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Description

The following analytic detects suspicious modifications to the sdclt.exe registry, a technique often used to bypass User Account Control (UAC). It leverages data from Endpoint Detection and Response (EDR) agents, focusing on specific registry paths and values associated with sdclt.exe. This activity is significant because UAC bypasses can allow attackers to execute payloads with elevated privileges without user consent. If confirmed malicious, this could lead to unauthorized code execution, privilege escalation, and potential persistence within the environment, posing a severe security risk.

  • Type: TTP
  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
  • Datamodel: Endpoint
  • Last Updated: 2024-05-12
  • Author: Steven Dick, Teoderick Contreras, Splunk
  • ID: d71efbf6-da63-11eb-8c6e-acde48001122

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1548.002 Bypass User Account Control Privilege Escalation, Defense Evasion
T1548 Abuse Elevation Control Mechanism Privilege Escalation, Defense Evasion
Kill Chain Phase
  • Exploitation
NIST
  • DE.CM
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 BY _time span=1h Processes.user Processes.process_id Processes.process_name Processes.process Processes.process_path Processes.dest Processes.parent_process_name Processes.parent_process Processes.process_guid 
| `drop_dm_object_name(Processes)` 
| join process_guid [ 
| tstats `security_content_summariesonly` count FROM datamodel=Endpoint.Registry WHERE ((Registry.registry_path= "*\\Windows\\CurrentVersion\\App Paths\\control.exe*" OR Registry.registry_path= "*\\exefile\\shell\\runas\\command\\*") (Registry.registry_value_name = "(Default)" OR Registry.registry_value_name = "IsolatedCommand")) BY _time span=1h Registry.registry_path Registry.registry_key_name Registry.registry_value_name Registry.registry_value_data Registry.process_guid 
| `drop_dm_object_name(Registry)`] 
| fields firstTime lastTime dest user parent_process_name parent_process process_name process_path process registry_key_name registry_path registry_value_name registry_value_data process_guid 
| where isnotnull(registry_value_data) 
| `security_content_ctime(firstTime)` 
| `security_content_ctime(lastTime)` 
| `sdclt_uac_bypass_filter`

Macros

The SPL above uses the following Macros:

:information_source: sdclt_uac_bypass_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.user
  • Processes.dest
  • Processes.process_id
  • Processes.process_name
  • Processes.process
  • Processes.process_path
  • Processes.parent_process_name
  • Processes.parent_process
  • Processes.process_guid
  • Registry.dest
  • Registry.registry_value_name
  • Registry.registry_key_name
  • Registry.registry_path
  • Registry.registry_value_data
  • Registry.process_guid

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

Limited to no false positives are expected.

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
63.0 70 90 Suspicious modification of registry $registry_path$ with possible payload path $registry_value_name$ in $dest$

: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