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Oct 12 · Monday
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About this collection Collection in progress We are building a large AI safety paper collection to help researchers find work related to their interests. Papers are collected automatically andfiltered only for relevance to AI safety , without judging quality, novelty or reading value. The default “Annotated first” shows papers with tags or published paper analyses first. Each group is ordered by original publication date, newest first, with undated papers last. “Newest first” uses publication dates only. This order is not a quality ranking.
One-line summaries, tags and paper analyses are prepared by AI from the papers. Language models may have systematic biases and produce hallucinations.We plan to carry out human annotation and review to reduce errors in this content.
提出 PERSISTBD，发布前强化供应链后门使其经良性 SFT 与 RL 后仍外发凭据
Published Oct 6
Evaluated models Qwen2.5-Coder-3B-Instruct , Qwen2.5-Coder-7B-Instruct , Qwen3-Coder-30B-A3B-Instruct Abstract 总结了论文关于后门在 SFT/RL 中存活的发现、两因子机制、PERSISTBD 方法与核心数字。本文研究第三方 LLM 智能体在开发者进行良性监督微调（SFT）和强化学习（RL）后训练时的后门持久性风险。
提出 CodePoisonRAG，对检索增强代码生成的知识库投毒以植入漏洞
Published Sep 3
Evaluated models Qwen 3.5 9B , Code Llama 13B , DeepSeek-Coder-V2 16B Abstract CodePoisonRAG 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。
提出针对 Agent Harness 的上下文特权提升攻击
Published Sep 1
Evaluated models GPT-5.5 , GPT-5.4 mini , Claude-Sonnet-4.6 and others7 系统研究 LLM 智能体记忆投毒并构建基准 MPBench
Published Jun 3
Evaluated models Meta-Llama-3.1-70B-Instruct , Deberta-v3-base , Llama-3.1-8B-Instruct and others5 Abstract 系统研究了智能体记忆投毒风险，揭示了写入渠道漏洞，构建了 MPBench 基准并指出提示注入防御的局限。
提出潜伏记忆投毒，诱导 Agent 把外部文档写成持久伪造记忆
Published May 15
Evaluated models GPT-5.4 , GPT-5.5 , Claude Sonnet 4.6 and others12 Abstract 持久记忆成为跨会话攻击面：通用载荷可写入伪造记忆，并在相关后续任务中影响行为。sleeper memory poisoning 研究带持久记忆的 LLM 助手：外部文档能否让助手存下一则伪造的用户记忆，并在原文档消失后的新会话里被取回、用来改变回复或动作。
提出 eTAMP，用网页内容跨会话投毒 Web Agent 轨迹记忆并诱导越权操作
Published Apr
Evaluated models GPT-5-mini , GPT-5.2 , GPT-OSS-120B and others6 Abstract 论文提出了基于环境注入的跨任务记忆投毒攻击 eTAMP，作者报告智能体在环境压力下易感性增加且能力与安全并不协同。该论文评估了基于大语言模型的 Web 智能体在利用历史交互轨迹进行记忆增强时的安全脆弱性。
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