Splunk tstats example how to#
Splunk tstats example software#

Optional arguments append Syntax: append= Description: When in prestats mode ( prestats=true), enables append=true where the prestats results append to existing results, instead of generating them. For an overview about using functions with commands, see Statistical and charting functions. Use the links in the table to see descriptions and examples for each function. The following table lists the supported functions by type of function. See Usage to learn more about using PREFIX(), and about searches you can run to find raw segments in your data.

You cannot use wildcards to specify field names. You cannot specify functions without applying them to fields or eval expressions that resolve into fields. You can also rename the result using the AS keyword, unless you are in prestats mode ( prestats=true). You can apply the function to a field, or to a PREFIX() directive if you want to aggregate a raw segment in your indexed events as if it were an extracted field-value pair. For a list of the supported functions for the tstats command, refer to the table below.

Description: Either perform a basic count of a field or perform a function on a field. ] Required arguments Syntax: (count | (PREFIX() | )). The indexed fields can be from indexed data or accelerated data models.īecause it searches on index-time fields instead of raw events, the tstats command is faster than the stats command.īy default, the tstats command runs over accelerated and unaccelerated data models. Quick Hunt Process Name Processes | tstats summariesonly=t values(Processes.process) from datamodel=Endpoint.Processes where (Processes.process='*$process_name_token$*') groupby Processes.parent_process_name | rename Processes.parent_process_name AS ParentProcess, values(Processes.process) AS CommandLine now none progressbar Network Activity | tstats summariesonly=t values(Processes.process_exec) from datamodel=Endpoint.Processes where (Processes.process_exec='*$process_name_token$*') groupby Processes.DestinationIp,Processes.DestinationPort | rename Processes.DestinationIp AS DestinationIP, Processes.DestinationPort AS DestinationPort, values(Processes.process_exec) AS ProcessName now none progressbar Image Loads | tstats summariesonly=t values(ImageLoads.ImageLoaded) from datamodel=Endpoint.ImageLoads where (ImageLoads.Image = '*$process_name_token$*') groupby ImageLoads.Image | rename ImageLoads.Image as 'Image', values(ImageLoads.ImageLoaded) as 'Images Loaded' now none Processes to Network Image ProcessGuidS index=sysmon EventCode=1 | eval ProcessGuidS = tostring(ProcessGuid) | table ProcessGuidS,Image now Network and Process | tstats summariesonly=t prestats=t values(Processes.process),values(Processes.parent_process),values(Processes.process_current_directory) from datamodel=Endpoint.Processes WHERE Processes.process_guid='*$process_guid_token$*' by Processes.process_guid | tstats summariesonly=t append=t prestats=t values(st),values(Ports.src),values(st_port) from datamodel=Endpoint.Ports WHERE Ports.process_guid='*$process_guid_token$*' by Ports.process_guid | rename Ports.process_guid as GUID, Processes.process_guid as GUID | stats values(st),values(Ports.src),values(st_port),values(Processes.process),values(Processes.process_current_directory),values(Processes.Use the tstats command to perform statistical queries on indexed fields in tsidx files.

Splunk tstats example how to#

I won’t go into huge detail about how to set up Splunk and data models, but you will need the following to get started:

Splunk tstats example software#

These specialized searches are used by Splunk software to generate reports for Pivot users.Īnother, more accessible way that I had this explained to me was that data models take unstructured data and make it structuredĪccelerated searches using Splunk data models return results almost instantly, even across large data sets. It encodes the domain knowledge necessary to build a variety of specialized searches of those datasets. What are data models?Īccording to Splunk’s documents, data models are:Ī data model is a hierarchically structured search-time mapping of semantic knowledge about one or more datasets. In this post, I wanted to highlight a feature in Splunk that helps – at least in part – address the challenge of hunting at scale: data models and tstats. Enabling different logging and sending those logs to some kind of centralized SIEM device sounds relatively straight forward at a high-level, but dealing with tens or even hundreds of thousands of endpoints presents us with huge challenges. One of the aspects of defending enterprises that humbles me the most is scale.