ID | Technique | Tactic |
---|---|---|
T1037 | Boot or Logon Initialization Scripts | Persistence |
T1037.001 | Logon Script (Windows) | Privilege Escalation |
Detection: Logon Script Event Trigger Execution
Description
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.
Search
1
2| 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
3| `security_content_ctime(lastTime)`
4| `security_content_ctime(firstTime)`
5| `drop_dm_object_name(Registry)`
6| `logon_script_event_trigger_execution_filter`
Data Source
Name | Platform | Sourcetype | Source |
---|---|---|---|
Sysmon EventID 13 | Windows | 'xmlwineventlog' |
'XmlWinEventLog:Microsoft-Windows-Sysmon/Operational' |
Macros Used
Name | Value |
---|---|
security_content_ctime | convert timeformat="%Y-%m-%dT%H:%M:%S" ctime($field$) |
logon_script_event_trigger_execution_filter | search * |
logon_script_event_trigger_execution_filter
is an empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
Annotations
Default Configuration
This detection is configured by default in Splunk Enterprise Security to run with the following settings:
Setting | Value |
---|---|
Disabled | true |
Cron Schedule | 0 * * * * |
Earliest Time | -70m@m |
Latest Time | -10m@m |
Schedule Window | auto |
Creates Notable | Yes |
Rule Title | %name% |
Rule Description | %description% |
Notable Event Fields | user, dest |
Creates Risk Event | True |
Implementation
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
unknown
Associated Analytic Story
Risk Based Analytics (RBA)
Risk Message | Risk Score | Impact | Confidence |
---|---|---|---|
Registry path $registry_path$ was modified, added, or deleted on $dest$. | 80 | 80 | 100 |
References
Detection Testing
Test Type | Status | Dataset | Source | Sourcetype |
---|---|---|---|---|
Validation | ✅ Passing | N/A | N/A | N/A |
Unit | ✅ Passing | Dataset | XmlWinEventLog:Microsoft-Windows-Sysmon/Operational |
XmlWinEventLog |
Integration | ✅ Passing | Dataset | XmlWinEventLog:Microsoft-Windows-Sysmon/Operational |
XmlWinEventLog |
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: GitHub | Version: 3