This analytic will identify a suspicious command-line that disables a user account using the
net.exe utility native to Windows. This technique may used by the adversaries to interrupt availability of such users to do their malicious act.
- Type: TTP
- Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Datamodel: Endpoint
- Last Updated: 2021-05-04
- Author: Teoderick Contreras, Splunk
- ID: c0325326-acd6-11eb-98c2-acde48001122
Kill Chain Phase
- Actions On Objectives
- CIS 10
1 2 3 4 5 6 | tstats `security_content_summariesonly` values(Processes.process) as process values(Processes.parent_process) as parent_process values(Processes.process_id) as process_id count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where `process_net` AND Processes.process="*user*" AND Processes.process="*/active:no*" by Processes.process_name Processes.original_file_name Processes.dest Processes.user Processes.parent_process_name | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `disabling_net_user_account_filter`
The SPL above uses the following Macros:
disabling_net_user_account_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
The detection is based on data that originates from Endpoint Detection and Response (EDR) agents. These agents are designed to provide security-related telemetry from the endpoints where the agent is installed. To implement this search, you must ingest logs that contain the process GUID, process name, and parent process. Additionally, you must ingest complete command-line executions. These logs must be processed using the appropriate Splunk Technology Add-ons that are specific to the EDR product. The logs must also be mapped to the
Processes node of the
Endpoint data model. Use the Splunk Common Information Model (CIM) to normalize the field names and speed up the data modeling process.
Known False Positives
Associated Analytic Story
|42.0||70||60||An instance of $parent_process_name$ spawning $process_name$ was identified disabling a user account on endpoint $dest$ by user $user$.|
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.
source | version: 2