Windows WMI Impersonate Token
The following analytic identifies a possible wmi token impersonation activities in a process or command. This technique was seen in Qakbot malware where it will execute a vbscript code contains wmi impersonation object to gain privilege escalation or as defense evasion. This Anomaly detection looks for wmiprvse.exe SourceImage having a duplicate handle or full granted access in a target process.
- Type: Anomaly
- Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Datamodel: Endpoint
- Last Updated: 2022-10-24
- Author: Teoderick Contreras, Splunk
- ID: cf192860-2d94-40db-9a51-c04a2e8a8f8b
Kill Chain Phase
- CIS 3
- CIS 5
- CIS 16
1 2 3 4 5 `sysmon` EventCode=10 SourceImage = "*\\wmiprvse.exe" GrantedAccess IN ("0x1478", "0x1fffff") | stats count min(_time) as firstTime max(_time) as lastTime by SourceImage TargetImage SourceProcessGUID TargetProcessGUID SourceProcessId TargetProcessId GrantedAccess CallTrace Computer | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `windows_wmi_impersonate_token_filter`
The SPL above uses the following Macros:
windows_wmi_impersonate_token_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
This search requires Sysmon Logs and a Sysmon configuration, which includes EventCode 10. This search uses an input macro named
sysmon. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives.
Known False Positives
administrator may execute impersonate wmi object script for auditing. Filter is needed.
Associated Analytic Story
|25.0||50||50||wmiprvse.exe process having a duplicate or full Granted Access $GrantedAccess$ to $TargetImage$ process 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.
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