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Oct 13 · Tuesday

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System type：LLM applications System type：coding agent System type：Embodied systems and robotics Attack surface / entry point：Web pages and interfaces Attack surface / entry point：Tool responses Clear all

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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 2610.11932Oct 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
Evaluation and benchmarksarXiv 2610.07639Oct 6
HarnessSecurity-Bench horizontally evaluates the security mechanisms of six coding agent frameworks.
评测编码智能体 harness 安全机制在对抗任务中的防护效果
arXiv
2610.07639
Published
Oct 6
Layer
Application layer
Setting
coding agent
- AttacksPrompt injection
- ComponentPermissions and sandboxing
Paper analysisRead analysis
DefensesarXiv 2610.05163Oct 4
Researchers construct segmented prompt injection on Claude Code and Codex and release a boundary action audit benchmark
提出 PAA 方法，在边界动作前审计长流程智能体的分阶段提示注入
arXiv
2610.05163
Published
Oct 4
Layer
Application layer
Setting
coding agent
Evaluated models
Claude Code (v2.1.172, Claude Sonnet 5), Codex CLI (v0.144.0, GPT-5.5)
- DefensesMonitoring and auditing
- AttacksPrompt injection
- ComponentMonitors
Abstract论文针对长流程注入提出边界动作审计与 PAA，在保持低误阻的同时实现高拦截率。
本研究针对长流程智能体在执行任务时面临的分阶段间接提示注入威胁，提出了在动作生效前进行拦截的边界动作审计框架与路径对齐归因方法。
Paper analysisRead analysis
DefensesarXiv 2610.02869Oct 2
AgentTrap：面向自主渗透测试 Agent 的有状态反馈欺骗蜜罐
提出 AgentTrap 有状态蜜罐，欺骗并反击自主渗透测试 Agent
arXiv
2610.02869
Published
Oct 2
Layer
Application layer
Setting
coding agent
Evaluated models
AIDA, Claude Code, PentestGPT and others8
- AttacksMalicious use
Paper analysisRead analysis
DefensesarXiv 2609.35659Sep 29
Tracekit：面向自主编码 Agent 的防篡改意图-推理-动作审计系统
提出 Tracekit，审计编码 Agent 的意图、推理与动作并检测账本篡改
arXiv
2609.35659
Published
Sep 29
Layer
Application layer
Setting
coding agent
Evaluated models
Claude Code (claude -p, version 2.1), 独立评审（同一 CLI，无工具）
- DefensesMonitoring and auditing
- AttacksPrompt injection
- RiskDangerous agent actions
- ComponentMonitors
AbstractTracekit 把意图、自述和动作写入可锚定的哈希链。
Tracekit 是无第三方依赖的编码智能体审计层：把人类请求、模型自述和已执行动作并排写入可外部锚定的哈希链，执行前用正则门，事后用规则和独立模型互查。
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
Analysis and theoryarXiv 2609.23215Sep 20
研究审计 Active Inference Agent 的 LLM 解释器失败模式
审计 Active Inference Agent 上 LLM 解释器的监督叙述失败
arXiv
2609.23215
Published
Sep 20
Layer
Application layer
Setting
LLM applications
Evaluated models
GPT-4o, Claude-3-Opus, Gemini
- AttacksPrompt injection
- RiskMisalignment and value divergence
Abstract三组触发下解释流畅但错误，所提缓解都未被评估。
作者审计的是挂在智能体上的运行时解释器，而不是智能体本身。操作员读到的是信念与动作的自然语言叙述。作者要问哪些可复现触发会让这段叙述失败，以及失败痕迹是什么样。
Paper analysisRead analysis
DefensesarXiv 2609.21088Sep 18
Provenance-Aware Transformers：用来源感知架构分离可信边界以防御间接提示注入
提出 Provenance-Aware Transformers，隔离不可信来源防御间接提示注入
arXiv
2609.21088
Published
Sep 18
Layer
Application layer
Setting
LLM applications
Evaluated models
SmolLM2-360M-Instruct, LLaMA-3-8B-Instruct, Qwen2.5-7B-Instruct and others4
- DefensesInstruction–data separation
- AttacksPrompt injection
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 2609.10707Sep 10
面向 AI-SOC 的神经符号防御框架：用 SIEM 解码器与 NeMo Guardrails 阻断日志投毒提示注入
提出神经符号纵深架构，阻断 AI-SOC 的日志投毒与间接提示注入
arXiv
2609.10707
Published
Sep 10
Layer
Application layer
Setting
LLM applications
Evaluated models
Gemma 3 (12B)
- DefensesDetection and filtering
- AttacksPrompt injection
- ComponentGuardrails and judges
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
Evaluation and benchmarksarXiv 2609.05535Sep 2
