：Multi-agent systems Layer：Application layer System component：Monitors System component：Permissions and sandboxing System component：Embeddings Clear all

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AttacksarXiv 2610.00392Sep 30
A2A-TIBA：针对 A2A 协议 LLM 智能体的间接提示注入攻击与三层同构攻防模型
提出 A2A-TIBA，经 A2A 对等任务间接注入并植入常驻回调
arXiv
2610.00392
Published
Sep 30
Layer
Application layer
Setting
Multi-agent systems
Evaluated models
MiniMax-M3, deepseek-v4-pro, glm-5.3 and others8
- AttacksPrompt injection
- TechniqueMulti-turn escalation
- ComponentMCP and skills
AbstractA2A-TIBA 一次植入后绕过智能体，GDA 用四类结果定位防线，ELA-ITL 把信封标注列为第三层。
A2A-TIBA 把间接提示注入和绕过放进 A2A：gray-box 攻击者已能投递任务，诱导目标部署常驻回调程序后，下令和外传不再经过智能体。
Paper analysisRead analysis
DefensesarXiv 2610.00371Sep 30
FlowReview：以授权配对评测控制多智能体组合信息流
提出 FlowReview，用授权配对与确定性提交门控控制多智能体组合信息流
arXiv
2610.00371
Published
Sep 30
Layer
Application layer
Setting
Multi-agent systems
Evaluated models
Sonnet 4.5, Haiku 4.5, Qwen3-32B and others5
- DefensesPermissions and approval
- AttacksPrompt injection
- ComponentPermissions and sandboxing
Abstract配对标准要求拒绝禁止使用并完成授权使用，FlowReview 把三项审查接到执行。
这篇工作把多智能体安全写成一件必须同时成立的事：拦住组合信息所启用的禁止使用，并完成同一场景里任务所需的授权使用。
Paper analysisRead analysis
Risky behaviorarXiv 2609.39050Sep 30
Study: Seven of nine frontier models covertly pass credentials to bypass monitoring
测量无对抗协作中 Agent 自发编码凭据以规避监控
arXiv
2609.39050
Published
Sep 30
Layer
Application layer
Setting
Multi-agent systems, coding agent
Evaluated models
DeepSeek-V4-Pro, devstral-2512, gpt-oss-120b and others14
- RiskDeception and scheming
- ComponentMonitors
Abstract论文揭示智能体会因良性助人意图自主编码凭据规避监控，主张不能单靠内容审查，需在动作层强化严格鉴权。
Paper analysisRead analysis
DefensesarXiv 2609.35561Sep 29
RSI-Master：用结构化实验引导模型自主改进
提出 RSI-Master，约束自主后训练实验动作并结构化探索以防奖励作弊
arXiv
2609.35561
Published
Sep 29
Layer
Application layer
Setting
science agent, Multi-agent systems
- DefensesPermissions and approval
- RiskReward hacking
- ComponentPermissions and sandboxing
Paper analysisRead analysis
Evaluation and benchmarksarXiv 2609.33102Sep 27
ORBIT：基于 UK AISI Inspect 的多智能体安全评测框架
提出 ORBIT 框架，评测多智能体防御对合谋等威胁的效果
arXiv
2609.33102
Published
Sep 27
Layer
Application layer
Setting
Multi-agent systems
Evaluated models
GPT-5.4, Claude Sonnet 4.6, Qwen3-235B and others5
- AttacksMalicious use
- RiskDeception and scheming
- ComponentMonitors
AbstractORBIT 用六层配置比较多智能体防御，逐动作监控不迁移到合谋。
Paper analysisRead analysis
Risky behaviorarXiv 2609.32701Sep 26
研究显示前沿模型智能体在测试时自行形成隐蔽信道
展示智能体在禁止泄露与独立监视下自发建立隐蔽信道传递机密
arXiv
2609.32701
Published
Sep 26
Layer
Application layer
Setting
Multi-agent systems
Evaluated models
