Try in Splunk Security Cloud

Description

The hunting analytic outlined below is designed to detect any version of the 3CXDesktopApp, also known as the 3CX Desktop App, operating on either Mac or Windows systems. It is important to note that this particular analytic employs the Endpoint datamodel Processes node, which means that the file version information is not provided. Recently, 3CX has identified a vulnerability specifically in versions 18.12.407 and 18.12.416 of the desktop app.

  • Type: Hunting
  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
  • Datamodel: Endpoint
  • Last Updated: 2023-03-30
  • Author: Michael Haag, Splunk
  • ID: 553d0429-1a1c-44bf-b3f5-a8513deb9ee5

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1195.002 Compromise Software Supply Chain Initial Access
Kill Chain Phase
  • Delivery
NIST
  • DE.AE
CIS20
  • CIS 10
CVE
ID Summary CVSS
CVE-2023-29059 3CX DesktopApp through 18.12.416 has embedded malicious code, as exploited in the wild in March 2023. This affects versions 18.12.407 and 18.12.416 of the 3CX DesktopApp Electron Windows application shipped in Update 7, and versions 18.11.1213, 18.12.402, 18.12.407, and 18.12.416 of the 3CX DesktopApp Electron macOS application. None 


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| 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 
| `drop_dm_object_name(Processes)` 
| `security_content_ctime(firstTime)` 
| `security_content_ctime(lastTime)` 
| `hunting_3cxdesktopapp_software_filter`

Macros

The SPL above uses the following Macros:

:information_source: hunting_3cxdesktopapp_software_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Required fields

List of fields required to use this analytic.

  • _time
  • Processes.dest
  • Processes.user
  • Processes.parent_process_name
  • Processes.parent_process
  • Processes.original_file_name
  • Processes.process_name
  • Processes.process
  • Processes.process_id
  • Processes.parent_process_path
  • Processes.process_path
  • Processes.parent_process_id

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

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

RBA

Risk Score Impact Confidence Message
40.0 80 50 An instance $process_name$ was identified on endpoint $dest$.

:information_source: The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.

Reference

Test Dataset

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

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