The search looks for files created with names matching those typically used in ransomware notes that tell the victim how to get their data back.
- Type: Hunting
- Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Datamodel: Endpoint
- Last Updated: 2020-11-09
- Author: David Dorsey, Splunk
- ID: ada0f478-84a8-4641-a3f1-d82362d6bd71
Kill Chain Phase
- Actions On Objectives
- CIS 10
1 2 3 4 5 6 7 | 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`
The SPL above uses the following Macros:
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.
List of fields required to use this analytic.
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
|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.|
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.
source | version: 4