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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 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 SkillVetBench 评估开源 Agent 技能的多维安全风险
Published Jun 15
Evaluated models Qwen2.5-14B-Instruct , Qwen2.5-32B , Llama-3.1-70B and others6 Abstract 公开排行榜用 LLM-as-Judge 给技能分列 SARS 与 CVSS，并对照市场官方审查。
提出企业级检测系统 ADR，识别编程 Agent 的提示注入与恶意 MCP
Published May 17 Abstract 提出了端点因果遥测、两级在线分流与离线红队闭环的 ADR 系统，并在生产环境中验证了有效性。
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