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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 WebMirage,用局部对抗图像劫持视觉网页 Agent 的浏览器操作
Published Oct 7
Evaluated models LLaVA-v1.5-13B , LLaVA-v1.6-34B , MiniCPM-o-8B and others6 Abstract 论文提出了针对网络智能体的端到端视觉红队框架 WebMirage,揭示了从视觉定位到浏览器执行的安全脆弱性。WebMirage 是一个面向视觉定位网络智能体的流水线感知端到端红队攻击框架。
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 PMPA,经外部源向 Agent 持久记忆投毒并跨会话泄露隐私
Published Sep 12
Evaluated models DeepSeek-V4-Flash , DeepSeek-V4-Pro , Qwen3-Max Abstract 论文提出了持久记忆投毒攻击 PMPA,报告了 harness 智能体在处理外部数据时易受跨会话记忆投毒与隐私泄露的风险。
对开源视觉购物智能体实施商品图对抗攻击并诱导买错
Published Mar 17
Evaluated models LLaVA-v1.5-7B , Qwen2.5-VL-7B Abstract 作者称 LLaVA 易被三种攻击诱导买错,Qwen 正确购买率仍接近其干净条件。作者在自建电商环境里比较两个开源 VLM 购物智能体对图像对抗扰动的鲁棒性。
提出 WAInjectBench 评测网页 Agent 的提示注入检测
Published Oct 2, 2025
Evaluated models GPT-4o , Mistral-7B-Instruct-v0.1 , Llama-Prompt-Guard-2-86M and others8 Abstract WAInjectBench 比较网页智能体的提示注入检测:显式线索可被部分检出,隐蔽攻击大多漏检。WAInjectBench 是网页智能体提示注入检测的基准。作者要看现有检测器能否发现这类攻击:攻击者改网页,使智能体执行目标动作,而不是用户任务。作者称这是首个此类综合基准。
Attacks arXiv 2406.12814 · Jun 19, 2024 提出 ARE 框架与图像文本攻击,评测多模态网页 Agent 的对抗鲁棒性
Published Jun 19, 2024
Evaluated models GPT-4o , GPT-4V , Claude-3-Opus and others4 Abstract 系统评估多模态网页智能体的脆弱性,指出推理时计算组件被攻破会加剧系统风险。
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