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Impact：Output manipulation Layer：Application layer System component：RAG System component：Permissions and sandboxing System component：Embeddings Clear all

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

AttacksarXiv 2610.11932Oct 8
A Fudan team measures the citation fragility of AI search: ordinary posts can enter citations and answer text
Measures citation fragility in AI search, demonstrating that ordinary public posts can enter citations and answers.
arXiv
2610.11932
Published
Oct 8
Layer
Application layer
Setting
LLM applications
Evaluated models
Grok, Doubao, ChatGPT and others10
- AttacksPoisoning and backdoors
- ComponentRAG
AbstractThe authors claim the paper quantifies vulnerabilities in AI search caused by citation preferences and low posting thresholds; tests show public web posts can penetrate AI citations, and they call for auditing the citation supply chain.
Paper analysisRead analysis
DefensesarXiv 2610.05826Oct 5
研究者提出临时可见性协议，限制持续摄入 RAG 向量库的投毒暴露
提出临时可见性协议，限制持续摄入 RAG 向量库的投毒暴露
arXiv
2610.05826
Published
Oct 5
Layer
Application layer
Setting
LLM applications
- DefensesInstruction–data separation
- AttacksPoisoning and backdoors
- ComponentRAG
Abstract用截止期限制未核验可见时长。
这篇工作给持续摄入的 RAG 向量库一个失败关闭的临时可见性协议，把协议能限制的未核验暴露和依赖检测器的中毒暴露分开。
Paper analysisRead analysis
DefensesarXiv 2610.04699Oct 3
CoVer：用干预检验为 Agent 构造可判定规则边界
提出 COVER，用干预门判定 Agent 规则谓词能否自动执行
arXiv
2610.04699
Published
Oct 3
Layer
Application layer
Setting
AI Agent
Evaluated models
Claude Sonnet, Claude Opus, GPT-4o and others5
- DefensesPermissions and approval
- ComponentPermissions and sandboxing
Abstract自可判定不能向模型索取。
这篇工作测的是智能体验证器在检查之前的分流：外部规则里的哪条谓词能用固定过程解决，哪条必须交给评审。
Paper analysisRead analysis
AttacksarXiv 2610.02373Oct 2
HDI 攻击：篡改 GraphRAG 辅助结构可致 88–94% 攻击成功率
提出 HDI 攻击以篡改 GraphRAG 辅助结构破坏检索
arXiv
2610.02373
Published
Oct 2
Layer
Application layer
Setting
LLM applications
Evaluated models
Microsoft GraphRAG, HippoRAG2
- AttacksPoisoning and backdoors
- ComponentRAG
Abstract论文形式化了 GraphRAG 辅助模式级实体攻击面，提出 HDI 攻击并验证其攻击效果。
Paper analysisRead analysis
Evaluation and benchmarksarXiv 2609.39146Sep 30
MADBench：多智能体辩论安全性评测基准发布
提出 MADBench，评测多智能体辩论是吸收还是放大对抗影响
arXiv
2609.39146
Published
Sep 30
Layer
Application layer
Setting
Multi-agent systems
Evaluated models
gpt-4o, GPT-5, GPT-6 Astra
- AttacksPrompt injection
- ComponentRAG
AbstractMADBench 显示辩论能吸收部分准确率攻击，同时放大未授权读写。
MADBench 是一个评测多智能体辩论安全性的基准，用来看攻击是被辩论吸收还是被放大。
Paper analysisRead analysis
AttacksarXiv 2609.35155Sep 28
LENS：检索增强生成中集合级投毒的整体危害大于各部分之和
提出 LENS，构造集合级 RAG 语料投毒以导向预设答案
arXiv
2609.35155
Published
Sep 28
Layer
Application layer
Setting
LLM applications
Evaluated models
