THIS IS A EXPERIMENTAL DETECTION
This detection has been marked experimental by the Splunk Threat Research team. This means we have not been able to test, simulate, or build datasets for this detection. Use at your own risk. This analytic is NOT supported.
The following analytic identifies suspicious processes spawning from WinRM (wsmprovhost.exe). This analytic is related to potential exploitation of CVE-2021-31166. which is a kernel-mode device driver http.sys vulnerability. Current proof of concept code will blue-screen the operating system. However, http.sys used by many different Windows processes, including WinRM. In this case, identifying suspicious process create (child processes) from
wsmprovhost.exe is what this analytic is identifying.
- Type: TTP
- Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Datamodel: Endpoint
- Last Updated: 2021-05-21
- Author: Drew Church, Michael Haag, Splunk
- ID: a081836a-ba4d-11eb-8593-acde48001122
Kill Chain Phase
- Actions on Objectives
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=wsmprovhost.exe Processes.process_name IN ("cmd.exe","sh.exe","bash.exe","powershell.exe","pwsh.exe","schtasks.exe","certutil.exe","whoami.exe","bitsadmin.exe","scp.exe") by Processes.dest Processes.user Processes.parent_process Processes.process_name Processes.process Processes.process_id Processes.parent_process_id | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `winrm_spawning_a_process_filter`
The SPL above uses the following Macros:
winrm_spawning_a_process_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
Known False Positives
Unknown. Add new processes or filter as needed. It is possible system management software may spawn processes from
Associated Analytic Story
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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