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 h4ckf0r0day · Agent Tool · ★ 28.3k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is obscura safe to install? View the security audit →
Obscura The open-source headless browser for AI agents and web scraping. Lightweight, stealthy, and built in Rust. Obscura is a headless browser engine written in Rust, built for web scraping and AI agent automation. It runs real JavaScript via V8, supports the Chrome DevTools Protocol, and acts as a drop-in replacement for headless Chrome with Puppeteer and Playwright. Why Obscura over headless Chrome? Designed for automation at scale, not desktop browsing. Install Download Grab the latest binary from Releases: bash Linux x8664 curl -LO https://github.com/h4ckf0r0day/obscura/releases/latest/download/obscura-x8664-linux.tar.gz tar xzf obscura-x8664-linux.tar.gz ./obscura fetch https://example.com --eval "document.title" macOS Apple Si
| Stars | 28,274 |
| Forks | 2,099 |
| Language | Rust |
| Category | Agent Tool |
| License | Apache-2.0 |
| Quality Score | 70.7020428870551/100 |
| Open Issues | 205 |
| Last Updated | 2026-10-03 |
| Created | 2026-04-13 |
| Platforms | browser, rust |
| Est. Tokens | ~23k |
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obscura is The headless browser for AI agents and web scraping. It is categorized as a Agent Tool with 28.3k GitHub stars.
obscura is primarily written in Rust. It covers topics such as antidetect, antidetect-browser, browser.
You can find installation instructions and usage details in the obscura GitHub repository at github.com/h4ckf0r0day/obscura. The project has 28.3k stars and 2099 forks, indicating an active community.
obscura is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to obscura on Agent Skills Hub include camofox-browser, nanobrowser, browser-use. 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: