Detection: Hunting 3CXDesktopApp Software

Updated Date: 2024-08-15 ID: 553d0429-1a1c-44bf-b3f5-a8513deb9ee5 Author: Michael Haag, Splunk Type: Hunting Product: Splunk Enterprise Security

Description

The following analytic detects the presence of any version of the 3CXDesktopApp, also known as the 3CX Desktop App, on Mac or Windows systems. It leverages the Endpoint data model's Processes node to identify instances of the application running, although it does not provide file version information. This activity is significant because 3CX has identified vulnerabilities in versions 18.12.407 and 18.12.416, which could be exploited by attackers. If confirmed malicious, this could lead to unauthorized access, data exfiltration, or further compromise of the affected systems.

1
2| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=3CXDesktopApp.exe OR Processes.process_name="3CX Desktop App" by Processes.dest Processes.user Processes.parent_process_name Processes.process_name Processes.original_file_name Processes.process Processes.process_id Processes.parent_process_id 
3| `drop_dm_object_name(Processes)` 
4| `security_content_ctime(firstTime)` 
5| `security_content_ctime(lastTime)` 
6| `hunting_3cxdesktopapp_software_filter`

Data Source

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

Macros Used

Name Value
security_content_ctime convert timeformat="%Y-%m-%dT%H:%M:%S" ctime($field$)
hunting_3cxdesktopapp_software_filter search *
hunting_3cxdesktopapp_software_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
T1195.002 Compromise Software Supply Chain Initial Access
KillChainPhase.DELIVERY
NistCategory.DE_AE
Cis18Value.CIS_10
APT41
Cobalt Group
Dragonfly
FIN7
GOLD SOUTHFIELD
Sandworm Team
Threat Group-3390

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 False
This configuration file applies to all detections of type hunting.

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

There may be false positives generated due to the reliance on version numbers for identification purposes. Despite this limitation, the primary goal of this approach is to aid in the detection of the software within the environment.

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
An instance $process_name$ was identified on endpoint $dest$. 40 80 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-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: 3