:no_entry: 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.

Try in Splunk Security Cloud

Description

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

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1204.002 Malicious File Execution
Kill Chain Phase
  • Actions on Objectives
NIST
  • ID.AM
  • PR.DS
CIS20
  • CIS 2
CVE 


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`

Macros

The SPL above uses the following Macros:

:information_source: 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.

Required fields

List of fields required to use this analytic.

  • _time

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

None identified

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
25.0 50 50 tbd

:information_source: The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.

Reference

Test Dataset

Replay any dataset to Splunk Enterprise by using our replay.py tool or the UI. Alternatively you can replay a dataset into a Splunk Attack Range

source | version: 4