:warning: 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.

Try in Splunk Security Cloud

Description

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

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1078 Valid Accounts Defense Evasion, Persistence, Privilege Escalation, Initial Access
T1078.001 Default Accounts Defense Evasion, Persistence, Privilege Escalation, Initial Access
Kill Chain Phase
  • Exploitation
NIST
  • DE.CM
CIS20
  • CIS 16
CVE 


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`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

Macros

The SPL above uses the following Macros:

:information_source: 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.

Required fields

List of fields required to use this analytic.

  • _time
  • displayMessage
  • client.geographicalContext.city
  • client.geographicalContext.state
  • user

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

RBA

Risk Score Impact Confidence Message
25.0 50 50 tbd

: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.

Reference

Test Dataset

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 | version: 2