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 NeoTheCapt · Codex Skill · ★ 112
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is RedteamAgent safe to install? View the security audit →
🔴 RedTeam Agent Autonomous AI-Powered Red Team Simulation Agent Install · Quick Start · Architecture · 中文 An autonomous red team simulation agent that works with Claude Code, OpenCode, and Codex. It transforms any workspace into a full penetration testing environment for CTF/lab targets — featuring 8 AI agents, containerized Kali tools, a streaming case collection pipeline, and 79 security reference files. Demo Key Features: Multi-CLI support — works with Claude Code, OpenCode,
| Stars | 112 |
| Forks | 25 |
| Language | Python |
| Category | Codex Skill |
| Quality Score | 71.6123482947539/100 |
| Open Issues | 3 |
| Last Updated | 2026-08-02 |
| Created | 2026-03-20 |
| Platforms | browser, claude-code, codex, python |
| Est. Tokens | ~18k |
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RedteamAgent is An AI red-team agent for authorized labs and web app pentesting workflows. Turns Claude Code / OpenCode / Codex into a structured recon → test → exploit → report workflow, with containerized tools and. It is categorized as a Codex Skill with 112 GitHub stars.
RedteamAgent is primarily written in Python. It covers topics such as ai-agents, automated-testing, bug-bounty.
You can find installation instructions and usage details in the RedteamAgent GitHub repository at github.com/NeoTheCapt/RedteamAgent. The project has 112 stars and 25 forks, indicating an active community.
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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: