THIS IS A EXPERIMENTAL DETECTION
This detection has been marked experimental by the Splunk Threat Research team. This means we have not been able to test, simulate, or build datasets for this detection. Use at your own risk. This analytic is NOT supported.
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
Kill Chain Phase
- CIS 10
1 2 3 4 5 6 `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
The SPL above uses the following Macros:
okta_user_logins_from_multiple_cities_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
List of fields required to use this analytic.
How To Implement
This search is specific to Okta and requires Okta logs are being ingested in your Splunk deployment.
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.
Associated Analytic Story
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.
source | version: 2