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Description

This analytic look for a spawned runas.exe process with a administrator user option parameter. This parameter was abused by adversaries, malware author or even red teams to gain elevated privileges in target host. This is a good hunting query to figure out privilege escalation tactics that may used for different stages like lateral movement but take note that administrator may use this command in purpose so its better to see other event context before and after this analytic.

  • Type: Hunting
  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
  • Datamodel: Endpoint
  • Last Updated: 2023-04-14
  • Author: Teoderick Contreras, Splunk
  • ID: 4807e716-43a4-11ec-a0e7-acde48001122

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1134 Access Token Manipulation Defense Evasion, Privilege Escalation
T1134.001 Token Impersonation/Theft Defense Evasion, Privilege Escalation
Kill Chain Phase
  • Exploitation
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=Endpoint.Processes where `process_runas` AND Processes.process = "*/user:*" AND Processes.process = "*admin*" by Processes.dest Processes.user Processes.parent_process_name Processes.parent_process Processes.process_name Processes.process Processes.process_id Processes.parent_process_id 
| `drop_dm_object_name(Processes)` 
| `security_content_ctime(firstTime)` 
| `security_content_ctime(lastTime)` 
| `runas_execution_in_commandline_filter`

Macros

The SPL above uses the following Macros:

:information_source: runas_execution_in_commandline_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
  • Processes.dest
  • Processes.user
  • Processes.parent_process_name
  • Processes.parent_process
  • Processes.process_name
  • Processes.process
  • Processes.process_id
  • Processes.parent_process_id

How To Implement

The detection is based on data that originates from Endpoint Detection and Response (EDR) agents. These agents are designed to provide security-related telemetry from the endpoints where the agent is installed. To implement this search, you must ingest logs that contain the process GUID, process name, and parent process. Additionally, you must ingest complete command-line executions. These logs must be processed using the appropriate Splunk Technology Add-ons that are specific to the EDR product. The logs must also be mapped to the Processes node of the Endpoint data model. Use the Splunk Common Information Model (CIM) to normalize the field names and speed up the data modeling process.

Known False Positives

A network operator or systems administrator may utilize an automated or manual execute this command that may generate false positives. filter is needed.

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
25.0 50 50 elevated process using runas on $dest$ by $user$

: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

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