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.
Query · spl
`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))
| 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
| stats latest(_time) as lasttime earliest(_time) as firsttime sum(successes) as successes sum(failures) as failures sum(pushes) as pushes
BY user
| eval seconds=lasttime-firsttime
| eval lasttime=strftime(lasttime, "%c")
| search (pushes>1)
| eval totalattempts=successes+failures
| eval finding="Normal authentication pattern"
| eval finding=if(failures==pushes AND pushes>1,"Authentication attempts not successful because multiple pushes denied",finding)
| eval finding=if(totalattempts==0,"Multiple pushes sent and ignored",finding)
| eval finding=if(successes>0 AND pushes>3,"Probably should investigate. Multiple pushes sent, eventual successful authentication!",finding)
| `okta_mfa_exhaustion_hunt_filter`
Implementation guide
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.
Analyst notes
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.