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Description

This analytic identifies commonly used command-line arguments used by rclone.exe to initiate a file transfer. Some arguments were negated as they are specific to the configuration used by adversaries. In particular, an adversary may list the files or directories of the remote file share using ls or lsd, which is not indicative of malicious behavior. During triage, at this stage of a ransomware event, exfiltration is about to occur or has already. Isolate the endpoint and continue investigating by review file modifications and parallel processes.

  • Type: TTP

  • Product: Splunk Behavioral Analytics

  • Last Updated: 2021-12-03
  • Author: Michael Haag, Splunk
  • ID: e8b74268-5454-11ec-a799-acde48001122

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1020 Automated Exfiltration Exfiltration
Kill Chain Phase
  • Actions On Objectives
NIST
  • DE.CM
CIS20
  • CIS 10
CVE 


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| from read_ba_enriched_events() 
| eval timestamp = ucast(map_get(input_event,"time"),"long", null) 
| eval metadata = ucast(map_get(input_event, "metadata"),"map<string, any>", null) 
| eval metadata_uid = ucast(map_get(metadata, "uid"),"string", null) 
| eval process=ucast(map_get(input_event,"process"), "map<string, any>", null) 
| eval process_pid=ucast(map_get(process,"pid"), "string", null) 
| eval process_file=ucast(map_get(process,"file"), "map<string, any>", null) 
| eval process_file_path=ucast(map_get(process_file,"path"), "string", null) 
| eval process_file_name=ucast(map_get(process_file,"name"), "string", null) 
| eval process_cmd_line=ucast(map_get(process,"cmd_line"), "string", null) 
| eval actor=ucast(map_get(input_event,"actor"), "map<string, any>", null) 
| eval actor_user=ucast(map_get(actor,"user"), "map<string, any>", null) 
| eval actor_user_name=ucast(map_get(actor_user,"name"), "string", null) 
| eval actor_process=ucast(map_get(actor,"process"), "map<string, any>", null) 
| eval actor_process_pid=ucast(map_get(actor_process,"pid"), "string", null) 
| eval actor_process_file=ucast(map_get(actor_process,"file"), "map<string, any>", null) 
| eval actor_process_file_path=ucast(map_get(actor_process_file,"path"), "string", null) 
| eval actor_process_file_name=ucast(map_get(actor_process_file,"name"), "string", null) 
| eval device=ucast(map_get(input_event,"device"), "map<string, any>", null) 
| eval device_hostname=ucast(map_get(device,"hostname"), "string", null) 
| where (like(process_cmd_line, "%--multi-thread-streams%") OR like(process_cmd_line, "%--transfers%") OR like(process_cmd_line, "%--auto-confirm%") OR like(process_cmd_line, "%--ignore-existing%") OR like(process_cmd_line, "%--no-check-certificate%") OR like(process_cmd_line, "%--progress%") OR like(process_cmd_line, "%--config%") OR like(process_cmd_line, "%ftp%") OR like(process_cmd_line, "%pcloud%") OR like(process_cmd_line, "%mega%") OR like(process_cmd_line, "%copy%")) AND process_file_name="rclone.exe" --finding_report--

Macros

The SPL above uses the following Macros:

:information_source: detect_rclone_command-line_usage_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.

  • process.pid
  • process.file.path
  • process.file.name
  • process.cmd_line
  • actor.user.name
  • actor.process.pid
  • actor.process.file.path
  • actor.process.file.name
  • device.hostname

How To Implement

To successfully implement this search you need to be ingesting information on process that include the name of the process responsible for the changes from your endpoints into the Endpoint_Processess datamodel.

Known False Positives

False positives should be limited as this is restricted to the Rclone process name. Filter or tune the analytic as needed.

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
35.0 50 70 An instance of $parent_process_name$ spawning $process_name$ was identified on endpoint $dest_device_id$ by user $dest_user_id$ attempting to connect to a remote cloud service to move files or folders.

: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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