Detection: Create Local User Accounts Using Net Exe

Description

The following analytic detects the creation of local administrator accounts using the net.exe command to mitigate the risks associated with unauthorized access and prevent further damage to the environment by responding to potential threats earlier and taking appropriate actions to protect the organization's systems and data. This detection is made by a Splunk query to search for processes with the name net.exe or net1.exe that include the "/add" parameter in their process name. This detection is important because the creation of unauthorized local user accounts might indicate that an attacker has successfully created a new user account and is trying to gain persistent access to a system or escalate their privileges for data theft, or other malicious activities. False positives might occur since there might be legitimate uses of the net.exe command and the creation of user accounts in certain circumstances. You must consider the context of the activity and other indicators of compromise before taking any action. For next steps, review the details of the identified process, including the user, parent process, and parent process name. Examine any relevant on-disk artifacts and look for concurrent processes to determine the source of the attack.

Annotations

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Implementation

To successfully implement this search, you need to be ingesting logs with the process name, parent process, and command-line executions from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. Tune and filter known instances where renamed net.exe may be used.

Known False Positives

System administrators or scripts may add user accounts via this technique. Filter as needed.

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
An instance of $parent_process_name$ spawning $process_name$ was identified on endpoint $dest$ by user $user$ attempting to add a user to the local group. 9 30 30
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.

References


Version: 6