Try in Splunk Security Cloud


The following analytic detects the modification of the UserInitMprLogonScript registry entry, which is often used by attackers to establish persistence and gain privilege escalation upon system boot. It leverages data from the Endpoint.Registry data model, focusing on changes to the specified registry path. This activity is significant because it is a common technique used by APT groups and malware to ensure their payloads execute automatically when the system starts. If confirmed malicious, this could allow attackers to maintain persistent access and potentially escalate their privileges on the compromised host.

  • Type: TTP
  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
  • Datamodel: Endpoint
  • Last Updated: 2024-05-10
  • Author: Teoderick Contreras, Splunk
  • ID: 4c38c264-1f74-11ec-b5fa-acde48001122




ID Technique Tactic
T1037 Boot or Logon Initialization Scripts Persistence, Privilege Escalation
T1037.001 Logon Script (Windows) Persistence, Privilege Escalation
Kill Chain Phase
  • Installation
  • Exploitation
  • DE.CM
  • CIS 10
| tstats `security_content_summariesonly` count  min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Registry where Registry.registry_path IN ("*\\Environment\\UserInitMprLogonScript") by Registry.dest  Registry.user Registry.registry_path Registry.registry_key_name Registry.registry_value_name 
| `security_content_ctime(lastTime)` 
| `security_content_ctime(firstTime)` 
| `drop_dm_object_name(Registry)` 
| `logon_script_event_trigger_execution_filter`


The SPL above uses the following Macros:

:information_source: logon_script_event_trigger_execution_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
  • Registry.dest
  • Registry.user
  • Registry.registry_path
  • Registry.registry_key_name
  • Registry.registry_value_name

How To Implement

To successfully implement this search, you must be ingesting data that records registry activity from your hosts to populate the endpoint data model in the registry node. This is typically populated via endpoint detection-and-response product, such as Carbon Black or endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report reads and writes to the registry.

Known False Positives


Associated Analytic Story


Risk Score Impact Confidence Message
80.0 80 100 Registry path $registry_path$ was modified, added, or deleted 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.


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

source | version: 2