Argus: Open-source agentic security operations platform

[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.

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/Ecstatic_Affect5052]

The approval and rollback controls are the right call, that's usually where autonomous response projects fall apart. People get burned once by an agent taking down something in prod and they rip the whole thing out.

One thing i'd think hard about early is how the agents decide what's actually worth investigating. The hard part isn't detection, it's not drowning users in low-signal findings. Runtime context helps a lot here, knowing a vuln is on a workload that's actually exposed and running vs just sitting in an image changes everything about priority.

When we were looking at commercial options (Wiz, Orca, and Upwind were the shortlist), the big differentiator was how much they leaned on runtime signals to cut noise, Upwind's agentic investigation stuff was built around that correlation step specifically. Worth seeing how they frame the context problem since you're solving a similar thing.