Mind2Web-Injection：面向网页 Agent 视觉提示注入护栏的证据对齐评测
提出 Mind2Web-Injection 评测网页 Agent 视觉注入护栏
arXiv
2609.05535
Published
Sep 2
Layer
Application layer
Setting
LLM applications
Evaluated models
GPT-5.6-luna, Qwen3-VL-32B, Qwen3-VL-8B and others6
- DefensesDetection and filtering
- AttacksPrompt injection
- ComponentGuardrails and judges
Abstract作者称检测、定位和反事实响应在六个 VLM 上可分开。
Mind2Web-Injection 用来检查网页截图护栏的判决是否对齐到该用的画面证据。。
Paper analysisRead analysis
Evaluation and benchmarksarXiv 2608.16824Aug 18
GEO-Flag：检测与测量面向生成式引擎优化的网页内容
提出 GEOFlagBench 与 IPT，检测并测量生成式引擎优化网页
arXiv
2608.16824
Published
Aug 18
Layer
Application layer
Setting
LLM applications
Evaluated models
ModernBERT-base, Qwen3-0.6B, Gemini-3.5-flash and others11
- DefensesDetection and filtering
- ComponentGuardrails and judges
AbstractGEOFlagBench 与 IPT 用于检测 GEO 页，并估计真实检索中的占比与引用可核验性。
GEO-Flag 把页面级 GEO 检测做成可评测任务，并在发布的检索结果上估计被判为 GEO 的页面占比。
Paper analysisRead analysis
DefensesarXiv 2608.02683Aug 3
S³：用多阶段防御提升 LLM 智能体安全
提出 S³，用 guard agent 编排阶段安全技能防御智能体多阶段风险
arXiv
2608.02683
Published
Aug 3
Layer
Application layer
Setting
Embodied systems and robotics
Evaluated models
DeepSeek-V4-Pro, DeepSeek-V4-Flash
- DefensesMonitoring and auditing
- AttacksPoisoning and backdoors
- RiskDangerous agent actions
- ComponentMonitors
Paper analysisRead analysis
AttacksarXiv 2607.11698Jul 13
AHA 用自动研究循环发现生产 Agent 漏洞概念
提出 AHA 自动科研循环，发现生产 Agent 的可复用漏洞概念
arXiv
2607.11698
Published
Jul 13
Layer
Application layer
Setting
coding agent
Attacker
Black-box
Evaluated models
Minimax-M2.7, Kimi-K2.6, Deepseek-V4-Pro and others5
- AttacksPrompt injection
- TechniqueAutomated search
Abstract论文提出基于可证伪科研循环的 AHA 框架，从生产级智能体中挖掘并沉淀漏洞概念图，提升攻击复用率并指导防御加固。
AHA 是一项针对生产级 LLM 智能体自动化红队测试的研究，旨在解决传统方法仅保留具体攻击载荷而缺乏成因解释、导致跨版本复用困难且无法指导修复的问题。
Paper analysisRead analysis
DefensesarXiv 2606.22673Jun 22
Agent MechSuits：面向多轮 CLI Agent 的机制子空间安全引导
提出 Agent MechSuits，对多轮 CLI Agent 做步级检测与子空间转向
arXiv
2606.22673
Published
Jun 22
Layer
Application layer
Setting
coding agent
Evaluated models
LLaMA-3.1-8B, Qwen-2.5-7B, Gemma-2-9B
- DefensesInference-time intervention
- AttacksMalicious use
- ComponentMonitors
Abstract白盒步级探针加稀疏转向可压低三模型恶意动作，同时提高生成崩溃率。
Agent MechSuits 是面向多轮 CLI 智能体的白盒、步级表示防御，并配有可执行轨迹基准 MAS。
Paper analysisRead analysis
AttacksarXiv 2605.24421May 23
研究者提出日志型提示注入攻击，可抑制 SOC 中 LLM 分析助手的恶意日志识别
提出日志基底提示注入，操纵 SOC 分析员的分类、摘要与处置建议
arXiv
2605.24421
Published
May 23
Layer
Application layer
Setting
LLM applications
Evaluated models
gpt-4o-mini
- AttacksPrompt injection
- TechniqueConversation structure manipulation
Abstract在 gpt-4o-mini 上，人格劫持与上下文操纵可改写 SOC 分析输出，直接覆盖在分类上无效。
Paper analysisRead analysis
AttacksarXiv 2602.05484Feb 5
Masked Mirror: Covert Prompt Injection Attacks Against LLM-Based Phishing Detection
提出隐蔽提示注入攻击 LLM 钓鱼检测器，并给出防御 InjectDefuser
arXiv
2602.05484
Published
Feb 5
Layer
Application layer
Setting
LLM applications
Evaluated models
OpenAI GPT-5, xAI Grok 4 Fast (Non-Reasoning), Meta Llama 4 Maverick and others4
- DefensesInstruction–data separation
- AttacksPrompt injection
- TechniqueEncoding and obfuscation
- ComponentGuardrails and judges
Paper analysisRead analysis
Evaluation and benchmarksarXiv 2601.10923Jan 16
Hidden-in-Plain-Text: A benchmark for indirect prompt injection in social network RAG
用 OpenRAG-Soc 评测社交网页 RAG 的间接提示注入与检索投毒
arXiv
2601.10923
Published
Jan 16
Layer
Application layer
Setting
LLM applications
Evaluated models
Llama-3-8B-Instruct, Mistral-7B-Instruct, Qwen2.5-14B and others8
- AttacksPrompt injection
- TechniqueEncoding and obfuscation
- ComponentRAG
Paper analysisRead analysis

