Unusual Hour for a User to Logon
A machine learning job detected a user logging in at a time of day that is unusual for the user. This can be due to credentialed access via a compromised account when the user and the threat actor are in different…
Description
A machine learning job detected a user logging in at a time of day that is unusual for the user. This can be due to credentialed access via a compromised account when the user and the threat actor are in different time zones. In addition, unauthorized user activity often takes place during non-business hours.
Detection logic
Its licence does not clear it for publishing here
Sunturai publishes a detection's own text where the licence it arrived under has been reviewed and permits it, and Elastic License 2.0 has not. The query as its source wrote it, its canonical form and the hash that pins this revision are in the workspace record.
Detection requirements
- Platform
- ContainersESXiIaaSIdentity ProviderLinuxmacOSNetwork DevicesOffice SuiteSaaSWindows
The rule states no platform. This is derived from the ATT&CK technique it maps to.
Known benign triggers
- Users working late, or logging in from unusual time zones while traveling, may trigger this rule.
MITRE ATT&CK mappings
0 exclusive techniques.This is coverage no other published rule has; it is not this rule's total technique count.
References
| Reference | Cited by |
|---|---|
| www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html | 103 |
From the source
- At source
- Open at source
- Upstream identifier
- 745b0119-0560-43ba-860a-7235dd8cee8d
- Tagged by the source as
- Data Source: Elastic DefendData Source: Windows Security Event LogsDomain: EndpointResources: Investigation GuideRule Type: Machine LearningRule Type: MLTactic: Initial AccessUse Case: Identity and Access AuditUse Case: Threat Detection
Licence
- Published under
- Elastic License 2.0Read the licence
- Attribution
- Required
Authorship
- Written by
- Published
- Sep 20, 2026
- Version
- 2