Detection: Azure AD Successful Authentication From Different Ips

Updated Date: 2024-09-24 ID: be6d868d-33b6-4aaa-912e-724fb555b11a Author: Mauricio Velazco, Splunk Type: TTP Product: Splunk Enterprise Security

Description

The following analytic detects an Azure AD account successfully authenticating from multiple unique IP addresses within a 30-minute window. It leverages Azure AD SignInLogs to identify instances where the same user logs in from different IPs in a short time frame. This behavior is significant as it may indicate compromised credentials being used by an adversary, potentially following a phishing attack. If confirmed malicious, this activity could allow unauthorized access to corporate resources, leading to data breaches or further exploitation within the network.

1`azure_monitor_aad`  properties.authenticationDetails{}.succeeded=true category=SignInLogs 
2| rename properties.* as * 
3| bucket span=30m _time 
4| stats count min(_time) as firstTime max(_time) as lastTime dc(src_ip) AS unique_ips values(src_ip) as src_ip values(appDisplayName) as appDisplayName by user 
5| `security_content_ctime(firstTime)` 
6| `security_content_ctime(lastTime)` 
7| where unique_ips  > 1 
8| `azure_ad_successful_authentication_from_different_ips_filter`

Data Source

Name Platform Sourcetype Source Supported App
Azure Active Directory Azure icon Azure 'azure:monitor:aad' 'Azure AD' N/A

Macros Used

Name Value
azure_monitor_aad sourcetype=azure:monitor:aad
azure_ad_successful_authentication_from_different_ips_filter search *
azure_ad_successful_authentication_from_different_ips_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
T1110.001 Password Guessing Credential Access
T1110.003 Password Spraying Credential Access
KillChainPhase.EXPLOITAITON
NistCategory.DE_CM
Cis18Value.CIS_10
APT28
APT38
APT39
DarkVishnya
Dragonfly
FIN5
Fox Kitten
HEXANE
OilRig
Turla
APT28
APT29
APT28
APT29
APT33
Chimera
HEXANE
Lazarus Group
Leafminer
Silent Librarian

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 Notable Yes
Rule Title %name%
Rule Description %description%
Notable Event Fields user, dest
Creates Risk Event True
This configuration file applies to all detections of type TTP. These detections will use Risk Based Alerting and generate Notable Events.

Implementation

You must install the latest version of Splunk Add-on for Microsoft Cloud Services from Splunkbase (https://splunkbase.splunk.com/app/3110/#/details). You must be ingesting Azure Active Directory events into your Splunk environment through an EventHub. This analytic was written to be used with the azure:monitor:aad sourcetype leveraging the Signin log category.

Known False Positives

A user with successful authentication events from different Ips may also represent the legitimate use of more than one device. Filter as needed and/or customize the threshold to fit your environment.

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
User $user$ has had successful authentication events from more than one unique IP address in the span of 30 minutes. 56 70 80
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 Azure AD azure:monitor:aad
Integration ✅ Passing Dataset Azure AD azure:monitor:aad

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: 5