仓库/Skill 库

面向黑客、渗透测试工程师和安全研究人员的各类精选清单合集A collection of various awesome lists for hackers, pentesters and security researchers

收录公开漏洞利用 PoC 与漏洞研究技术报告的单一归档库。本人在发布时这些内容尚未被披露，欢迎自行上报并领取 CVE 编号（若获分配，权当一乐）。请勿滥用。我做这件事是为了吸引更多人进入这一领域，并且一直认为这是最高效的方式。A single archive of public exploit PoCs and vulnerability research writeups. At the time I post these, none have been reported. Feel free to report them yourself and take credit for the CVE if handed out lulz. Please do not abuse these. I do this so to allure people into the field, and I've always found this is the most efficient way.

反检测与人性化工具及浏览器列表，含验证码识别与短信激活。List of anti-detect and humanizing tools and browsers, including captcha solvers and sms-activation.

差分隐私联邦学习系统综述（ACM Survey）；Adap dp-fl：自适应噪声的差分隐私联邦学习（TrustCom'2022）Differentially private federated learning: A systematic review (ACM Survey); Adap dp-fl: Differentially private federated learning with adaptive noise (TrustCom'2022)

本综述目标有二：(i) 综述对抗机器学习（AML）在推荐系统（RS）安全上的最新进展，即攻击与防御推荐模型；(ii) 展示 AML 在生成对抗网络（GAN）生成应用中的成功应用，得益于其学习（高维）数据分布的能力。本文对发表于主流 RS 与 ML 期刊会议的 74 篇文献进行了详尽综述，可作为 RS 社区在推荐系统安全及利用 GAN 提升生成模型质量方面的参考The goal of this survey is two-fold: (i) to present recent advances on adversarial machine learning (AML) for the security of RS (i.e., attacking and defense recommendation models), (ii) to show another successful application of AML in generative adversarial networks (GANs) for generative applications, thanks to their ability for learning (high-dimensional) data distributions. In this survey, we provide an exhaustive literature review of 74 articles published in major RS and ML journals and conferences. This review serves as a reference for the RS community, working on the security of RS or on generative models using GANs to improve their quality.

围绕 LLM 人类价值观与多元对齐的精选论文、基准、数据集与工具合集。A curated collection of papers, benchmarks, datasets, and tools on human values in LLMs and pluralistic alignment.

大语言模型情境感知相关论文精选目录。Curated bibliography of papers on situational awareness in large language models

个人简介：可信 AI、可复现研究、开发者工具。Profile overview: trustworthy AI, reproducible research, and developer tools.

用于探索 LLM Security 新兴研究主题的研究路线图与文献综述仓库。A research roadmap and literature review repository for exploring emerging research topics in Large Language Model Security.

活文献综述：面向网络安全领域的现代数据架构Living literature review: Modern data architecture for cybersecurity

关于细菌抗生素耐药程度标准化定义使用的系统综述与建议A systematic review and recommendations on the use of standard definitions for extent of antibiotic resistance in bacteria

一项系统性文献综述A systematic literature review