Flagged: sudo usage. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by vectra-ai-research · Agent Tool · ★ 342
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
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Halberd: Multi-Cloud Agentic Attack Tool Validate your multi-cloud defenses through realistic attack emulation 🚀 Get Started • 📖 About • ✨ Features • 📚 Guide • 📋 Docs • 🤝 Contributing 🚀 Quick Start Get Halberd running in under 60 seconds. Choose the installation method that works best for you. Option 1: Docker (Recommended) The fastest way to get started. One command and you're ready: Then open your browser to a
| Stars | 342 |
| Forks | 35 |
| Language | Python |
| Category | Agent Tool |
| License | GPL-3.0 |
| Quality Score | 67.6357723180051/100 |
| Open Issues | 7 |
| Last Updated | 2026-04-08 |
| Created | 2024-03-06 |
| Platforms | aws, python |
| Est. Tokens | ~220k |
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Halberd is Halberd : Multi-Cloud Agentic Attack Tool. It is categorized as a Agent Tool with 342 GitHub stars.
Halberd is primarily written in Python. It covers topics such as aws, azure, azuread.
You can find installation instructions and usage details in the Halberd GitHub repository at github.com/vectra-ai-research/Halberd. The project has 342 stars and 35 forks, indicating an active community.
Halberd is released under the GPL-3.0 license, making it free to use and modify according to the license terms.
The top alternatives to Halberd on Agent Skills Hub include Ivy-Framework, terrashark, RedteamAgent. 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: