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 browser-use · Agent Tool · ★ 16.6k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is web-ui safe to install? View the security audit →
This project builds upon the foundation of the browser-use, which is designed to make websites accessible for AI agents. We would like to officially thank WarmShao for his contribution to this project. WebUI: is built on Gradio and supports most of functionalities. This UI is designed to be user-friendly and enables easy interaction with the browser agent. Expanded LLM Support: We've integrated support for various Large Language Models (LLMs), including: Google, OpenAI, Azure OpenAI, Anthropic, DeepSeek, Ollama etc. And we plan to add support for even more models in the future. Custom Browser Support: You can use your own browser with our tool, eliminating the need to re-login to sites or deal with other authentication challenges. This feature also supports high-definition screen recording. Persistent B
| Stars | 16,602 |
| Forks | 2,766 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 67.9274844671591/100 |
| Open Issues | 327 |
| Last Updated | 2026-09-25 |
| Created | 2025-01-02 |
| Platforms | browser, python |
| Est. Tokens | ~15k |
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web-ui is 🖥️ Run AI Agent in your browser.. It is categorized as a Agent Tool with 16.6k GitHub stars.
web-ui is primarily written in Python. It covers topics such as ai-agent, browser-automation, browser-use-box.
You can find installation instructions and usage details in the web-ui GitHub repository at github.com/browser-use/web-ui. The project has 16.6k stars and 2766 forks, indicating an active community.
web-ui is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to web-ui on Agent Skills Hub include stagehand, moli, chatgpt-on-wechat. 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: