Translation in progress Some entries still include text in the original language.
Oct 13 · Tuesday
All papers Found 12 papers Another 201 papers do not have category tags yet and are not included in filtered results.
“
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.
Retest and extend prompt injection against AI agents, and use Agent Card deception to manipulate A2A selection
Published Oct 8
Evaluated models Ollama Mistral 0.9.5 , llama3-8b-8192 , gemini-2.0-flash-lite and others5 Abstract Single-agent filtering and classification can be bypassed by format or wording, and A2A card selection is also biased toward names and descriptions.The authors retested prompt injection on their own LangChain, AutoGen, and A2A systems, and modified the Agent Card to see if choices shifted. The abstract states the experiments mainly highlight single-agent weaknesses while extending attacks to multi-agent.
提出 AdaLCPI,把恶意指令拆成碎片嵌入工具返回并诱导 Agent 越权执行
Published Sep 29
Evaluated models GPT-4.1 , GPT-5.1 , GPT-5.6-Luna and others7 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 PaperGuard,用图文注入与梯度扰动抬高自动审稿分数并检测恶意指令
Published Jun 11
Evaluated models Claude-sonnet-4.5 , GPT-4o , GPT-4.1 and others11 Abstract PaperGuard 测到提示注入与白盒视觉抬分,并比较分块检索防御。PaperGuard 同时评测并检测多模态 AI 审稿中的评分操纵。
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。 。
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。
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.
提出查询无关黑盒攻击 DQ-A,用可迁移文末后缀降低文档检索排名
Published Jan 31
Evaluated models Qwen-1.5-7B-Instruct , SFR-Embedding-Mistral , E5-Mistral-7B-Instruct and others10 Abstract DQ-A 以无查询黑盒后缀压低 LLM 检索排名,并在 BRIGHT 上比较三种基线。DQ-A 是一种 query-agnostic、complete black-box 的文档隐藏攻击,对象是用最后隐层相似度匹配的 LLM 检索。
提出 AST-ASIP ,把对抗指令植入编译器忽略区域以劫持代码评分
Published Jan 29
Evaluated models DeepSeek-V3.2 , Qwen3-235B , GPT-OSS-120B and others9 Abstract 作者称 RLHF 的服从性使评分脱离代码。这篇工作把自动代码评分中的失败称为 Compliance Paradox:评分模型可以离开提交逻辑,转而执行嵌在可编译代码里的隐藏指令。
提出查询中心词的单次插入或替换攻击,操纵神经排序名次
Published Jan 28
Evaluated models BERT-base-mdoc-BM25 , monoT5-base-MSMARCO Abstract 作者称单词扰动即可抬升名次、中段文档最脆弱,且比白盒 PRADA 更少编辑。单个与查询对齐的词,就可能改掉神经重排结果。要做的是少改原文,仍把目标文档在 NRM 列表里的名次抬高。
Attacks arXiv 2512.10449 · Dec 11, 2025 提出 DSAAP,以不可见文本对科学审稿 PDF 做间接提示注入
Published Dec 11, 2025
Evaluated models gpt-oss-20B , tulu3-8B , Llama 3.1-8B and others13 You have reached the end