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This analytic is to detect deletion of registry with suspicious process file path. This technique was seen in Double Zero wiper malware where it will delete all the subkey in HKLM, HKCU and HKU registry hive as part of its destructive payload to the targeted hosts. This anomaly detections can catch possible malware or advesaries deleting registry as part of defense evasion or even payload impact but can also catch for third party application updates or installation. In this scenario false positive filter is needed.

  • Type: Anomaly
  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
  • Datamodel: Endpoint
  • Last Updated: 2023-04-14
  • Author: Steven Dick, Teoderick Contreras, Splunk
  • ID: 15e70689-f55b-489e-8a80-6d0cd6d8aad2




ID Technique Tactic
T1112 Modify Registry Defense Evasion
Kill Chain Phase
  • Exploitation
  • DE.AE
  • CIS 10
| tstats `security_content_summariesonly` count from datamodel=Endpoint.Registry WHERE Registry.action=deleted BY _time span=1h Registry.dest Registry.registry_path Registry.registry_value_name Registry.registry_key_name Registry.process_guid Registry.registry_value_data Registry.action 
| `drop_dm_object_name(Registry)` 
| join process_guid [
| tstats `security_content_summariesonly` count FROM datamodel=Endpoint.Processes WHERE NOT (Processes.process_path IN ("*\\windows\\*", "*\\program files*")) by _time span=1h Processes.process_id Processes.process_name Processes.process Processes.user Processes.parent_process_name Processes.parent_process Processes.process_path Processes.process_guid 
| `drop_dm_object_name(Processes)`] 
| fields _time parent_process_name parent_process process_name process_path process process_guid registry_path registry_value_name registry_value_data registry_key_name action dest user 
| `windows_deleted_registry_by_a_non_critical_process_file_path_filter`


The SPL above uses the following Macros:

:information_source: windows_deleted_registry_by_a_non_critical_process_file_path_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.

  • Processes.user
  • Processes.dest
  • Processes.process_id
  • Processes.process_name
  • Processes.process
  • Processes.process_path
  • Processes.parent_process_name
  • Processes.parent_process
  • Processes.process_guid
  • Registry.dest
  • Registry.registry_value_name
  • Registry.registry_key_name
  • Registry.registry_path
  • Registry.registry_value_data
  • Registry.process_guid

How To Implement

The detection is based on data that originates from Endpoint Detection and Response (EDR) agents. These agents are designed to provide security-related telemetry from the endpoints where the agent is installed. To implement this search, you must ingest logs that contain the process GUID, process name, and parent process. Additionally, you must ingest complete command-line executions. These logs must be processed using the appropriate Splunk Technology Add-ons that are specific to the EDR product. The logs must also be mapped to the Processes node of the Endpoint data model. Use the Splunk Common Information Model (CIM) to normalize the field names and speed up the data modeling process.

Known False Positives

This detection can catch for third party application updates or installation. In this scenario false positive filter is needed.

Associated Analytic Story


Risk Score Impact Confidence Message
36.0 60 60 registry was deleted by a suspicious $process_name$ with proces path $process_path in $dest$

: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.


Test Dataset

Replay any dataset to Splunk Enterprise by using our tool or the UI. Alternatively you can replay a dataset into a Splunk Attack Range

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