⚠️ WARNING THIS IS A EXPERIMENTAL DETECTION
We have not been able to test, simulate or build datasets for it, use at your own risk!
This search detects logins from the same user from different cities in a 24 hour period.
- Type: Anomaly
- Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Last Updated: 2020-07-21
- Author: Rico Valdez, Splunk
- ID: 7594fa07-9f34-4d01-81cc-d6af6a5db9e8
|T1078.001||Default Accounts||Defense Evasion, Persistence, Privilege Escalation, Initial Access|
`okta` displayMessage="User login to Okta" client.geographicalContext.city!=null | stats min(_time) as firstTime max(_time) as lastTime dc(client.geographicalContext.city) as locations values(client.geographicalContext.city) as cities values(client.geographicalContext.state) as states by user | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `okta_user_logins_from_multiple_cities_filter` | search locations > 1
Associated Analytic Story
How To Implement
This search is specific to Okta and requires Okta logs are being ingested in your Splunk deployment.
Kill Chain Phase
Known False Positives
Users in your enviornment may legitmately be travelling and loggin in from different locations. This search is useful for those users that should not be travelling for some reason, such as the COVID-19 pandemic. The search also relies on the geographical information being populated in the Okta logs. It is also possible that a connection from another region may be attributed to a login from a remote VPN endpoint.
source | version: 2