Qwen3.6-35B-A3B, Llama-3.1-70B-Instruct, DeepSeek-V4-Pro
- AttacksPoisoning and backdoors
- TechniqueAutomated search
- ComponentRAG
Paper analysisRead analysis
Evaluation and benchmarksarXiv 2609.37501Sep 28
RegLLM：面向受监管智能体 AI 的有限自主性诊断测试框架
提出 REGLLM 框架，评测受监管智能体何时作答或升级
arXiv
2609.37501
Published
Sep 28
Layer
Application layer
Setting
AI Agent
Evaluated models
Qwen2.5-3B
- RiskDangerous agent actions
- ComponentPermissions and sandboxing
AbstractREGLLM 把升级对错做成可核验信号，并在 smoke 规模上看到适配器方向被运行方差淹没。
REGLLM 是诊断有界自主的框架，示例是 UK FCA 合规智能体。作者把它做成 smoke 规模演示，而不是完整基准验证。
Paper analysisRead analysis
AttacksarXiv 2609.37468Sep 26
论文提出针对 Agentic RAG 的检索器后门攻击与 DOU 隐藏方法
提出检索器后门攻击操纵智能体搜索，并用 DOU 逃避检测
arXiv
2609.37468
Published
Sep 26
Layer
Application layer
Setting
AI Agent
Evaluated models
E5, Contriever-MSMARCO
- AttacksPoisoning and backdoors
- TechniqueDormant triggers
- ComponentRAG
Abstract论文展示了通过恶意检索器操纵智能体多轮搜索并利用诱饵重塑表征隐蔽后门的可行性与系统风险。
Paper analysisRead analysis
Evaluation and benchmarksarXiv 2609.31342Sep 25
Research reveals outdated document poisoning: RAG retrieval can make models abandon originally correct answers
评测 RAG 中过期文档推翻模型原本正确回答的现象
arXiv
2609.31342
Published
Sep 25
Layer
Application layer
Setting
LLM applications
Evaluated models
GPT-4o, GPT-4.1, Claude-Opus-4.5 and others13
- ComponentRAG
Abstract论文评测了陈旧检索推翻正确知识的中毒现象，并分析了其内部机制与防御局限。
这篇论文是对检索增强生成（RAG）中“陈旧文档中毒”现象的实证与机理评估研究。
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 2609.11757Sep 11
Researchers disclose a Whisper prompt injection attack on the AP2 payment protocol and propose the A-VIP defense
提出 AP2 支付协议的 Whisper 攻击与 A-VIP 绑定防御
arXiv
2609.11757
Published
Sep 11
Layer
Application layer
Setting
AI Agent
Evaluated models
gemini-2.5-flash-lite, gemini-3.1-flash-lite, gemini-3-flash-preview and others15
- DefensesPermissions and approval
- AttacksPrompt injection
- ComponentPermissions and sandboxing
Abstract论文揭示了 AP2 协议决策层受操纵的风险，提出结构化与权能绑定防御 A-VIP，并发布评测基准。
Paper analysisRead analysis
DefensesarXiv 2609.04159Sep 4
Sentinel-RL：将拓扑推理从 LLM 智能体中卸载到安全运营中心
提出 Sentinel-RL，将拓扑处置从 LLM 卸载到受约束图策略
arXiv
2609.04159
Published
Sep 4
Layer
Application layer
Setting
LLM applications
Evaluated models
HetGAT, PPO
- DefensesPermissions and approval
- RiskDangerous agent actions
- ComponentPermissions and sandboxing
AbstractSentinel-RL 用图编码器与 PPO 承担拓扑决策，LLM 负责叙述与门控，并在 LANL 上报告检测与时延。
Sentinel-RL 是面向 SOC 的神经符号架构：拓扑决策离开 LLM，改由认证图上的 HetGAT 与 PPO 完成。
Paper analysisRead analysis
AttacksarXiv 2609.02774Sep 3
CodePoisonRAG：针对检索增强代码生成的知识投毒攻击
提出 CodePoisonRAG，对检索增强代码生成的知识库投毒以植入漏洞
arXiv
2609.02774
Published
Sep 3
Layer
Application layer
Setting
LLM applications
Evaluated models
Qwen 3.5 9B, Code Llama 13B, DeepSeek-Coder-V2 16B
- AttacksPoisoning and backdoors
- TechniqueDormant triggers
- ComponentRAG
AbstractCodePoisonRAG 展示了 RACG 外部知识库的新攻击面，在较低投毒率下可定向诱发指定漏洞并部分抵御防御。
Paper analysisRead analysis
Evaluation and benchmarksarXiv 2609.02316Sep 2
Counter-GEO-Bench：现有护栏难挡 GEO 虚假信息
构建 COUNTER-GEO-BENCH，评测生成式搜索中的 GEO 虚假信息防御
arXiv
2609.02316
Published
Sep 2
Layer
Application layer
Setting
LLM applications
Evaluated models
Gemma-4-31B-IT, Qwen-3.5-35B-A3B, Llama-4-Scout-17B-16E and others8
- DefensesDetection and filtering
- AttacksPrompt injection
- ComponentRAG
Abstract论文构建了针对 GEO 虚假信息的首个防御基准，揭示通用护栏的失效与反作用，并提出了有效的轻量对比检测基线。
Paper analysisRead analysis
AttacksarXiv 2609.01325Sep 1
VerTox：用可验证奖励引导的强化学习对神经排序模型实施语料投毒
提出 VerTox，用可验证奖励强化学习生成误导文档并投毒检索语料
arXiv
2609.01325
Published
Sep 1
Layer
Application layer
Setting
LLM applications
Evaluated models
SimLM-base, BGE-base, Cohere-embed-english-v3.0 and others8
- AttacksPoisoning and backdoors
- TechniqueAutomated search
- ComponentRAG
AbstractVerTox 以可验证奖励微调小 LLM，生成能抬高排序并腐蚀事实的投毒文档。
VerTox 用可验证奖励把小 LLM 微调成语料投毒生成器，用来探测神经排序器在注入文档下的暴露面。
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
Analysis and theoryarXiv 2609.00060Aug 30
论文用 Tamarin 形式化分析 x402、MPP、ACP、AP2 四个智能体支付协议
用 Tamarin 形式化分析智能体支付协议的跨阶段安全关系
arXiv
2609.00060
Published
Aug 30
Layer
Application layer
Setting
AI Agent
Evaluated models
x402, MPP, ACP and others4
- ComponentPermissions and sandboxing
Paper analysisRead analysis
AttacksarXiv 2608.29381Aug 30
Researchers propose five categories of safety failures in agent checkpoint rollback and implement three attacks on Hermes, Cline, and LangGraph
提出利用检查点回滚破坏 Agent 执行连续性的攻击
arXiv
2608.29381
Published
Aug 30
Layer
Application layer
Setting
AI Agent
- ComponentPermissions and sandboxing
Abstract论文系统研究了智能体 C/R 的安全性，分析了合法回滚破坏执行连续性的机理，并实证评估了其普遍性与危害。
Paper analysisRead analysis
AttacksarXiv 2608.04565Aug 5
Researchers propose Breadcrumbing long-range attack that can hijack the evidence chain of DeepResearch-style search agents
提出权威链劫持与轨迹引导策略演化，劫持搜索 Agent 的证据链
arXiv
2608.04565
Published
Aug 5
Layer
Application layer
Setting
web agent
Evaluated models
Qwen3.5-9B, Gemma4-31B, DeepResearch and others7
- AttacksPrompt injection
- TechniqueAutomated search
- ComponentRAG
Abstract论文揭示了多步搜索智能体在受限中间人操纵下的脆弱性，提出 ACH 策略与 TGSE 演化方法并完成系统验证。
Paper analysisRead analysis
Evaluation and benchmarksarXiv 2607.20891Jul 23
MisKnow-Agent 评测
用 MisKnow-Agent 评测深度研究智能体是否采纳误导文档结论
arXiv
2607.20891
Published
Jul 23
Layer
Application layer
Setting
web agent
Evaluated models
DeerFlow, WebThinker, Gemini Deep Research and others6
- AttacksPrompt injection
- ComponentRAG
Abstract论文通过 MisKnow-Agent 框架评估发现长程研究智能体易采纳误导性知识，且现有防御难以完全消除该现象。
Paper analysisRead analysis

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