Detection: Potentially malicious code on commandline

Description

The following analytic detects potentially malicious command lines using a pretrained machine learning text classifier. It identifies unusual keyword combinations in command lines, such as "streamreader," "webclient," "mutex," "function," and "computehash," which are often associated with adversarial PowerShell code execution for C2 communication. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on command lines longer than 200 characters. This activity is significant as it can indicate an attempt to execute malicious scripts, potentially leading to unauthorized code execution, data exfiltration, or further system compromise.

 1
 2| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel="Endpoint.Processes" by Processes.parent_process_name Processes.process_name Processes.process Processes.user Processes.dest  
 3| `drop_dm_object_name(Processes)`  
 4| where len(process) > 200 
 5| `potentially_malicious_code_on_cmdline_tokenize_score` 
 6| apply unusual_commandline_detection 
 7| eval score='predicted(unusual_cmdline_logits)', process=orig_process 
 8| fields - unusual_cmdline* predicted(unusual_cmdline_logits) orig_process 
 9| where score > 0.5 
10| `security_content_ctime(firstTime)` 
11| `security_content_ctime(lastTime)` 
12| `potentially_malicious_code_on_commandline_filter`

Data Source

Name Platform Sourcetype Source Supported App
CrowdStrike ProcessRollup2 N/A 'crowdstrike:events:sensor' 'crowdstrike' N/A

Macros Used

Name Value
potentially_malicious_code_on_cmdline_tokenize_score eval orig_process=process, process=replace(lower(process), "", "")
potentially_malicious_code_on_commandline_filter search *
potentially_malicious_code_on_commandline_filter is an empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Annotations

- MITRE ATT&CK
+ Kill Chain Phases
+ NIST
+ CIS
- Threat Actors
ID Technique Tactic
T1059.003 Windows Command Shell Execution
KillChainPhase.INSTALLATION
NistCategory.DE_AE
Cis18Value.CIS_10
APT1
APT18
APT28
APT3
APT32
APT37
APT38
APT41
APT5
Aquatic Panda
BRONZE BUTLER
Blue Mockingbird
Chimera
Cinnamon Tempest
Cobalt Group
Dark Caracal
Darkhotel
Dragonfly
Ember Bear
FIN10
FIN13
FIN6
FIN7
FIN8
Fox Kitten
GALLIUM
Gamaredon Group
Gorgon Group
HAFNIUM
Higaisa
Indrik Spider
Ke3chang
Kimsuky
Lazarus Group
LazyScripter
Machete
Magic Hound
Metador
MuddyWater
Mustang Panda
Nomadic Octopus
OilRig
Patchwork
Rancor
Silence
Sowbug
Suckfly
TA505
TA551
TeamTNT
Threat Group-1314
Threat Group-3390
ToddyCat
Tropic Trooper
Turla
Volt Typhoon
Wizard Spider
ZIRCONIUM
admin@338
menuPass

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
This configuration file applies to all detections of type anomaly. These detections will use Risk Based Alerting.

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

This model is an anomaly detector that identifies usage of APIs and scripting constructs that are correllated with malicious activity. These APIs and scripting constructs are part of the programming langauge and advanced scripts may generate false positives.

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
Unusual command-line execution with command line length greater than 200 found on $dest$ with commandline value - [$process$] 12 60 20
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

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: 2