The following analytic is to identify a process that imports applocker xml policy using PowerShell commandlet. This technique was seen in Azorult malware where it drop an xml Applocker policy that will deny several AV products and further executed the PowerShell Applocker commandlet.
- Type: Hunting
- Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Datamodel: Endpoint
- Last Updated: 2022-06-24
- Author: Teoderick Contreras, Splunk
- ID: 467ed9d9-8035-470e-ad5e-ae5189283033
Kill Chain Phase
- CIS 3
- CIS 5
- CIS 16
1 2 3 4 5 6 | tstats `security_content_summariesonly` values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where `process_powershell` AND Processes.process="*Import-Module Applocker*" AND Processes.process="*Set-AppLockerPolicy *" AND Processes.process="* -XMLPolicy *" by Processes.dest Processes.user Processes.parent_process Processes.process_name Processes.original_file_name Processes.process Processes.process_id Processes.parent_process_id | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `windows_impair_defense_add_xml_applocker_rules_filter`
The SPL above uses the following Macros:
windows_impair_defense_add_xml_applocker_rules_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
List of fields required to use this analytic.
How To Implement
To successfully implement this search you need to be ingesting information on process that include the name of the process responsible for the changes from your endpoints into the
Endpoint datamodel in the
Processes node. In addition, confirm the latest CIM App 4.20 or higher is installed and the latest TA for the endpoint product.
Known False Positives
Administrators may execute this command that may cause some false positive.
Associated Analytic Story
|25.0||50||50||Applocker importing xml policy command was executed in $dest$|
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.
source | version: 1