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Description

The following analytic identifies the execution of risky commands within the Splunk platform, such as runshellscript, delete, and sendemail. It leverages the Search_Activity data model to detect ad hoc searches containing these commands, excluding those run by the splunk-system-user. This activity is significant because it may indicate attempts at data exfiltration, deletion, or other unauthorized actions by a malicious user. If confirmed malicious, this could lead to data loss, unauthorized data transfer, or system compromise, severely impacting the organization's security posture.

  • Type: Hunting
  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
  • Datamodel: Splunk_Audit
  • Last Updated: 2024-05-19
  • Author: Michael Haag, Splunk
  • ID: 1cf58ae1-9177-40b8-a26c-8966040f11ae

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1059 Command and Scripting Interpreter Execution
Kill Chain Phase
  • Installation
NIST
  • DE.AE
CIS20
  • CIS 10
CVE 


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| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Splunk_Audit.Search_Activity where Search_Activity.search IN ("*
| runshellscript *", "*
| collect *","*
| delete *", "*
| fit *", "*
| outputcsv *", "*
| outputlookup *", "*
| run *", "*
| script *", "*
| sendalert *", "*
| sendemail *", "*
| tscolle*") Search_Activity.search_type=adhoc Search_Activity.user!=splunk-system-user by Search_Activity.search Search_Activity.info Search_Activity.total_run_time Search_Activity.user Search_Activity.search_type 
| `drop_dm_object_name(Search_Activity)` 
| `security_content_ctime(firstTime)` 
| `security_content_ctime(lastTime)` 
| `splunk_command_and_scripting_interpreter_risky_commands_filter`

Macros

The SPL above uses the following Macros:

:information_source: splunk_command_and_scripting_interpreter_risky_commands_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
  • Search_Activity.search
  • Search_Activity.info
  • Search_Activity.total_run_time
  • Search_Activity.user
  • Search_Activity.savedsearch_name
  • Search_Activity.search_type

How To Implement

To successfully implement this search acceleration is recommended against the Search_Activity datamodel that runs against the splunk _audit index. In addition, this analytic requires the Common Information Model App which includes the Splunk Audit Datamodel https://splunkbase.splunk.com/app/1621/. Splunk SOAR customers can find a SOAR workbook that walks an analyst through the process of running these hunting searches in the references list of this detection. In order to use this workbook, a user will need to run a curl command to post the file to their SOAR instance such as "curl -u username:password https://soar.instance.name/rest/rest/workbook_template -d @splunk_psa_0622.json". A user should then create an empty container or case, attach the workbook, and begin working through the tasks.

Known False Positives

False positives will be present until properly filtered by Username and search name.

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
20.0 50 40 A risky Splunk command has ran by $user$ and should be reviewed.

: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: 2