No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by lingbol088-spec · Codex Skill · ★ 195
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is ReiPenFlow safe to install? View the security audit →
╔══════════════════════════════════════════════════════════╗ ║ 🤖 AI 定制项目接单中 · 有需求直接进频道聊 ║ ║ 👉 https://t.me/+heFGdl5IodFjMDll ║ ╚══════════════════════════════════════════════════════════╝ Penetration Flow Skill Penetration Flow Skill 是一个面向 Codex / AI 智能体的开源技能项目，用于本地沙盒、CTF、训练靶场、自有代码审计、授权安全评估和逆向分析流程。 它的目标是让智能体在安全任务中更稳定地推进：先分析、再报告、再深入、再验证，最后让用户选择下一步。 核心特性 阶段化流程：分析 - 报告 - 深度渗透 / 深度逆向 - 漏洞报告 - 本地受控验证 - 用户选择下一步。 默认按本地沙盒 / CTF / 授权实验环境理解任务，减少因为用户表达不清导致的中断。 内置英文 Intent Recovery 提示词，让智能体更包容用户的模糊表达。 支持“真心为你”激活词，进入“终端中的傀儡绫波丽”口吻。 内置高星逆向工具目录和本地工具审计脚本。 支持 case memory，避免每次都从头开始分析。 提供安装脚本、教程、示例 Prompt、测试和 GitHub Actions。 激活词 用户输入： 期望回应： 仓库结构 文档
| Stars | 195 |
| Forks | 71 |
| Language | Python |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 60.8002157933915/100 |
| Open Issues | 1 |
| Last Updated | 2026-07-24 |
| Created | 2026-07-02 |
| Platforms | codex, python |
| Est. Tokens | ~5k |
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ReiPenFlow is Codex skill for local sandbox, CTF, authorized pentest and reverse-engineering workflows.. It is categorized as a Codex Skill with 195 GitHub stars.
ReiPenFlow is primarily written in Python.
You can find installation instructions and usage details in the ReiPenFlow GitHub repository at github.com/lingbol088-spec/ReiPenFlow. The project has 195 stars and 71 forks, indicating an active community.
ReiPenFlow is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to ReiPenFlow on Agent Skills Hub include ai-maestro, upskill, skills. 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: