#99th of 19 in Security

aisoc

Self-hosted SOC that detects threats and investigates alerts with auditable AI agents

Stars
7.2k
License
MIT
Last commit
Nov 2026
Last release
Nov 2026
Language
Python
Stars, last 28 weeks+6,989
27 Apr 2026: 259 stars4 May 2026: 263 stars11 May 2026: 558 stars18 May 2026: 908 stars25 May 2026: 964 stars1 Jun 2026: 1,169 stars8 Jun 2026: 1,271 stars15 Jun 2026: 1,310 stars22 Jun 2026: 1,368 stars29 Jun 2026: 1,397 stars6 Jul 2026: 1,433 stars13 Jul 2026: 1,448 stars20 Jul 2026: 1,572 stars27 Jul 2026: 1,743 stars3 Aug 2026: 1,770 stars10 Aug 2026: 1,834 stars17 Aug 2026: 2,376 stars24 Aug 2026: 2,437 stars31 Aug 2026: 2,455 stars7 Sept 2026: 2,466 stars14 Sept 2026: 2,471 stars21 Sept 2026: 2,505 stars28 Sept 2026: 2,520 stars5 Oct 2026: 2,534 stars12 Oct 2026: 2,555 stars19 Oct 2026: 2,574 stars26 Oct 2026: 3,901 stars2 Nov 2026: 6,311 stars9 Nov 2026: 7,248 stars

259 on 27 Apr 20267,248 on 9 Nov 2026

From GitHub's daily star counts.

Checked on GitHub.

Overview

AiSOC ingests security telemetry through 91 connectors and four cloud collectors, runs 2966 executable detection rules, correlates alerts into incidents, and has AI agents triage them. Every prompt and tool call goes to an Investigation Ledger that exports as a signed bundle, and response actions need human approval. The core stack bundles a local llama3.2:3b model via Ollama and runs on Kafka, Postgres, Redis and Qdrant.

Who it is for: Security teams self-hosting an AI-assisted SOC with human-approved response

Strengths

  • Every agent prompt, tool call and citation is logged and exports as a signed evidence bundle
  • Ships a local model, so triage works with no API key or hosted provider
  • Response actions and playbooks default to preview and need a separate approver
  • Detection rules count as executable only after replay proves they fire

Weaknesses

  • Heavy stack: 16 services and about 8 GB RAM for core, about 12 GB for full
  • No hosted LLM provider has been tested; bundled 3B model is not frontier-class
  • Event lake, entity graph and full-text search need the larger full profile
  • Splunk rule migration is mostly partial: 1,711 of 1,734 translated rules

What it needs

  • RAM ≥ 8 GB
  • GPU optional
  • Compose
  • Needs Docker Compose v2, Kafka, Postgres, Redis, Qdrant, Ollama, ClickHouse (full), Neo4j (full), OpenSearch (full)
  • Models: Ollama llama3.2:3b-instruct-q4_K_M (bundled), Local OpenAI-compatible endpoints, Custom providers via console

What changed

  1. v23.1.0 ↗ (opens in a new tab)Security fix

    “The Splunk connector validates the operator-supplied index= token”

  2. v23.0.0 ↗ (opens in a new tab)BreakingSecurity fix

    “DeploymentConfig and DeploymentConfigUpdate drop the self-update”

    GHSA-HRC5-W9R3-2G8R, GHSA-GHPM-VC6J-HP5R, GHSA-CVFR-9R25-GQPF, GHSA-QP9F-459J-W89C, GHSA-9Q6P-M345-H3HJ. “404 and 403 are no longer one branch, here or anywhere else in the connector tree. A 403 on audit events is the token not owning the group or the plan not including them, and stays an info line; a 40…”

From the release notes. No flag means the note does not say so, not that the upgrade is safe.

Quick answers

Is aisoc open source?

Yes. Its code is on GitHub under the MIT license.

Can you run aisoc with Docker?

Yes. Its repository has a Docker setup: a Dockerfile, a Compose file or a published image.

Does aisoc need a GPU?

No. It runs on a CPU and can use a GPU when you have one. Plan for at least 8 GB of RAM.

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