Detection: Okta User Logins from Multiple Cities

Updated Date: 2024-05-09 ID: a3d1df37-c2a9-41d0-aa8f-59f82d6192a8 Author: Bhavin Patel, Splunk Type: Anomaly Product: Splunk Enterprise Security

Description

The following analytic identifies instances where the same Okta user logs in from different cities within a 24-hour period. This detection leverages Okta Identity Management logs, analyzing login events and their geographic locations. Such behavior is significant as it may indicate a compromised account, with an attacker attempting unauthorized access from multiple locations. If confirmed malicious, this activity could lead to account takeovers and data breaches, allowing attackers to access sensitive information and potentially escalate their privileges within the environment.

1
2| tstats  `security_content_summariesonly` values(Authentication.app) as app values(Authentication.action) as action values(Authentication.user) as user values(Authentication.reason) as reason values(Authentication.dest) as dest values(Authentication.signature) as signature  values(Authentication.method) as method  from datamodel=Authentication where  Authentication.signature=user.session.start by _time Authentication.src 
3| `drop_dm_object_name("Authentication")` 
4| `security_content_ctime(firstTime)` 
5| `security_content_ctime(lastTime)` 
6| iplocation src 
7| stats count min(_time) as firstTime max(_time) as lastTime dc(src) as distinct_src dc(City) as distinct_city values(src) as src values(City) as City values(Country) as Country values(action) as action by user 
8| where distinct_city > 1 
9| `okta_user_logins_from_multiple_cities_filter`

Data Source

Name Platform Sourcetype Source Supported App
Okta N/A 'OktaIM2:log' 'Okta' N/A

Macros Used

Name Value
security_content_ctime convert timeformat="%Y-%m-%dT%H:%M:%S" ctime($field$)
okta_user_logins_from_multiple_cities_filter search *
okta_user_logins_from_multiple_cities_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
T1586.003 Cloud Accounts Resource Development
KillChainPhase.WEAPONIZATION
NistCategory.DE_AE
Cis18Value.CIS_10
APT29

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 True
This configuration file applies to all detections of type anomaly. These detections will use Risk Based Alerting.

Implementation

This detection utilizes logs from Okta Identity Management (IM) environments. It requires the ingestion of OktaIm2 logs through the Splunk Add-on for Okta Identity Cloud (https://splunkbase.splunk.com/app/6553).

Known False Positives

It is uncommon for a user to log in from multiple cities simultaneously, which may indicate a false positive.

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
A user [$user$] has logged in from multiple cities [$City$] from IP Address - [$src$]. Investigate further to determine if this was authorized. 81 90 90
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.

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: 2