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 beenuar · MCP Server · ★ 2.4k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is AiSOC safe to install? View the security audit →
AiSOC An open-source, self-hostable AI Security Operations Center. It ingests your security telemetry, detects and correlates threats, investigates them with AI agents whose reasoning is fully auditable, and proposes responses a human approves. Docs · Architecture · What actually works · Discussions What AiSOC does Telemetry arrives from your security tools. AiSOC normalizes it, runs 833 executable detection rules over it, groups what fires into incidents,
| Stars | 2,380 |
| Forks | 265 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 68.9956162960755/100 |
| Open Issues | 4 |
| Last Updated | 2026-10-03 |
| Created | 2026-05-02 |
| Platforms | claude-code, mcp, python |
| Est. Tokens | ~16k |
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AiSOC is Open-source AI Security Operations Center: alert fusion, LLM-agent triage, MITRE ATT&CK investigation, and a replayable decision ledger for every agent step. Self-hostable, runs with no API keys, MIT . It is categorized as a MCP Server with 2.4k GitHub stars.
AiSOC is primarily written in Python. It covers topics such as agentic-ai, ai-security, alert-triage.
You can find installation instructions and usage details in the AiSOC GitHub repository at github.com/beenuar/AiSOC. The project has 2.4k stars and 265 forks, indicating an active community.
AiSOC is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to AiSOC on Agent Skills Hub include mcp-security, Adrian, cve-mcp-server. 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: