Detection: Azure Active Directory High Risk Sign-in

Description

The following analytic detects high-risk sign-in attempts against Azure Active Directory, identified by Azure Identity Protection. It leverages the RiskyUsers and UserRiskEvents log categories from Azure AD events ingested via EventHub. This activity is significant as it indicates potentially compromised accounts, flagged by heuristics and machine learning. If confirmed malicious, attackers could gain unauthorized access to sensitive resources, leading to data breaches or further exploitation within the environment.

1`azure_monitor_aad` category=UserRiskEvents properties.riskLevel=high 
2| rename properties.* as * 
3| stats count min(_time) as firstTime max(_time) as lastTime values(user) as user by src_ip, activity, riskLevel, riskEventType, additionalInfo 
4| `security_content_ctime(firstTime)` 
5| `security_content_ctime(lastTime)` 
6| `azure_active_directory_high_risk_sign_in_filter`

Data Source

Name Platform Sourcetype Source
Azure Active Directory Azure icon Azure 'azure:monitor:aad' 'Azure AD'

Macros Used

Name Value
azure_monitor_aad sourcetype=azure:monitor:aad
azure_active_directory_high_risk_sign_in_filter search *
azure_active_directory_high_risk_sign_in_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 Compromise Accounts Resource Development
T1586.003 Cloud Accounts Resource Development
T1110 Brute Force Credential Access
T1110.003 Password Spraying Credential Access
KillChainPhase.EXPLOITAITON
KillChainPhase.WEAPONIZATION
NistCategory.DE_CM
Cis18Value.CIS_10
APT29
APT28
APT38
APT39
APT41
Agrius
DarkVishnya
Dragonfly
Ember Bear
FIN5
Fox Kitten
HEXANE
OilRig
Turla
APT28
APT29
APT33
Agrius
Chimera
Ember Bear
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. Specifically, this analytic leverages the RiskyUsers and UserRiskEvents log category in the azure:monitor:aad sourcetype.

Known False Positives

Details for the risk calculation algorithm used by Identity Protection are unknown and may be prone to false positives.

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
A high risk event was identified by Identify Protection for user $user$ 54 60 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 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