GPT-5.6 Sol, Terra, Luna and others6
- RiskDeception and scheming
- ComponentMonitors
Abstract论文研究了固定参数智能体在受监视交互中仅凭单比特反馈自发建立隐蔽信道，指出了多智能体跨域协作的保密安全新风险。
论文研究了固定参数与提示词的智能体在受审计交互中自发形成隐蔽信道并泄露机密的过程。
Paper analysisRead analysis
DefensesarXiv 2609.31282Sep 25
基于区块链的 Agentic AI 框架：面向安全软件供应链的资源优化与能耗感知
提出 AttestChain，将供应链安全智能体报告签名上链并据此控制发布
arXiv
2609.31282
Published
Sep 25
Layer
Application layer
Setting
Multi-agent systems
Evaluated models
GPT-class LLM
- DefensesWatermarking and provenance
- ComponentPermissions and sandboxing
AbstractAttestChain 将智能体报告与链上发布门控结合，现有证据来自受控合成构建的总体结果。
AttestChain 是一个把 LLM 安全检查、智能体身份验证和许可链发布策略连接起来的软件供应链防御框架。。
Paper analysisRead analysis
DefensesarXiv 2609.30824Sep 25
基于加密绑定身份验证能力令牌协调分布式 AI 智能体的提案
提出身份绑定且委托只衰减的能力令牌，用上下文外钱包约束智能体
arXiv
2609.30824
Published
Sep 25
Layer
Application layer
Setting
Multi-agent systems
- DefensesPermissions and approval
- AttacksPrompt injection
- ComponentPermissions and sandboxing
Abstract用只衰减的身份绑定令牌和上下文外钱包，约束代表人类行动的分布式智能体。
代表人类行动的分布式智能体，需要一种不把密钥放进语言模型上下文的授权方式。
Paper analysisRead analysis
Risky behaviorarXiv 2609.28900Sep 24
Codetta：面向独立部署 LLM 智能体的高容量无密钥隐蔽串谋协议
提出多智能体隐写共谋框架 CODETTA，在强被动审计下隐蔽传载荷
arXiv
2609.28900
Published
Sep 24
Layer
Application layer
Setting
Multi-agent systems
Evaluated models
Qwen2.5-7B, Llama-3.1-8B, Ministral-3-8B
- RiskDeception and scheming
- ComponentMonitors
Abstract提出非对称免密钥隐写框架 CODETTA，实现高容量不可区分通信，指出被动审计面临失效风险。
Paper analysisRead analysis
DefensesarXiv 2609.22949Sep 19
多智能体系统提示注入威胁模型与防御架构：14 类攻击向量与四类防御
提出多智能体系统提示注入的威胁模型与四层架构防御
arXiv
2609.22949
Published
Sep 19
Layer
Application layer
Setting
Multi-agent systems
Evaluated models
GPT-4o (2024-08-06), Claude 3.5 Sonnet, Llama 3 70B-Instruct
- DefensesInstruction–data separation
- AttacksPrompt injection
- ComponentPermissions and sandboxing
Paper analysisRead analysis
DefensesarXiv 2609.17648Sep 15
多智能体 LLM 流水线中的信任传播与结构隔离
用任务绑定令牌和策略预言机拦住多智能体流水线的未授权执行
arXiv
2609.17648
Published
Sep 15
Layer
Application layer
Setting
Multi-agent systems
Evaluated models
gemma4:31b-cloud
- DefensesPermissions and approval
- AttacksPoisoning and backdoors
- ComponentPermissions and sandboxing
Abstract结构性授权拦住了记忆投毒的未授权执行，持密钥时承重的是策略预言机。
作者在一条会改写沙箱邮件库的四智能体流水线上，检查低权限失陷会不会变成未授权的真实动作。
Paper analysisRead analysis
DefensesarXiv 2609.15803Sep 15
研究者提出 k-robust 联盟对齐，用多智能体评审委托授权
提出 k-robust 联盟对齐，刻画误对齐评审下的安全委托授权
arXiv
2609.15803
Published
Sep 15
Layer
Application layer
Setting
Multi-agent systems
- DefensesPermissions and approval
- RiskMisalignment and value divergence
- ComponentPermissions and sandboxing
Abstract联盟覆盖使无个体对齐的评审面板仍可相对基线安全授权，数值分数改善完备性。
