GitHub Repo

Detection: Okta Account Locked Out

REMOVED DETECTION

This detection has been removed from the Splunk Threat Research content library and is no longer maintained or supported.

Reason: Detections updated to use the new search logic and field names due to the TA update

Removed in version: 5.2.0

Replacement: Okta Multiple Accounts Locked Out

If you have any questions or concerns, please reach out to us at research@splunk.com.

Updated Date: 2026-05-13 ID: d650c0ae-bdc5-400e-9f0f-f7aa0a010ef1 Author: Michael Haag, Splunk Type: Anomaly Product: Splunk Enterprise Security

Description

DEPRECATION NOTE - This search has been deprecated and replaced with Okta Multiple Accounts Locked Out. The following analytic utilizes the user.acount.lock event to identify associates who are locked out of Okta. An adversary attempting to brute force or password spray account names may lock accounts out depending on the threshold.

1`okta` eventType=user.account.lock 
2| stats count min(_time) as firstTime max(_time) as lastTime values(displayMessage) values(src_user) as user by src_ip eventType status 
3| where count >=3 
4| `security_content_ctime(firstTime)` 
5| `security_content_ctime(lastTime)`
6| `okta_account_locked_out_filter`

Data Source

No data sources specified for this detection.

Macros Used

Name Value
okta eventtype=okta_log OR sourcetype = "OktaIM2:log"
okta_account_locked_out_filter ``
okta_account_locked_out_filter is an empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Annotations

- MITRE ATT&CK
+ Kill Chain Phases
+ NIST
+ CIS
- Threat Actors
ID Technique Tactic
T1110 Brute Force Credential Access

Default Configuration

This detection is configured by default in Splunk Enterprise Security to run with the following settings:

Setting Value
Disabled true
Cron Schedule N/A
Earliest Time N/A
Latest Time N/A
Schedule Window N/A
Creates Finding (Notable) No
Creates Intermediate Finding (Risk Event) No
Anomaly detections generate Intermediate Findings (Risk Events). They do not generate a Finding (Notable) directly.

Implementation

This analytic is specific to Okta and requires Okta logs to be ingested.

Known False Positives

False positives may be present. Tune Okta and tune the analytic to ensure proper fidelity. Modify risk score as needed. Drop to anomaly until tuning is complete.

Associated Analytic Story

References

Detection Testing

Test Type Status Dataset Source Sourcetype
Validation Not Applicable N/A N/A N/A
Unit Not Applicable N/A N/A N/A
Integration Not Applicable N/A N/A N/A

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: GitHub |

Version: 3