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Description

The following analytic identifies the use of Windows Curl.exe uploading a file to a remote destination.
-T or --upload-file is used when a file is to be uploaded to a remotge destination.
-d or --data POST is the HTTP method that was invented to send data to a receiving web application, and it is, for example, how most common HTML forms on the web work.
HTTP multipart formposts are done with -F, but this appears to not be compatible with the Windows version of Curl. Will update if identified adversary tradecraft.
Adversaries may use one of the three methods based on the remote destination and what they are attempting to upload (zip vs txt). During triage, review parallel processes for further behavior. In addition, identify if the upload was successful in network logs. If a file was uploaded, isolate the endpoint and review.

  • Type: TTP
  • Product: Splunk Behavioral Analytics
  • Datamodel: Endpoint_Processes
  • Last Updated: 2021-12-03
  • Author: Michael Haag, Splunk
  • ID: cc8d046a-543b-11ec-b864-acde48001122

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1105 Ingress Tool Transfer Command And Control
Kill Chain Phase
  • Exploitation
NIST
CIS20
CVE
1
2
3
4
5
6
7
8
9
10
| from read_ssa_enriched_events() 
| where "Endpoint_Processes" IN(_datamodels) 
| eval timestamp=parse_long(ucast(map_get(input_event, "_time"), "string", null)), cmd_line=ucast(map_get(input_event, "process"), "string", null), process_name=ucast(map_get(input_event, "process_name"), "string", null), process_path=ucast(map_get(input_event, "process_path"), "string", null), parent_process_name=ucast(map_get(input_event, "parent_process_name"), "string", null), event_id=ucast(map_get(input_event, "event_id"), "string", null)

| where cmd_line IS NOT NULL AND process_name IS NOT NULL AND process_name="curl.exe" AND (like (cmd_line, "%-T %") OR like (cmd_line, "%--upload-file %")OR like (cmd_line, "%-d %") OR like (cmd_line, "%--data %") OR like (cmd_line, "%-F %"))

| eval start_time=timestamp, end_time=timestamp, entities=mvappend(ucast(map_get(input_event, "dest_user_id"), "string", null), ucast(map_get(input_event, "dest_device_id"), "string", null)) 
| eval body=create_map(["event_id", event_id, "cmd_line", cmd_line, "process_name", process_name, "parent_process_name", parent_process_name, "process_path", process_path]) 
| into write_ssa_detected_events();

Macros

The SPL above uses the following Macros:

:information_source: windows_curl_upload_to_remote_destination_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
  • dest_device_id
  • process_name
  • parent_process_name
  • process_path
  • dest_user_id
  • process
  • cmd_line

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 may be limited to source control applications and may be required to be filtered out.

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
80.0 80 100 An instance of $parent_process_name$ spawning $process_name$ was identified on endpoint $dest_device_id$ by user $dest_user_id$ uploading a file to a remote destination.

: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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