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Description

The following analytic detects the creation of files with names commonly associated with ransomware notes. It leverages file-system activity data from the Endpoint Filesystem data model, typically populated by endpoint detection and response (EDR) tools or Sysmon logs. This activity is significant because ransomware notes indicate a potential ransomware attack, which can lead to data encryption and extortion. If confirmed malicious, this activity could result in significant data loss, operational disruption, and financial impact due to ransom demands.

  • Type: Hunting
  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
  • Datamodel: Endpoint
  • Last Updated: 2024-05-22
  • Author: David Dorsey, Splunk
  • ID: ada0f478-84a8-4641-a3f1-d82362d6bd71

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1485 Data Destruction Impact
Kill Chain Phase
  • Actions On Objectives
NIST
  • DE.AE
CIS20
  • CIS 10
CVE 


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| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime values(Filesystem.user) as user values(Filesystem.dest) as dest values(Filesystem.file_path) as file_path from datamodel=Endpoint.Filesystem by Filesystem.file_name 
| `drop_dm_object_name(Filesystem)` 
| `security_content_ctime(lastTime)` 
| `security_content_ctime(firstTime)` 
| `ransomware_notes` 
| `common_ransomware_notes_filter`

Macros

The SPL above uses the following Macros:

:information_source: common_ransomware_notes_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
  • Filesystem.user
  • Filesystem.dest
  • Filesystem.file_path
  • Filesystem.file_name

How To Implement

You must be ingesting data that records file-system activity from your hosts to populate the Endpoint Filesystem data-model node. This is typically populated via endpoint detection-and-response product, such as Carbon Black, or via other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file-system reads and writes.

Known False Positives

It's possible that a legitimate file could be created with the same name used by ransomware note files.

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
90.0 90 100 A file - $file_name$ was written to disk on endpoint $dest$ by user $user$, this is indicative of a known ransomware note file and should be reviewed immediately.

: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

source | version: 5