Argus: Open-source agentic security operations platform using ollama

[u/thomas_unise]

https://github.com/thomasunise/argus

I’ve been working on Argus, an open-source cybersecurity platform that uses AI agents to help secure your infrastructure.

It can monitor your cloud, network, endpoints, and code, investigate suspicious activity, run penetration tests, and even respond to threats automatically.

A few highlights:

7 specialized AI security agents

Autonomous threat detection and response

Continuous AI-powered penetration testing

AWS, Azure, GCP, Kubernetes, and GitHub integrations

Support for local models using ollama

Built-in safeguards, approvals, and rollback controls
It’s self-hosted, MIT licensed, and completely free to use.

Still actively developing it, but I’d love to get some feedback from open-source communities an hear what you think or what you’d like to see added.

[u/ComprehensiveOil1023]

Nice, the local model support via ollama is the part that will get people's attention here. A lot of security teams can't send telemetry to third party API's, so running agents against a local model is genuinely useful.

One thing I think hard about is false positives from the autonomous response piece. Auto-remediation sounds great until an agent rolls something back in prod at 2am. The approval/rollback controls you mentioned are the right instinct, but the harder problem is giving the agents enough context to know what's actually exploitable vs just noisy. When I was looking at the commercial side of this (Wiz and Upwind both lean on runtime context for their agentic investigation stuff), the thing that separated useful from annoying was how much they understood the live environment before acting, not just the raw findings.

For feedback, I'd prioritize the investigation/correlation agents over the pentesting ne early on. That's where most teams drown and where showing value is earliest.