LoFP / 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.

Techniques

Sample rules

Unusually Long Command Line - MLTK

• source: splunk
• technicques:

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.

Detection logic

| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes by Processes.user Processes.dest Processes.process_name Processes.process 
| `drop_dm_object_name(Processes)` 
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| eval processlen=len(process) 
| search user!=unknown 
| apply cmdline_pdfmodel threshold=0.01 
| rename "IsOutlier(processlen)" as isOutlier 
| search isOutlier > 0 
| table firstTime lastTime user dest process_name process processlen count 
| `unusually_long_command_line___mltk_filter`