Windows Command Obfuscation with Environment Variable Substrings

 Original Source: [splunk source]
Name:Windows Command Obfuscation with Environment Variable Substrings
id:08a9ddcc-5b02-4055-abc5-945ba399f596
version:2
date:None
author:Raven Tait, Splunk
status:production
type:Anomaly
Description:Detects command obfuscation by using a technique to build a target command using character indexes from environment variables. This hides the true intent of the command by building it on the fly. In Windows command prompt, you can use the :~ format to extract substrings from environment variable values. This behavior has been observed in various malware families, including Cobalt Strike and Meterpreter.
Data_source:
  • -Sysmon EventID 1
  • -Windows Event Log Security 4688
  • -CrowdStrike ProcessRollup2
search:| tstats `security_content_summariesonly`
count min(_time) as firstTime
max(_time) as lastTime

from datamodel=Endpoint.Processes where

Processes.process="*%%*:~*,*"

by Processes.process Processes.vendor_product Processes.user_id Processes.process_hash
Processes.parent_process_name Processes.parent_process_exec Processes.action
Processes.dest Processes.process_current_directory Processes.process_path
Processes.process_integrity_level Processes.original_file_name
Processes.parent_process Processes.parent_process_path
Processes.parent_process_guid Processes.parent_process_id
Processes.process_guid Processes.process_id
Processes.user Processes.process_name

| `drop_dm_object_name(Processes)`
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `windows_command_obfuscation_with_environment_variable_substrings_filter`


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:Some legitimate scripts and system maintenance tools may use substring extraction from environment variables for dynamic command construction. Review and whitelist authorized scripts to reduce false positives.
References:
drilldown_searches:
 earliest_offset:'$info_min_time$'
 latest_offset:'$info_max_time$'
 name:'View the detection results for - "$user$" and "$dest$"'
 search:'%original_detection_search% | search user = "$user$" dest = "$dest$"'
 name:'View risk events for the last 7 days for - "$user$" and "$dest$"'
 search:'| from datamodel Risk.All_Risk | search normalized_risk_object IN ("$user$", "$dest$") | stats count min(_time) as firstTime max(_time) as lastTime values(search_name) as "Search Name" values(risk_message) as "Risk Message" values(analyticstories) as "Analytic Stories" values(annotations._all) as "Annotations" values(annotations.mitre_attack.mitre_tactic) as "ATT&CK Tactics" by normalized_risk_object | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`'
 earliest_offset:'7d'
 latest_offset:'0'
analytic_story:['Malicious PowerShell']

asset_type:Endpoint

mitre_attack_id:['T1027.010']

product:['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud']

category:endpoint

security_domain:endpoint

tags:

tests:
 name:'True Positive Test'
 attack_data:
  data: https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/attack_techniques/T1027.010/snapattack/snapattack.log
  source: XmlWinEventLog:Security
  sourcetype: XmlWinEventLog
 test_type:'unit'
manual_test:None

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