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Oct 12 · Monday
Another 233 papers do not have category tags yet and are not included in filtered results.
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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 ClawSentry 多层监控网关,在技能准入和运行时拦截恶意技能与隐藏指令
Published Aug 21
Evaluated models Codex/GPT-5.4 , Codex/GPT-5.5 , Claude Code/GLM-5.1 and others6 Abstract ClawSentry 用包准入、三级运行时门控和反绕过,压低 skill 攻击并保住干净任务。ClawSentry 是挂在智能体运行时之外的安全监督网关,用来同时盖住 skill 执行的多个生命周期边界,并把已被拒绝的效果记到会话里。
提出 S³,用 guard agent 编排阶段安全技能防御智能体多阶段风险
Published Aug 3
Evaluated models DeepSeek-V4-Pro , DeepSeek-V4-Flash Proposes MTGuard, which blocks unsafe tool calls by comparing MCP call declarations with execution traces.
Published Jul 28
Evaluated models DeepSeek-V4-Flash , DeepSeek-V4-Pro , GPT-5.6 Luna 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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