by digitranslab · Agent Tool · ★ 197
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🔒 Is allama safe to install? View the security audit →
Allama Open-Source AI Security Automation Automate threat detection and response with AI-powered workflows. Self-hosted. 80+ integrations. Built for modern SOC teams. Why Allama • Features • Quick Start • Architecture Why Allama? Security teams face 500+ alerts daily. Manual investigation is slow, inconsistent, and burns out analysts. Legacy SOAR tools cost $100k+ and require consultants to implement. Allama changes this: 90% faster triage — AI agents enrich and prioritise alerts automatically Zero vendor lock-in — 100% open source, self-hosted on your infrastructure No coding required — Visual workflow builder for common automation -
git clone https://github.com/digitranslab/allama.gitTaken from the project's README on GitHub. Check the security audit before running it.
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 →
| Stars | 197 |
| Forks | 18 |
| Language | Python |
| Category | Agent Tool |
| License | AGPL-3.0 |
| Quality Score | 66.0483100462084/100 |
| Open Issues | 3 |
| Last Updated | 2026-02-11 |
| Created | 2026-01-30 |
| Platforms | python |
| Est. Tokens | ~1617k |
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allama is 🔥🔥🔥 AI security automation platform. Build visual workflows, deploy autonomous agents, and automate threat detection and response. 80+ integrations with SIEM, EDR, ticketing, and cloud tools. Self-. It is categorized as a Agent Tool with 197 GitHub stars.
allama is primarily written in Python. It covers topics such as ai, ai-agents, ai-agents-framework.
The README on GitHub (github.com/digitranslab/allama) gives: git clone https://github.com/digitranslab/allama.git. Usage details are in the same README.
allama is released under the AGPL-3.0 license, making it free to use and modify according to the license terms.
The top alternatives to allama on Agent Skills Hub include Wazuh-MCP-Server, ai_for_the_win, Awesome-AI-For-Security. 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: