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Description

The following analytic detects the execution of sdbinst.exe with parameters indicative of silently creating a shim database. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names, parent processes, and command-line arguments. This activity is significant because shim databases can be used to intercept and manipulate API calls, potentially allowing attackers to bypass security controls or achieve persistence. If confirmed malicious, this could enable unauthorized code execution, privilege escalation, or persistent access to the compromised system.

  • Type: TTP
  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
  • Datamodel: Endpoint
  • Last Updated: 2024-05-09
  • Author: David Dorsey, Splunk
  • ID: 404620de-46d8-48b6-90cc-8a8d7b0876a3

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1546.011 Application Shimming Privilege Escalation, Persistence
T1546 Event Triggered Execution Privilege Escalation, Persistence
Kill Chain Phase
  • Exploitation
  • Installation
NIST
  • DE.CM
CIS20
  • CIS 10
CVE 


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| tstats `security_content_summariesonly` values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = sdbinst.exe by Processes.process_name Processes.parent_process_name Processes.dest Processes.user 
| `drop_dm_object_name(Processes)` 
| `security_content_ctime(firstTime)` 
| `security_content_ctime(lastTime)` 
| `shim_database_installation_with_suspicious_parameters_filter`

Macros

The SPL above uses the following Macros:

:information_source: shim_database_installation_with_suspicious_parameters_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.process_name
  • Processes.parent_process_name
  • Processes.dest
  • Processes.user

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

None identified

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
63.0 70 90 A process $process_name$ that possible create a shim db silently in host $dest$

: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: 5