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.
The following anomaly will generate based on account lockout events utilizing Okta eventTypes of user.account.lock.limit or user.account.lock. Per the Okta docs site, this event is fired when a user account has reached the lockout limit. The account will not auto-unlock and a user or client cannot gain access to the account. This event indicates an account that will not be able to log in until remedial action is taken by the account admin. This event can be used to understand the specifics of an account lockout. Often this indicates a client application that is repeatedly attempting to authenticate with invalid credentials such as an old password.
- Type: Anomaly
Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Last Updated: 2022-09-19
- Author: Michael Haag, Rico Valdez, Splunk
- ID: 62b70968-a0a5-4724-8ac4-67871e6f544d
Kill Chain Phase
- CIS 10
1 2 3 4 5 6 `okta` eventType IN (user.account.lock.limit,user.account.lock) | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | stats count min(_time) as firstTime max(_time) as lastTime values(src_user) by displayMessage, country, state, city, src_ip | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `okta_account_lockout_events_filter`
The SPL above uses the following Macros:
okta_account_lockout_events_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 analytic is specific to Okta and requires Okta logs to be ingested.
Known False Positives
None. Account lockouts should be followed up on to determine if the actual user was the one who caused the lockout, or if it was an unauthorized actor.
Associated Analytic Story
|25.0||50||50||The following user $src_user$ has locked out their account within Okta.|
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