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Oct 12 · Monday
All papers Found 12 papers 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.
Auditing training labels for label-only backdoors, comparing spaces and statistics, and judging by retraining
Published Oct 9
Evaluated models ResNet-32 Abstract Label inspection must be done in a space that has not been fitted to these labels, and judged by retrained models rather than detection scores.The authors ask: can a defender without trusted data decide which training labels to keep, and how much clean data this destroys, and what the final model accuracy is.
提出 PyCache Trap，用字节码缓存替换绕过 Agent 技能扫描器
Published Oct 7
Evaluated models CISCO , HSS , AUDITOR and others8 Abstract 论文剖析智能体技能审查与执行脱节盲区，提出 PyCache Trap 攻击并构建基于可信复现的 EAV 防御。这篇论文研究了智能体技能（Agent Skills）安全扫描中的“审查–执行脱节”问题，并提出了对应的攻击验证与防御方案。
提出 AgentSpy，在系统调用层观测 Agent 行为并检测技能注入
Published Oct 5
Evaluated models gpt-5.6-terra , deepseek-v4-flash , glm-5.3-flash and others4 Abstract 提出了系统级智能体监控框架 AgentSpy，揭示出通过测试背后的非预期行为与注入风险。本研究提出了面向 AI 智能体的系统级外部监控与行为分析框架 AgentSpy 。
提出 SAGE，用少量已核验样本按相似度清洗投毒训练数据
Published Oct 1
Evaluated models ResNet-18 , VGG-16 为协同异常检测提出物理准入门，在聚合前拦截不合规训练批次
Published Sep 28
Evaluated models deep reconstruction autoencoder Abstract 物理准入为联邦检测增加数据约束，但合规证明不等于无投毒或训练来源证明。这是一项面向水基础设施联邦异常检测的物理准入防御研究。 作者针对隐藏训练遥测带来的投毒检查问题，结合不变量挖掘、聚合前过滤和零知识抽样证明。
提出 Fed-ADR，用编排服务器协同操纵梯度攻破联邦学习并检测恢复
Published Sep 23
Evaluated models CNN（MNIST：2 Conv + 3 FC） , CNN（Fashion-MNIST：6 Conv + 1 FC） , ResNet18（CIFAR-10） Abstract Fed-ADR 用 gray-box 编排攻击绕过多种聚合防御，再用 Hessian 一致性检测和窗口内恢复把准确率拉回。Fed-ADR 是一套面向联邦学习的攻击、检测与恢复框架：编排服务器改写合谋客户端的梯度，使参数服务器的现有防御把投毒更新当成良性，同时在发现后用历史梯度把全局模型原地修回来。
提出 SkillSecurer，检测并修补 Agent 技能中的提示注入漏洞
Published Sep 13
Evaluated models Claude Sonnet 5 , Gemini 3.6 Flash , GPT-5.6 Sol and others10 提出 VERITAS，用双边背书剪除本地隐私图学习中的投毒节点
Published Sep 7
Evaluated models GCN , GraphSAGE , GAT Abstract VERITAS 用分级信任的双边背书剪除 LDP 图学习中的投毒节点，并恢复分类准确率。VERITAS 是面向本地差分隐私图学习的投毒防御协议，按 trust-but-verify 在保持 ϵ-LDP 的同时剪除伪造节点。
提出持续学习下的净化与选择性恢复框架，抵御逐任务训练投毒后门
Published Sep 6
Evaluated models ViT-B/16 Abstract 作者报告任务内净化与恢复可配合动态专家防御后门，但保证依赖分离条件。这是一项面向持续图像分类的后门防御研究 ：模型只使用当前任务数据，同时需要保留过去知识并避免学习恶意监督。
提出 FedMAST，用多轴结构痕迹检测并遏制联邦学习后门
Published Sep 4
Evaluated models Tiny ResNet-18 Propose Z-PEFT, which detects PEFT backdoors in a zero-shot manner using per-head spectral features.
Published Aug 3
Evaluated models Z-PEFT , Llama-2-7B , Llama-2-13B and others6 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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