Flagged: sudo usage. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by lusipad · Codex Skill · ★ 221
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🔒 Is unofficial-codex-app-offline safe to install? View the security audit →
Codex App Offline English 本项目提供两种使用 Codex 的方式，共享同一套离线技能 seed： 桌面版：OpenAI Codex Windows 应用的非官方离线便携重打包——解压即用，无需 Store、无需登录 Microsoft 账户。 浏览器版（Web Gateway）：提供一个本地 Web 服务，在浏览器中使用 Codex 的全部功能。Gateway 负责渲染前端 UI 并将请求转发给本机安装的 CLI 执行。本质是 "Codex CLI 做后端，浏览器做前端" 的架构，因此跨平台通用。 构建时自动拉取 openai/skills，离线 seed 打包；首次 Setup 仅安装基础 profile，其余技能留在包内按需同步。 快速开始 Windows 完整包 从 Releases 下载 ，解压后： 首次运行双击 ，按提示完成引导 日常使用桌面版：双击 （无需 Node.js） 使用浏览器版：先装 Node.js 18+，双击 ，浏览器打开 完整包同时包含桌面版和浏览器版。桌面版开箱即用；浏览器版需要额外安装 Node.js。 浏览器版独立包（Web-Only / Windows / Linux / macOS） 安装后同一个脚本也可以做管理入口： 如果安装时选择了 systemd 服务，这些命令会优先调用 ；否则回落到包内的 / / 。 手动安装： 安装 Node.js 18+ 和 Codex CLI 从 [Releases
| Stars | 221 |
| Forks | 11 |
| Language | JavaScript |
| Category | Codex Skill |
| Quality Score | 69.5579697328497/100 |
| Open Issues | 2 |
| Last Updated | 2026-09-19 |
| Created | 2026-03-06 |
| Platforms | browser, codex, node |
| Est. Tokens | ~14k |
Looking for a unofficial-codex-app-offline alternative? If you're comparing unofficial-codex-app-offline with other codex skill tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
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unofficial-codex-app-offline is Unofficial offline / portable repackaging of the OpenAI Codex Windows app.. It is categorized as a Codex Skill with 221 GitHub stars.
unofficial-codex-app-offline is primarily written in JavaScript. It covers topics such as codex, codex-app, codex-web.
You can find installation instructions and usage details in the unofficial-codex-app-offline GitHub repository at github.com/lusipad/unofficial-codex-app-offline. The project has 221 stars and 11 forks, indicating an active community.
The top alternatives to unofficial-codex-app-offline on Agent Skills Hub include Agents-Anywhere, Codex-App-Manager, codex-app. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: