Shim Database Installation With Suspicious Parameters
Description
This search detects the process execution and arguments required to silently create a shim database. The sdbinst.exe application is used to install shim database files (.sdb). A shim is a small library which transparently intercepts an API, changes the parameters passed, handles the operation itself, or redirects the operation elsewhere.
- Type: TTP
- Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Datamodel: Endpoint
- Last Updated: 2020-11-23
- Author: David Dorsey, Splunk
- ID: 404620de-46d8-48b6-90cc-8a8d7b0876a3
Annotations
ATT&CK
Kill Chain Phase
- Actions on Objectives
NIST
- DE.CM
CIS20
- CIS 8
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:
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.
Supported Add-on (TA)
List of Splunk Add-on’s tested to work with the analytic.
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
You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model.
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 $dest$ |
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