ID | Technique | Tactic |
---|---|---|
T1110 | Brute Force | Credential Access |
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
Name | Platform | Sourcetype | Source | Supported App |
---|---|---|---|---|
Okta | N/A | 'OktaIM2:log' |
'Okta' |
N/A |
Macros Used
Name | Value |
---|---|
okta | eventtype=okta_log OR sourcetype = "OktaIM2:log" |
okta_mfa_exhaustion_hunt_filter | search * |
okta_mfa_exhaustion_hunt_filter
is an empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
Annotations
Default Configuration
This detection is configured by default in Splunk Enterprise Security to run with the following settings:
Setting | Value |
---|---|
Disabled | true |
Cron Schedule | 0 * * * * |
Earliest Time | -70m@m |
Latest Time | -10m@m |
Schedule Window | auto |
Creates Risk Event | False |
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
Risk Based Analytics (RBA)
Risk Message | Risk Score | Impact | Confidence |
---|---|---|---|
$user$ account has rejected multiple Okta pushes. | 18 | 30 | 60 |
References
Detection Testing
Test Type | Status | Dataset | Source | Sourcetype |
---|---|---|---|---|
Validation | ✅ Passing | N/A | N/A | N/A |
Unit | ✅ Passing | Dataset | Okta |
OktaIM2:log |
Integration | ✅ Passing | Dataset | Okta |
OktaIM2:log |
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