Stat! 3 Must-Have Data Filtering Techniques
Data filtering techniques for threat hunting Why is filtering data important? Well, Splunk allows you to store gigabytes, terabytes, or even petabytes of full-fidelity security data — yet the evidence you are seeking during a hunt or investigation is often contained in just a few events. You need to eliminate the noise and expose the signal. To do this, we will focus on three specific techniques for filtering data that you can start using right away. For all three tutorials, below, we use data from our Boss of the SOC v1.0 data set. Technique 1. It’s About Time: Specifying a time range The most obvious (but often overlooked) technique for reducing the number of events returned by your Splunk search — and getting you closer to actionable results — is to specify an appropriate time range. If you can put a left and right boundary on the timeline of your hunt, you enable Splunk to ignore events from time periods that have nothing to do with your hypothesis, ...