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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 TrustProbe，挖掘技能智能体中不可信 skill 到特权操作的信任链漏洞
Published Sep 30
Evaluated models OpenClaw , OpenCode , Hermes Agent and others11 提出 HOOKPRY，用插件钩子版本更新供应链劫持 Agent 框架
Published Sep 3 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 提出 EVOMAL，诱导自演化编码 Agent 在创建技能时自我投毒并蠕虫传播
Published Aug 26
Evaluated models Devstral-Small-2 , Gemma-4-31B-IT , Qwen3-Coder-Next and others7 Abstract 论文指出了自演化智能体模仿检索代码的自我毒化漏洞，提出 EVOMAL 攻击与防御，阐明了供应链新风险。
提出 ElasticBack，在单个 Agent 技能中植入条件后门
Published Aug 10
Evaluated models GLM-5.2 , MiniMax-M3 , GPT-5.4 and others4 Abstract ElasticBack 用冻结规则加遗传搜索演化 trigger，在单 skill 上做条件后门。ElasticBack 是放在 LLM agent 单个 skill 里的条件后门攻击。 。
提出 SYNCHAIN，诱导计算机使用 Agent 自建跨任务持久攻击链
Published Aug 7
Evaluated models Qwen3.5-9B , Llama-3.1-8B , Ministral-3-8B Abstract 论文揭示了 CUA 自合成工件带来的内部供应链威胁，验证了潜伏载荷的跨任务传播能力与防御局限。
提出 PoisonedEvolution 轨迹投毒，诱导自演化技能系统固化恶意行为
Published Aug 6
Evaluated models GPT-5.4 , MiniMax-M2.5 , DeepSeek-V3.2 and others6 Abstract 论文揭示自演化技能系统的证据晋升漏洞，提出并验证轨迹投毒攻击。这篇论文揭示了自演化技能系统在将交互经验转化为持久指令时的安全风险。
Attacks arXiv 2507.10457 · Jul 15, 2025 提出 LPCI，把延迟条件载荷写入记忆与检索库以跨会话触发
Published Jul 15, 2025
Evaluated models ChatGPT , Claude , LLaMA3 and others8 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。
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