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Description

The following analytic detects file writes with extensions that are consistent with a SamSam ransomware attack to proactively detect and respond to potential SamSam ransomware attacks, minimizing the impact and reducing the likelihood of successful ransomware infections. This detection is made by a Splunk query to search for specific file extensions that are commonly associated with SamSam ransomware, such as .stubbin, .berkshire, .satoshi, .sophos, and .keyxml. This identifies file extensions in the file names of the written files. If any file write events with these extensions are found, it suggests a potential SamSam ransomware attack. This detection is important because SamSam ransomware is a highly destructive and financially motivated attack and suggests that the organization is at risk of having its files encrypted and held for ransom, which can lead to significant financial losses, operational disruptions, and reputational damage. False positives might occur since legitimate files with these extensions can exist in the environment. Therefore, next steps include conducting a careful analysis and triage to confirm the presence of a SamSam ransomware attack. Next steps include taking immediate action to contain the attack, mitigate the impact, and prevent further spread of the ransomware. This might involve isolating affected systems, restoring encrypted files from backups, and conducting a thorough investigation to identify the attack source and prevent future incidents.

  • Type: TTP
  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
  • Datamodel: Endpoint
  • Last Updated: 2018-12-14
  • Author: Rico Valdez, Splunk
  • ID: 02c6cfc2-ae66-4735-bfc7-6291da834cbf

Annotations

ATT&CK
Kill Chain Phase
NIST
  • DE.CM
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)`
| rex field=file_name "(?<file_extension>\.[^\.]+)$" 
| search file_extension=.stubbin OR file_extension=.berkshire OR file_extension=.satoshi OR file_extension=.sophos OR file_extension=.keyxml 
| `file_with_samsam_extension_filter`

Macros

The SPL above uses the following Macros:

:information_source: file_with_samsam_extension_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 file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data.

Known False Positives

Because these extensions are not typically used in normal operations, you should investigate all results.

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
90.0 100 90 File writes $file_name$ with extensions consistent with a SamSam ransomware attack seen on $dest$

: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: 1