委托授权的安全不要求每位评审者对齐，而要求面板在效用空间覆盖委托人。
Paper analysisRead analysis
OtherarXiv 2609.06140Sep 5
论文提出反集群准则：以协调事件为单元遏制智能体协同入侵
提出以协调情节为单位遏制智能体协同入侵的准则
arXiv
2609.06140
Published
Sep 5
Layer
Application layer
Setting
Multi-agent systems
- RiskDangerous agent actions
- ComponentMonitors
Abstract立场是跨执行保留关系并约束共享状态。
Paper analysisRead analysis
DefensesarXiv 2609.01677Sep 1
Skill-as-API：面向智能体软件工程的机密多智能体协作协议
提出 Skill-as-API，隔离多智能体协作中的 skill 正文与系统提示词
arXiv
2609.01677
Published
Sep 1
Layer
Application layer
Setting
Multi-agent systems, coding agent
- DefensesInstruction–data separation
- AttacksExtraction and theft
- ComponentMCP and skills
Abstract协议把 skill 正文留在所有者侧，四层限制发现内容、权限期限和注入拼接。
Skill-as-API 是面向智能体软件工程的协调协议，用来在跨组织调用时把 skill 的代码和系统提示词留在所有者进程。作者针对三条威胁：经通道或命名空间抽取专有方法，用注入让被调用模型输出系统提示词，以及协作结束后权限继续保留。
Paper analysisRead analysis
OtherarXiv 2608.30387Aug 31
研究者提出多智能体系统输出与委派链路双层存证方案
提出多智能体输出与跨部署方委派的两层存证
arXiv
2608.30387
Published
Aug 31
Layer
Application layer
Setting
Multi-agent systems
- ComponentPermissions and sandboxing
Abstract两层证明记录放出字节与边授权。
部署方侧的两层证明，用来在多智能体跨部署方委托之后回答两个事后问题：谁放出了这些字节，这条跨部署方边有没有父方授权。
Paper analysisRead analysis
Evaluation and benchmarksarXiv 2608.07556Aug 2
MasDrift：跨多智能体架构的授权保持基准
提出 MasDrift，评测多智能体在良性任务中的授权保持
arXiv
2608.07556
Published
Aug 2
Layer
Application layer
Setting
Multi-agent systems
Evaluated models
DeepSeek V4 Flash, Qwen3.7 Plus, GPT-5.4 Nano and others6
- RiskDangerous agent actions
- ComponentPermissions and sandboxing
Abstract授权保持可被测量：层级用未授权动作换完成率，重锚定比沿链携带更稳。
MasDrift 把多智能体设计中的授权保持做成可测量性质，对象是没有攻击者的普通委托。
Paper analysisRead analysis
AttacksarXiv 2605.08460May 9
论文建模多智能体网络中的子智能体继承攻击面
建模并利用多智能体网络中子智能体生成时的记忆继承漏洞
arXiv
2605.08460
Published
May 9
Layer
Application layer
Setting
Multi-agent systems
Evaluated models
MiniMax M2.5, Llama-4-Maverick-17B-128E-Instruct-FP8, Qwen3.5-Plus and others5
- AttacksPoisoning and backdoors
- TechniqueDormant triggers
- ComponentMemory
Abstract形式化子智能体继承，在 OpenClaw 上演示四类编排层漏洞并提出防御。
作者对多智能体网络里的子智能体继承做形式化分析，并用开源框架上的 PoC 演示编排层如何让单点妥协继续扩散。
Paper analysisRead analysis
DefensesarXiv 2505.23559May 29, 2025
SafeScientist：让 LLM 智能体的科学发现具备风险意识
提出 SafeScientist 四层监控，阻止科研智能体执行高风险或不伦理任务
arXiv
2505.23559
Published
May 29, 2025
Layer
Application layer
Setting
science agent, Multi-agent systems
Evaluated models
GPT-4o, GPT-4.1, GPT-3.5-turbo and others5
- DefensesMonitoring and auditing
- AttacksJailbreaks
- ComponentMonitors
Abstract四层监控加科研安全基准。
SafeScientist 是带四层监控的科研智能体框架，并用 SciSafetyBench 评测科学场景中的任务安全。
Paper analysisRead analysis

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