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 jo-inc · Agent Tool · ★ 11.1k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is camofox-browser safe to install? View the security audit →
camofox-browser Anti-detection browser server for AI agents, powered by Camoufox Standing on the mighty shoulders of Camoufox - a Firefox fork with fingerprint spoofing at the C++ level. Built by the team behind jo, a personal AI agent that runs half on your Mac, half on a dedicated cloud machine just for you -- with zero maintenance needed. Available on macOS, Telegram, WhatsApp, and email. Try the beta free - bash git clone https://github.com/jo-inc/camofox-browser && cd camo
| Stars | 11,115 |
| Forks | 1,098 |
| Language | JavaScript |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 72.9223427139466/100 |
| Open Issues | 91 |
| Last Updated | 2026-09-19 |
| Created | 2026-01-26 |
| Platforms | browser, node |
| Est. Tokens | ~22k |
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camofox-browser is Stealth headless browser for AI agents — bypass Cloudflare, bot detection, and anti-scraping. Drop-in Puppeteer/Playwright replacement.. It is categorized as a Agent Tool with 11.1k GitHub stars.
camofox-browser is primarily written in JavaScript. It covers topics such as ai-agent, anti-bot, antidetect-browser.
You can find installation instructions and usage details in the camofox-browser GitHub repository at github.com/jo-inc/camofox-browser. The project has 11.1k stars and 1098 forks, indicating an active community.
camofox-browser is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to camofox-browser on Agent Skills Hub include obscura, nanobrowser, shortest. 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: