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Attack type：Detection evasion Attack surface / entry point：User input Attack surface / entry point：Tool responses Attack surface / entry point：Code repositories and dependencies Layer：Application layer Clear all

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

AttacksarXiv 2610.12292Oct 9
The paper proposes an option channel attack: changing one option label can make an agent guardrail allow a prohibited operation
Proposing an option channel attack that renames option labels so that agent guardrails allow prohibited operations
arXiv
2610.12292
Published
Oct 9
Layer
Application layer
Setting
LLM applications
Attacker
Black-box
Evaluated models
LAYA-TD, LAYA-EN, LAYA-ML and others5
- AttacksDetection evasion
- ComponentGuardrails and judges
AbstractThe authors' evaluation indicates that typed models should not serve as final safety arbiters; they are susceptible to off-policy text and option name manipulation, and confidence filtering cannot resist attacks.
Paper analysisRead analysis
AttacksarXiv 2610.10742Oct 8
BRANCH 方法绕过 6 套多扫描器护栏系统
提出 BRANCH 方法，用分支搜索绕过多扫描器护栏
arXiv
2610.10742
Published
Oct 8
Layer
Application layer
Setting
LLM applications
Attacker
Black-box
Evaluated models
Meta Llama Guard 3 8B, Meta Llama Guard 7B, Meta Llama Guard 3 1B and others18
- AttacksDetection evasion
- TechniqueAutomated search
- ComponentGuardrails and judges
Paper analysisRead analysis
DefensesarXiv 2610.09793Oct 7
用时序逻辑监控工具 Agent
提出 MFOTL 离线时序验证以监控工具 Agent 的危险动作链
arXiv
2610.09793
Published
Oct 7
Layer
Application layer
Setting
AI Agent
Attacker
Black-box
- DefensesMonitoring and auditing
- AttacksPrompt injection
- ComponentMonitors
Abstract形式化验证可有效识别多步攻击，但其有效性高度依赖轨迹的可信历史记录。
这篇论文对工具调用大语言模型智能体的安全监控进行了形式化时序验证研究。
Paper analysisRead analysis
DefensesarXiv 2610.08668Oct 7
SBW：面向 LLM 智能体的语义行为水印方法
提出 SBW，为 LLM Agent 轨迹做抗改写与伪造的语义行为水印
arXiv
2610.08668
Published
Oct 7
Layer
Application layer
Setting
AI Agent
Evaluated models
Qwen2.5-3B-Instruct, LLaMA-3.2-3B, Qwen2.5-7B and others5
- DefensesWatermarking and provenance
- AttacksDetection evasion
AbstractSBW 在语义簇上做溯源水印，改写检测高于精确符号，链式重放仍开放。
SBW 是免训练的智能体行为水印，把所有者标识放在离散动作选择上，而不是输出 token。
Paper analysisRead analysis
DefensesarXiv 2610.02432Oct 2
论文提出 LLM 输入扰动鲁棒性度量，并发布 ASA 攻击与 AttestMCP 防护
提出 ASA 与 AttestMCP，度量并降低 LLM 对输入序列扰动的敏感
arXiv
2610.02432
Published
Oct 2
Layer
Application layer
Setting
LLM applications, AI Agent
Attacker
Black-box
Evaluated models
Gemma-3-27B-Instruct, Gemma-3-4B-Instruct, Llama-3.2-3B-Instruct and others12
- DefensesDetection and filtering
- AttacksDetection evasion
- ComponentGuardrails and judges
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
AttacksarXiv 2609.29130Sep 24
ClaimMirage：域名中的自我声明如何改变 LLM 威胁判断
提出 ClaimMirage，以域名自述声称改变 LLM 威胁告警判断
arXiv
2609.29130
Published
Sep 24
Layer
Application layer
Setting
LLM applications
Evaluated models
Llama 3.3 70B Instruct-Turbo, Gemma 3 4B it, Gemma 3 12B it and others5
- AttacksDetection evasion
- ComponentGuardrails and judges
Abstract作者称自述声称可增减告警。
Paper analysisRead analysis
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
DefensesarXiv 2608.06422Aug 6
CMU 研究：分片判断可避免 LLM 监督失效并抵御对抗利用
提出分片监督，将评判标准分配给独立调用以抵御展示攻击
arXiv
2608.06422
Published
Aug 6
Layer
Application layer
Setting
LLM applications
Attacker
Black-box
Evaluated models
Claude Opus 4.8, Claude Sonnet 4.6, Claude Opus 4.6 and others4
- DefensesDetection and filtering
- AttacksDetection evasion
- ComponentGuardrails and judges
Abstract论文揭示决策负载是大模型监督的独立瓶颈，提出分片与辩论机制有效分离注意力与平衡证据，在多项高难度基准上实现稳健评判。
本文系统研究了大语言模型在执行多标准监督与评判时的决策负载瓶颈及其安全风险。
Paper analysisRead analysis
DefensesarXiv 2608.12361Jul 5
基于搜索增强 LLM 的中文新词毒性共识检测框架 SeTox
提出 SeTox 检索增强框架，检测中文新词的隐性毒性
arXiv
2608.12361
Published
Jul 5
Layer
Application layer
Setting
LLM applications
Evaluated models
SeTox-Qwen2.5-7B
- DefensesDetection and filtering
- AttacksDetection evasion
- ComponentGuardrails and judges
AbstractSeTox 用检索把公共共识接入静态 LLM，以检测中文毒性新词。
SeTox 研究中文新词上的隐性毒性检测：词表加检索增强，使静态 LLM 在不重训练的情况下利用公开网页上下文。
Paper analysisRead analysis
AttacksarXiv 2605.22258May 21
CITA：面向中文隐式毒性的攻击与防御数据生成框架
提出 CITA 三阶段框架，生成可绕过毒性检测器的中文隐式毒性文本
arXiv
2605.22258
Published
May 21
Layer
Application layer
Setting
LLM applications
Evaluated models
Tencent, Baidu, Gemini 3.1 Pro and others11
- AttacksDetection evasion
- TechniqueEncoding and obfuscation
- ComponentGuardrails and judges
Paper analysisRead analysis
AttacksarXiv 2602.00979Feb 1
GradingAttack: Revealing Security Vulnerabilities in LLM-Based Educational Grading Agents
提出 GradingAttack，用梯度后缀与角色扮演操纵教育评分智能体判定
arXiv
2602.00979
Published
Feb 1
Layer
Application layer
Setting
LLM applications
Evaluated models
Qwen2.5-7B, Qwen2.5-7B-Instruct, Qwen2.5-14B-Instruct and others8
- AttacksDetection evasion
- TechniqueGradient and representation optimization
Paper analysisRead analysis
AttacksarXiv 2602.02569Jan 31
DECEIVE-AFC：针对检索式 LLM 事实核查系统的对抗性主张攻击
提出 DECEIVE-AFC，以声明改写诱导搜索增强事实核查误判
arXiv
2602.02569
Published
Jan 31
Layer
Application layer
Setting
LLM applications
Attacker
Black-box
Evaluated models
HiSS, LEMMA, DEFAME and others4
- AttacksDetection evasion
- TechniqueAutomated search
- ComponentRAG
Paper analysisRead analysis

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