Detection: Shim Database Installation With Suspicious Parameters

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

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.

1
2| 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 
3| `drop_dm_object_name(Processes)` 
4| `security_content_ctime(firstTime)` 
5| `security_content_ctime(lastTime)` 
6| `shim_database_installation_with_suspicious_parameters_filter`

Data Source

Name Platform Sourcetype Source Supported App
CrowdStrike ProcessRollup2 N/A 'crowdstrike:events:sensor' 'crowdstrike' N/A

Macros Used

Name Value
security_content_ctime convert timeformat="%Y-%m-%dT%H:%M:%S" ctime($field$)
shim_database_installation_with_suspicious_parameters_filter search *
shim_database_installation_with_suspicious_parameters_filter is an empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Annotations

- MITRE ATT&CK
+ Kill Chain Phases
+ NIST
+ CIS
- Threat Actors
ID Technique Tactic
T1546.011 Application Shimming Persistence
T1546 Event Triggered Execution Privilege Escalation
KillChainPhase.EXPLOITAITON
KillChainPhase.INSTALLATION
NistCategory.DE_CM
Cis18Value.CIS_10
FIN7

Default Configuration

This detection is configured by default in Splunk Enterprise Security to run with the following settings:

Setting Value
Disabled true
Cron Schedule 0 * * * *
Earliest Time -70m@m
Latest Time -10m@m
Schedule Window auto
Creates Notable Yes
Rule Title %name%
Rule Description %description%
Notable Event Fields user, dest
Creates Risk Event True
This configuration file applies to all detections of type TTP. These detections will use Risk Based Alerting and generate Notable Events.

Implementation

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

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
A process $process_name$ that possible create a shim db silently in host $dest$ 63 70 90
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.

Detection Testing

Test Type Status Dataset Source Sourcetype
Validation ✅ Passing N/A N/A N/A
Unit ✅ Passing Dataset XmlWinEventLog:Microsoft-Windows-Sysmon/Operational xmlwineventlog
Integration ✅ Passing Dataset XmlWinEventLog:Microsoft-Windows-Sysmon/Operational xmlwineventlog

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: GitHub | Version: 5