Hi,
In our application we have data in a specific format. We are converting this data to CIM model (say IntrusionDetection, Malware etc) and then uploading to Splunk.
Now once its get uploaded I want to verify from Splunk side whether that data is as per specific CIM model or not.
How to go ahead with this?
One useful thing is the CIM Validation datamodel. This can help to find what extractions are still missing or which are misnamed. You can install the CIM on a new test Splunk instance and feed a bit of the data to it and test, or if you are already pumping that data into your regular Splunk install, well, that's OK too. 🙂
I've also found usefulness from just cracking open the appropriate datamodel and doing some pivots. A lot can be determined if you have a reasonably well known set of data and run some confirming pivots on that data.
And more importantly there is no directory called $SPLUNK_HOME/etc/apps/Splunk_SA_CIM/default
My bad..I was looking at different Splunk instance 😞
I am able to see missing extractions using CIM Validation datamodel..thank you.
Now trying how can I use CIM Validation datamodel with python.
Yes, I went through CIM Validation datamodel but I am not able to make much out of it.
Could you please try to explain with example?
Hi rich7177,
Could you please elaborate more on this as I am new to Splunk. And more importantly I wanted to this with automation.
Thanks
Rupeshshiremath, did you try reviewing the link to the CIM Validation datamodel that Rich posted?