Detection: Powershell Execute COM Object

Description

The following analytic detects the execution of a COM CLSID through PowerShell. It leverages EventCode 4104 and searches for specific script block text indicating the creation of a COM object. This activity is significant as it is commonly used by adversaries and malware, such as the Conti ransomware, to execute commands, potentially for privilege escalation or bypassing User Account Control (UAC). If confirmed malicious, this technique could allow attackers to gain elevated privileges or persist within the environment, posing a significant security risk.

1`powershell` EventCode=4104 ScriptBlockText = "*CreateInstance([type]::GetTypeFromCLSID*" 
2| stats count min(_time) as firstTime max(_time) as lastTime by EventCode ScriptBlockText Computer UserID 
3| rename Computer as dest 
4| rename UserID as user 
5| `security_content_ctime(firstTime)` 
6| `security_content_ctime(lastTime)` 
7| `powershell_execute_com_object_filter`

Data Source

Name Platform Sourcetype Source Supported App
Powershell Script Block Logging 4104 Windows icon Windows 'xmlwineventlog' 'XmlWinEventLog:Microsoft-Windows-PowerShell/Operational' N/A

Macros Used

Name Value
powershell (source=WinEventLog:Microsoft-Windows-PowerShell/Operational OR source="XmlWinEventLog:Microsoft-Windows-PowerShell/Operational")
powershell_execute_com_object_filter search *
powershell_execute_com_object_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
T1546.015 Component Object Model Hijacking Persistence
T1546 Event Triggered Execution Privilege Escalation
T1059.001 PowerShell Persistence
KillChainPhase.EXPLOITAITON
KillChainPhase.INSTALLATION
NistCategory.DE_CM
Cis18Value.CIS_10
APT28
APT19
APT28
APT29
APT3
APT32
APT33
APT38
APT39
APT41
APT5
Aquatic Panda
BRONZE BUTLER
Blue Mockingbird
Chimera
Cinnamon Tempest
Cobalt Group
Confucius
CopyKittens
DarkHydrus
DarkVishnya
Deep Panda
Dragonfly
Earth Lusca
Ember Bear
FIN10
FIN13
FIN6
FIN7
FIN8
Fox Kitten
GALLIUM
GOLD SOUTHFIELD
Gallmaker
Gamaredon Group
Gorgon Group
HAFNIUM
HEXANE
Inception
Indrik Spider
Kimsuky
Lazarus Group
LazyScripter
Leviathan
Magic Hound
Molerats
MoustachedBouncer
MuddyWater
Mustang Panda
Nomadic Octopus
OilRig
Patchwork
Poseidon Group
Sandworm Team
Sidewinder
Silence
Stealth Falcon
TA2541
TA459
TA505
TeamTNT
Threat Group-3390
Thrip
ToddyCat
Tonto Team
Turla
Volt Typhoon
WIRTE
Wizard Spider
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 Notable Yes
Rule Title %name%
Rule Description %description%
Notable Event Fields user, dest
Creates Risk Event True
This configuration file applies to all detections of type TTP. These detections will use Risk Based Alerting and generate Notable Events.

Implementation

To successfully implement this search, you need to be ingesting logs with the process name, parent process, and command-line executions from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA.

Known False Positives

network operrator may use this command.

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
A suspicious powershell script contains COM CLSID command on host $dest$ 5 10 50
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-PowerShell/Operational xmlwineventlog
Integration ✅ Passing Dataset XmlWinEventLog:Microsoft-Windows-PowerShell/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: 3