Translation in progress Some entries still include text in the original language.

Oct 13 · Tuesday

All papers

Found 8 papers

Filter5

Attack type

Prompt injection6 Poisoning and backdoors6

Attack technique

Encoding and obfuscation3 Dormant triggers4

Impact

Output manipulation6

System type

LLM applications4 AI Agent4

Attack surface / entry point

User input16 Web pages and interfaces5 Documents and messages4 Code repositories and dependencies1 Retrieval corpus27 Memory writes3

Layer

Application layer8

System component

MCP and skills12 Memory45 RAG8 Guardrails and judges13 Monitors6 Reasoning chains5 Permissions and sandboxing24 Vision10 Multimodal10

Select any value within a category; different categories must all match. Counts include the other filters you have selected.Another 213papers have no tags yet and are not included in filtered results.

Attack surface / entry point：Web pages and interfaces Attack surface / entry point：Code repositories and dependencies Attack surface / entry point：Memory writes Layer：Application layer System component：RAG Clear all

Another 213papers 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
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 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
AttacksarXiv 2603.17239Mar 18
LAAF: A Systematic Red-Teaming Method and Automated Attack Framework for LPCI Vulnerabilities in Agentic LLM Systems
Proposes LAAF, which automatically attacks LPCI vulnerabilities in agent systems in stages
arXiv
2603.17239
Published
Mar 18
Layer
Application layer
Setting
AI Agent
Evaluated models
gemini-2.0-flash-001, claude-3-haiku-20240307, meta-llama/llama-3.1-70b-instruct and others5
- AttacksPoisoning and backdoors
- TechniqueDormant triggers
- ComponentMemory
AbstractLAAF does LPCI red teaming with taxonomy plus stage seeding.
The authors state that LAAF is an automated red-teaming framework built specifically for LPCI in agentic LLMs. The issue to address is that encoded, delayed, and conditionally triggered payloads can persist in memory or RAG and re-enter across sessions, whereas Garak and PyRIT do not use the previous round's breakthrough results to seed the next stage across the six stages.
Paper analysisRead analysis
AttacksarXiv 2602.15654Feb 17
Zombie Agent: Persistent Control of Self-Evolving LLM Agents via Self-Reinforcing Injection
提出 Zombie Agent 攻击，经网页间接注入将载荷写入长期记忆并跨会话触发
arXiv
2602.15654
Published
Feb 17
Layer
Application layer
Setting
AI Agent
Evaluated models
Gemini-2.5-Flash, GLM-4.7-Flash
- AttacksPoisoning and backdoors
- TechniqueDormant triggers
- ComponentMemory
Abstract记忆写入把一次网页间接注入变成跨会话控制。
Zombie Agent 把自进化 LLM 智能体的跨会话记忆当成攻击面：攻击者只发布网页，良性任务读入后，正常记忆更新留下载荷，并在以后无关会话里触发未授权工具行为。
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
AttacksarXiv 2507.10457Jul 15, 2025
论文提出 LPCI：针对 Agent 逻辑层与持久记忆的提示控制注入攻击
提出 LPCI，把延迟条件载荷写入记忆与检索库以跨会话触发
arXiv
2507.10457
Published
Jul 15, 2025
Layer
Application layer
Setting
AI Agent
Evaluated models
ChatGPT, Claude, LLaMA3 and others8
- AttacksPoisoning and backdoors
- TechniqueDormant triggers
- ComponentMemory
Abstract作者定义 LPCI。
作者把LPCI定义为针对智能体逻辑执行、记忆留存和工具集成的跨阶段漏洞类，而不是单次输入上的提示改写。
Paper analysisRead analysis

You have reached the end

AI Safety Daily

Read the latest issueOne issue per day, updated as events develop