Awesome-Cybersecurity-Datasets VS attack_range

My advice… Don’t rush. Study the material and get a good understanding of the fundamentals. Each certification builds on the previous ones. If Splunk is a path you want to pursue, build those fundamentals. Put in the reps in a lab. Download BOTS, attack range data sets. Take a look at Splunk & Machine Learning YouTube channel. His videos are fantastic and he maintains a GitHub repo so you can use the datasets to practice what you learned on the video.

Somewhat related, but if you’re using splunk, you could use Splunk Attack Range which simulates attacks.

hey I think you are looking at a older repo for the local attack_range, we have not maintained this .. the current Splunk Attack Range lives here: https://github.com/splunk/attack_range/

Since you mention your in-depth ELK workflow, have you tried DetectionLab or Splunk's Attack Range? If you just want a fully working AD domain set up with various hosts, you can spin up the Red Team Attack Lab and then hook in your own logging stuff after it's built.

This is a project I've contributed to at work. It's designed to launch & configure a lab environment for security researchers, but that's not too important. It has a python CLI that takes a configuration file. That config file determines what bits of Terraform and ansible are executed. The Terraform builds instances in AWS (or Azure) and all the associated bits, and then calls the ansible playbook to provision that type of host.

Attack range: https://github.com/splunk/attack_range

have a look at Splunk's Attack Range project, which automates Caldera and Atomic Red Team for these kinds of purposes. i think this might help you as you gauge visibility, rulesets, etc ... https://github.com/splunk/attack_range