Detection: Windows Remote Access Software Hunt

Description

The following analytic identifies the use of remote access software within the environment. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process execution logs. This detection is significant as unauthorized remote access tools can be used by adversaries to maintain persistent access to compromised systems. If confirmed malicious, this activity could allow attackers to remotely control systems, exfiltrate data, or further infiltrate the network. Review the identified software to ensure it is authorized and take action against any unauthorized utilities.

Search

1
2| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime values(Processes.process) as process values(Processes.parent_process) as parent_process from datamodel=Endpoint.Processes where Processes.dest!=unknown Processes.user!=unknown by Processes.dest Processes.user Processes.process_name Processes.process 
3| `security_content_ctime(firstTime)` 
4| `security_content_ctime(lastTime)` 
5| `drop_dm_object_name(Processes)` 
6| lookup remote_access_software remote_utility AS process_name OUTPUT isutility 
7| search isutility = True 
8| `windows_remote_access_software_hunt_filter`

Data Source

Macros Used

Annotations

Default Configuration

This detection is configured by default in Splunk Enterprise Security to run with the following settings:

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

False positives will be found. Filter as needed and create higher fidelity analytics based off banned remote access software.

Associated Analytic Story

• Command And Control

• Insider Threat

• Ransomware

Risk Based Analytics (RBA)

References

• https://thedfirreport.com/2022/08/08/bumblebee-roasts-its-way-to-domain-admin/

• https://github.com/redcanaryco/atomic-red-team/blob/master/atomics/T1219/T1219.md

• https://thedfirreport.com/2022/11/28/emotet-strikes-again-lnk-file-leads-to-domain-wide-ransomware/

Detection Testing

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