ID | Technique | Tactic |
---|---|---|
T1531 | Account Access Removal | Impact |
Detection: Excessive Usage Of Net App
Description
The following analytic detects excessive usage of net.exe
or net1.exe
within a one-minute interval. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names, parent processes, and command-line executions. This behavior is significant as it may indicate an adversary attempting to create, delete, or disable multiple user accounts rapidly, a tactic observed in Monero mining incidents. If confirmed malicious, this activity could lead to unauthorized user account manipulation, potentially compromising system integrity and enabling further malicious actions.
Search
1
2| tstats `security_content_summariesonly` values(Processes.process) as process values(Processes.process_id) as process_id count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where `process_net` by Processes.process_name Processes.parent_process_name Processes.original_file_name Processes.dest Processes.user _time span=1m
3| where count >=10
4| `drop_dm_object_name(Processes)`
5| `security_content_ctime(firstTime)`
6| `security_content_ctime(lastTime)`
7| `excessive_usage_of_net_app_filter`
Data Source
Name | Platform | Sourcetype | Source |
---|---|---|---|
CrowdStrike ProcessRollup2 | N/A | 'crowdstrike:events:sensor' |
'crowdstrike' |
Sysmon EventID 1 | Windows | 'xmlwineventlog' |
'XmlWinEventLog:Microsoft-Windows-Sysmon/Operational' |
Windows Event Log Security 4688 | Windows | 'xmlwineventlog' |
'XmlWinEventLog:Security' |
Macros Used
Name | Value |
---|---|
process_net | (Processes.process_name="net.exe" OR Processes.original_file_name="net.exe" OR Processes.process_name="net1.exe" OR Processes.original_file_name="net1.exe") |
excessive_usage_of_net_app_filter | search * |
excessive_usage_of_net_app_filter
is an empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
Annotations
Default Configuration
This detection is configured by default in Splunk Enterprise Security to run with the following settings:
Setting | Value |
---|---|
Disabled | true |
Cron Schedule | 0 * * * * |
Earliest Time | -70m@m |
Latest Time | -10m@m |
Schedule Window | auto |
Creates Risk Event | True |
Implementation
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
unknown. Filter as needed. Modify the time span as needed.
Associated Analytic Story
Risk Based Analytics (RBA)
Risk Message | Risk Score | Impact | Confidence |
---|---|---|---|
Excessive usage of net1.exe or net.exe within 1m, with command line $process$ has been detected on $dest$ by $user$ | 28 | 40 | 70 |
References
Detection Testing
Test Type | Status | Dataset | Source | Sourcetype |
---|---|---|---|---|
Validation | ✅ Passing | N/A | N/A | N/A |
Unit | ✅ Passing | Dataset | XmlWinEventLog:Microsoft-Windows-Sysmon/Operational |
XmlWinEventLog |
Integration | ✅ Passing | Dataset | XmlWinEventLog:Microsoft-Windows-Sysmon/Operational |
XmlWinEventLog |
Replay any dataset to Splunk Enterprise by using our replay.py
tool or the UI.
Alternatively you can replay a dataset into a Splunk Attack Range
Source: GitHub | Version: 4