Detection: Okta MFA Exhaustion Hunt

Description

The following analytic detects patterns of successful and failed Okta MFA push attempts to identify potential MFA exhaustion attacks. It leverages Okta event logs, specifically focusing on push verification events, and uses statistical evaluations to determine suspicious activity. This activity is significant as it may indicate an attacker attempting to bypass MFA by overwhelming the user with push notifications. If confirmed malicious, this could lead to unauthorized access, compromising the security of the affected accounts and potentially the entire environment.

Search

 1`okta` eventType=system.push.send_factor_verify_push OR ((legacyEventType=core.user.factor.attempt_success) AND (debugContext.debugData.factor=OKTA_VERIFY_PUSH)) OR ((legacyEventType=core.user.factor.attempt_fail) AND (debugContext.debugData.factor=OKTA_VERIFY_PUSH)) 
 2| stats count(eval(legacyEventType="core.user.factor.attempt_success"))  as successes count(eval(legacyEventType="core.user.factor.attempt_fail")) as failures count(eval(eventType="system.push.send_factor_verify_push")) as pushes by user,_time 
 3| stats latest(_time) as lasttime earliest(_time) as firsttime sum(successes) as successes sum(failures) as failures sum(pushes) as pushes by user 
 4| eval seconds=lasttime-firsttime 
 5| eval lasttime=strftime(lasttime, "%c") 
 6| search (pushes>1) 
 7| eval totalattempts=successes+failures 
 8| eval finding="Normal authentication pattern" 
 9| eval finding=if(failures==pushes AND pushes>1,"Authentication attempts not successful because multiple pushes denied",finding) 
10| eval finding=if(totalattempts==0,"Multiple pushes sent and ignored",finding) 
11| eval finding=if(successes>0 AND pushes>3,"Probably should investigate. Multiple pushes sent, eventual successful authentication!",finding) 
12| `okta_mfa_exhaustion_hunt_filter`

Data Source

Macros Used

Annotations

Default Configuration

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

Implementation

The analytic leverages Okta OktaIm2 logs to be ingested using the Splunk Add-on for Okta Identity Cloud (https://splunkbase.splunk.com/app/6553).

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

• Okta Account Takeover

• Okta MFA Exhaustion

Risk Based Analytics (RBA)

References

• https://developer.okta.com/docs/reference/api/event-types/?q=user.acount.lock

• https://sec.okta.com/everythingisyes

• https://splunkbase.splunk.com/app/6553

Detection Testing

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: 4