THIS IS A DEPRECATED DETECTION
This detection has been marked deprecated by the Splunk Threat Research team. This means that it will no longer be maintained or supported.
This search looks for applications on the endpoint that you have marked as uncommon.
- Type: Hunting
- Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Datamodel: Endpoint
- Last Updated: 2020-07-22
- Author: David Dorsey, Splunk
- ID: 29ccce64-a10c-4389-a45f-337cb29ba1f7
Kill Chain Phase
- Actions on Objectives
- CIS 2
1 2 3 4 5 6 7 | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes by Processes.dest Processes.user Processes.process Processes.process_name | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `drop_dm_object_name(Processes)` | `uncommon_processes` |`uncommon_processes_on_endpoint_filter`
The SPL above uses the following Macros:
uncommon_processes_on_endpoint_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
List of fields required to use this analytic.
How To Implement
You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. This search uses a lookup file
uncommon_processes_default.csv to track various features of process names that are usually uncommon in most environments. Please consider updating
uncommon_processes_local.csv to hunt for processes that are uncommon in your environment.
Known False Positives
Associated Analytic Story
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.
source | version: 4