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All papers

Attack type

Attack technique

Defense type

Impact

System type

Attack surface / entry point

Layer

System component

The paper proposes an option channel attack: changing one option label can make an agent guardrail allow a prohibited operation

A Fudan team measures the citation fragility of AI search: ordinary posts can enter citations and answer text

HarnessSecurity-Bench horizontally evaluates the security mechanisms of six coding agent frameworks.

Researchers construct segmented prompt injection on Claude Code and Codex and release a boundary action audit benchmark

AgentTrap：面向自主渗透测试 Agent 的有状态反馈欺骗蜜罐

Tracekit：面向自主编码 Agent 的防篡改意图-推理-动作审计系统

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

研究审计 Active Inference Agent 的 LLM 解释器失败模式

Provenance-Aware Transformers：用来源感知架构分离可信边界以防御间接提示注入

研究：跨通道碎片化攻击可绕过 MCP 单通道防御

面向 AI-SOC 的神经符号防御框架：用 SIEM 解码器与 NeMo Guardrails 阻断日志投毒提示注入

Counter-GEO-Bench：现有护栏难挡 GEO 虚假信息

Mind2Web-Injection：面向网页 Agent 视觉提示注入护栏的证据对齐评测

GEO-Flag：检测与测量面向生成式引擎优化的网页内容

S³：用多阶段防御提升 LLM 智能体安全

AHA 用自动研究循环发现生产 Agent 漏洞概念

Agent MechSuits：面向多轮 CLI Agent 的机制子空间安全引导

研究者提出日志型提示注入攻击，可抑制 SOC 中 LLM 分析助手的恶意日志识别

Masked Mirror: Covert Prompt Injection Attacks Against LLM-Based Phishing Detection

Hidden-in-Plain-Text: A benchmark for indirect prompt injection in social network RAG