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Oct 13 · Tuesday
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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 PyCache Trap，用字节码缓存替换绕过 Agent 技能扫描器
Published Oct 7
Evaluated models CISCO , HSS , AUDITOR and others8 Abstract 论文剖析智能体技能审查与执行脱节盲区，提出 PyCache Trap 攻击并构建基于可信复现的 EAV 防御。这篇论文研究了智能体技能（Agent Skills）安全扫描中的“审查–执行脱节”问题，并提出了对应的攻击验证与防御方案。
提出 CORSA，按任务簇优化技能注入的检索与执行
Published Oct 6
Evaluated models GPT-5.4 , DeepSeek-V4-Pro , Qwen3.8-27B and others5 提出 CoordPoison，解耦技能投毒的借口与动作
Published Sep 30
Evaluated models DeepSeek-V4-Flash , GLM-5.3-Flash , Claude-Sonnet-4.6 and others5 Abstract CoordPoison 外置借口。CoordPoison 是一种 Skill 供应链投毒方法，把“为何执行”和“执行什么”拆到两个 Skill。 。
提出 MMSkillRisk 基准，评测多模态技能图像中的隐藏指令诱导 Agent 越权操作
Published Sep 28
Evaluated models GPT-5.6-sol , Kimi-K2.6 , Kimi-K3 and others6 Abstract 论文提出 MMSkillRisk 基准与 NCVA 攻击，揭示多模态技能中教学图像潜藏指令可引发未授权操作并与良性任务共存。
提出 SkillDRE，用预执行与运行时双阶段反馈演化恶意 Agent 技能
Published Sep 26
Evaluated models DeepSeek-V4-Pro , GLM-5.2 , Qwen3.5-397B-A17B and others4 提出跨通道分段攻击，利用 MCP 隐式信任外发敏感文件
Published Sep 16
Evaluated models GPT-4o , GPT-4o-mini , GPT-5.4 and others15 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。
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 SKILLBLOAT，改写技能文档放大编码 Agent token 消耗
Published Aug 22
Evaluated models GLM-4.7-Flash , GLM-5 , GPT-5.4 Mini and others4 提出 ColluSkill，用跨技能组合绕过 Agent 技能扫描器
Published Aug 10
Evaluated models GPT-5.5 , DeepSeek-V4-Pro , GLM-5.2 Abstract 论文揭示了单技能孤立扫描的盲区，提出多技能链攻击 ColluSkill 与上下文防御 ChainGuard 并验证了有效性。
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。 。
提出技能名称抢注攻击，利用 Agent 虚构技能名实施供应链劫持
Published Jul 14
Evaluated models GLM-4.5-Air , GPT-5.4-mini , Claude Sonnet 4.6 and others12 Abstract 研究证实智能体虚构技能名具有高发生率与可预测性，现有防御难以兼顾安全与效用，亟需注册表结构性防护。本研究系统揭示了大模型智能体技能推荐场景下的虚构技能名称安全风险，将其形式化为一种新型供应链抢注攻击。
提出 AHA 自动科研循环，发现生产 Agent 的可复用漏洞概念
Published Jul 13
Evaluated models Minimax-M2.7 , Kimi-K2.6 , Deepseek-V4-Pro and others5 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。
提出 MAStrike，用 Shapley 选联盟对多智能体做共谋红队
Published Jun 11
Evaluated models Claude Opus 4.7 , GPT-5.5 , Gemini 3.1 Pro 提出 PoisonedSkills，评测编码 Agent 技能生态的文档投毒
Published Apr 3
Evaluated models Claude Sonnet 4.6 , GLM-4.7 , MiniMax-M2.5 and others5 Abstract 作者称技能文档可成为系统操作攻击入口，但结果只评估加载后的阶段。PoisonedSkills 研究编码智能体的技能供应链投毒，重点是文档内容如何进入实际系统操作。 。
Proposes SkillJect, which automatically generates poisoned skills to induce code agents to execute hidden scripts
Published Feb 16
Evaluated models Claude-4.6-Sonnet , GPT-5-mini , GLM-4.7 and others10 Abstract SkillJect poisons skills using dual channels and closed-loop refinement.SkillJect is an automated prompt injection framework targeting installable agent skills. The authors address the problem that malicious instructions placed in publicly available or manually installed skills are often rejected or ignored, yet once a skill is installed, it is repeatedly loaded as trusted guidance.
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