Detect Renamed WinRAR
The following analtyic identifies renamed instances of
WinRAR.exe. In most cases, it is not common for WinRAR to be used renamed, however it is common to be installed by a third party application and executed from a non-standard path. During triage, validate additional metadata from the binary that this is
WinRAR. Review parallel processes and file modifications.
- Type: Hunting
- Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Datamodel: Endpoint
- Last Updated: 2021-09-16
- Author: Michael Haag, Splunk
- ID: 1b7bfb2c-b8e6-11eb-99ac-acde48001122
Kill Chain Phase
- CIS 10
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.original_file_name=WinRAR.exe (Processes.process_name!=rar.exe OR Processes.process_name!=winrar.exe) by Processes.dest Processes.user Processes.parent_process_name Processes.process_name Processes.process Processes.process_id Processes.parent_process_id Processes.original_file_name | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `detect_renamed_winrar_filter`
The SPL above uses the following Macros:
detect_renamed_winrar_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
Unknown. It is possible third party applications use renamed instances of WinRAR.
Associated Analytic Story
|27.0||30||90||The following $process_name$ has been identified as renamed, spawning from $parent_process_name$ on $dest$ by $user$.|
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: 3