Detection: Unusually Long Command Line - MLTK

Description

The following analytic identifies unusually long command lines executed on hosts, which may indicate malicious activity. It leverages the Machine Learning Toolkit (MLTK) to detect command lines with lengths that deviate from the norm for a given user. This is significant for a SOC as unusually long command lines can be a sign of obfuscation or complex malicious scripts. If confirmed malicious, this activity could allow attackers to execute sophisticated commands, potentially leading to unauthorized access, data exfiltration, or further compromise of the system.

Search

 1
 2| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes
 3  BY Processes.action Processes.dest Processes.original_file_name
 4     Processes.parent_process Processes.parent_process_exec Processes.parent_process_guid
 5     Processes.parent_process_id Processes.parent_process_name Processes.parent_process_path
 6     Processes.process Processes.process_exec Processes.process_guid
 7     Processes.process_hash Processes.process_id Processes.process_integrity_level
 8     Processes.process_name Processes.process_path Processes.user
 9     Processes.user_id Processes.vendor_product
10
11| `drop_dm_object_name(Processes)`
12
13| `security_content_ctime(firstTime)`
14
15| `security_content_ctime(lastTime)`
16
17| eval processlen=len(process)
18
19| search user!=unknown
20
21| apply cmdline_pdfmodel threshold=0.01
22
23| rename "IsOutlier(processlen)" as isOutlier
24
25| search isOutlier > 0
26
27| table firstTime lastTime user dest process_name process processlen count
28
29| `unusually_long_command_line___mltk_filter`

Data Source

Name	Platform	Sourcetype	Source
Sysmon EventID 1	Windows	'XmlWinEventLog'	'XmlWinEventLog:Microsoft-Windows-Sysmon/Operational'
Windows Event Log Security 4688	Windows	'XmlWinEventLog'	'XmlWinEventLog:Security'
CrowdStrike ProcessRollup2	Other	'crowdstrike:events:sensor'	'crowdstrike'

Macros Used

Annotations

Default Configuration

This detection is configured by default in Splunk Enterprise Security to run with the following settings:

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. In addition, the Machine Learning Toolkit (MLTK) version 4.2 or greater must be installed on your search heads, along with any required dependencies. Finally, the support search "ESCU - Baseline of Command Line Length - MLTK" must be executed before this detection search, because it builds a machine-learning (ML) model over the historical data used by this search. It is important that this search is run in the same app context as the associated support search, so that the model created by the support search is available for use. You should periodically re-run the support search to rebuild the model with the latest data available in your environment.

Known False Positives

Some legitimate applications use long command lines for installs or updates. You should review identified command lines for legitimacy. You may modify the first part of the search to omit legitimate command lines from consideration. If you are seeing more results than desired, you may consider changing the value of threshold in the search to a smaller value. You should also periodically re-run the support search to re-build the ML model on the latest data. You may get unexpected results if the user identified in the results is not present in the data used to build the associated model.

Associated Analytic Story

• Suspicious Command-Line Executions

• Unusual Processes

• Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns

• Ransomware

Detection Testing

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: 9