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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 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。
提出任意字母置换密码越狱,无需微调即可诱导有害输出
Published Sep 9
Evaluated models Claude Sonnet 4 , Claude Sonnet 4.5 , Gemini 3 Flash (preview) and others7 Abstract 前沿大模型无需微调即可通过提示词学会字母置换密码,进而绕过分类器与对齐,作者呼吁关注能力提升带来的安全风险。
提出 SinoGlyphBench,用配对字形混淆诊断中文审核稳定性
Published Sep 5
Evaluated models GPT-5.4 mini , GPT-5.5 , DeepSeek V4 Flash and others12 Abstract SinoGlyphBench 显示中文字形混淆会同时增加有害漏报和误报,全文扰动最重。SinoGlyphBench 是一个配对诊断基准,用来看内容审核在可还原的中文字形混淆下是否还保持原决定。
提出 HACA,将图文越狱拆为原子策略并自动组合以诱导有害输出
Published Aug 3
Evaluated models LLaVA-1.6-Mistral-7B , InternVL-3.5-8B , VLGuard (LLaVA-v1.5-7B-Mixed) and others5 提出 DSR 跨模态越狱,用无害图文诱导 MLLM 生成有害图像
Published Jun 1
Evaluated models gemini-2.5-flash-image , qwen-image-2.0 , Tongyi Wanx 2.5 Abstract DSR 用无害图文诱导商业 MLLM 输出有害图像,作者称组合能力会反过来扩大攻击面。DSR 是一种 black-box 跨模态越狱:输入侧不放显式有害内容,而让商业 MLLM 在推理中把无害图文重组成有害图像。
提出多图越狱框架 DMN,把有害意图拆进图像序列绕过安全护栏
Published May 18
Evaluated models GPT-4V , GPT-4o , GPT-5 and others10 提出删字变体越狱方法,利用重构与隐藏权衡绕过多模态模型安全过滤
Published May 7
Evaluated models GPT-5.4-nano , GPT-5.4-mini , Gemini-2.5-Flash and others19 提出四类视觉越狱,把有害意图编码进图像以绕过安全拒答
Published May 1
Evaluated models GPT-5.2 , Claude-Haiku-4.5 , Gemini-3-Flash and others8 Abstract 四类视觉越狱在六个 VLM 上检验文本对齐能否挡住视觉意图,模型与攻击之间差异大。四类视觉越狱用来检验前沿 VLM 的文本安全训练能否挡住由图像传达的有害意图。 。
提出多流扰动攻击,交织有害与良性任务绕过思考型 LLM 安全对齐
Published Mar 10
Evaluated models Qwen3 1.7B , Qwen3 4B , Qwen3 8B and others11 Abstract 多流扰动用任务交织测试 thinking 模式,作者称它同时冲击内容安全与推理稳定性。多流扰动攻击把有害任务与良性任务织进同一提示词,测试 thinking 模式的内容安全与推理稳定性。作者认为,交织多任务会拉长思考,使安全检测面对被打散的有害意图,并可能把推理用于合理化,或陷入崩溃与重复。方法不访问梯度。
提出 StructAttack,用结构图把无害语义槽诱导视觉模型拼成恶意内容
Published Mar 8
Evaluated models GPT-4o (1120) , Gemini-2.0-Flash (001) , Gemini-2.5-Flash and others6 Abstract StructAttack 把有害查询拆成无害槽并画进结构图,在黑盒单次查询下诱导 LVLM 填出有害内容。StructAttack is a black-box, single-query jailbreak against LVLMs: it decomposes a harmful instruction into separate seemingly harmless slots, draws them into a structural diagram, and then makes the model reassemble the slots into harmful content.
提出 MIDAS ,把有害语义拆进多张视觉谜题并跨图重构以越狱多模态模型
Published Feb 28
Evaluated models GPT-4o , GPT-5-Chat , Gemini-2.5-Pro and others7 用简历中的不可见指令做间接提示注入,操纵招聘推荐
Published Feb 20
Evaluated models Qwen 3 30B A3B Instruct 2507 , Qwen 3 30B A3B Thinking 2507 Abstract 作者称推理在简单注入下会帮攻击圆谎,在不合逻辑的复杂注入下又会把欺骗漏出来。
提出 COMET 跨模态纠缠攻击,越狱视觉语言模型
Published Feb 10
Evaluated models GPT-4.1 , GPT-4.1-mini , Gemini-2.5-Flash and others9 Abstract COMET 做黑盒跨模态纠缠越狱。COMET 是面向具备多模态推理的 VLM 的黑盒越狱,用来红队测试跨模态安全对齐。作者要处理的缺口是:把恶意线索分到图文的固定组合,测不到多步推理里才出现的漏洞。攻击不访问梯度,只构造图文输入。
提出 Text-DJ,用拆分文本图网格越狱视觉语言模型
Published Jan 31
Evaluated models Qwen/Qwen3-VL-4B-Instruct , Qwen/Qwen3-VL-8B-Instruct , Qwen/Qwen3-VL-30B-A3B-Instruct and others6 提出 BVS 图文越狱,用中和拼接图和诱导提示词让模型生成有害图像
Published Jan 22
Evaluated models GPT-5 (12 January 2026 release) , Gemini 1.5 Flash (15 January 2026 release) Abstract BVS 以重建后再生成诱导有害图像。BVS 用图文对诱导 MLLM 生成有害图像。作者认为,相对文本越狱和单模态图像诱导,视觉生成的安全审查仍不充分。
提出 GAMBIT 游戏化越狱框架,用拼图与竞赛场景攻击多模态模型
Published Jan 7
Evaluated models Qwen2.5-VL , InternVL 2.5 , GPT-4o and others8 Attacks arXiv 2512.20168 · Dec 23, 2025 提出双重隐写越狱 Odysseus,用图像隐写绕过多模态系统安全过滤器
Published Dec 23, 2025
Evaluated models GPT-4o-2024-08-06 , Gemini-2.0-pro , Gemini-2.0-flash and others4 You have reached the end