Mshta spawning Rundll32 OR Regsvr32 Process
This search is to detect a suspicious mshta.exe process that spawn rundll32 or regsvr32 child process. This technique was seen in several malware nowadays like trickbot to load its initial .dll stage loader to execute and download the the actual trickbot payload.
- Type: TTP
- Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Datamodel: Endpoint
- Last Updated: 2021-07-19
- Author: Teoderick Contreras, Splunk
- ID: 4aa5d062-e893-11eb-9eb2-acde48001122
Kill Chain Phase
1 2 3 4 5 6 | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.parent_process_name = "mshta.exe" `process_rundll32` OR `process_regsvr32` by Processes.parent_process Processes.process_name Processes.process Processes.process_id Processes.process_guid Processes.user Processes.dest | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)` |`security_content_ctime(lastTime)` | `mshta_spawning_rundll32_or_regsvr32_process_filter`
The SPL above uses the following Macros:
mshta_spawning_rundll32_or_regsvr32_process_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.
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
limitted. this anomaly behavior is not commonly seen in clean host.
Associated Analytic Story
|56.0||70||80||a mshta parent process $parent_process_name$ spawn child process $process_name$ 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.
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replay.py tool or the UI.
Alternatively you can replay a dataset into a Splunk Attack Range
source | version: 2