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 PathOnAIOrg · Agent Tool · ★ 153
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is LiteWebAgent safe to install? View the security audit →
LiteWebAgent Disclaimer: Please note that LiteWebAgent is not affiliated with any for-profit company. This is a collaborative project from PathOnAI.org, an open-source AI research community, where Danqing Zhang (danqing.zhang.personal@gmail.com) is the main contributor and lead author of the NAACL paper. If anyone claims LiteWebAgent is affiliated with any for-profit company, please contact Danqing Zhang (danqing.zhang.personal@gmail.com) for verification. Follow-Up Work: VisualTreeSearch VisualTreeSearch is a production-ready system for visualizing and understanding web agent test-time scaling. It builds upon LiteWebAgent to provide an intuitive framework for researchers and users to understand tree search execution in web agents. Resources 🌐 Project Page: PathOnAI.org/VisualTreeSearch 🎮 Live Demo: visual-tree-search.pathonai.org 📄 Paper: Read on arXiv 🎥 Video Demo: Watch on YouTube Join the community!
| Stars | 153 |
| Forks | 27 |
| Language | Python |
| Category | Agent Tool |
| Quality Score | 62.0004481755788/100 |
| Last Updated | 2025-07-11 |
| Created | 2024-07-16 |
| Platforms | browser, python |
| Est. Tokens | ~5656k |
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LiteWebAgent is [NAACL2025] LiteWebAgent: The Open-Source Suite for VLM-Based Web-Agent Applications. It is categorized as a Agent Tool with 153 GitHub stars.
LiteWebAgent is primarily written in Python. It covers topics such as agent, agent-based-framework, agentic-agi.
You can find installation instructions and usage details in the LiteWebAgent GitHub repository at github.com/PathOnAIOrg/LiteWebAgent. The project has 153 stars and 27 forks, indicating an active community.
The top alternatives to LiteWebAgent on Agent Skills Hub include Agent-ChatRoom, open-computer-use, craftgen. 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: