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Description

The following analytic detects unusual authentication activity in Azure AD, specifically when a single user account has over 8 authentication attempts using 3+ unique application IDs and 5+ unique user agents within a short period. It leverages Azure AD audit logs, focusing on authentication events and using statistical thresholds. This behavior is significant as it may indicate an adversary probing for MFA requirements. If confirmed malicious, it suggests a compromised account, potentially leading to further exploitation, lateral movement, and data exfiltration. Early detection is crucial to prevent substantial harm.

  • Type: Anomaly
  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
  • Datamodel: Authentication
  • Last Updated: 2024-05-26
  • Author: Mauricio Velazco, Splunk
  • ID: 5d8bb1f0-f65a-4b4e-af2e-fcdb88276314

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1078 Valid Accounts Defense Evasion, Persistence, Privilege Escalation, Initial Access
Kill Chain Phase
  • Exploitation
  • Installation
  • Delivery
NIST
  • DE.AE
CIS20
  • CIS 10
CVE 


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 `azure_monitor_aad` category=SignInLogs operationName="Sign-in activity" (properties.authenticationRequirement="multiFactorAuthentication" AND properties.status.additionalDetails="MFA required in Azure AD") OR (properties.authenticationRequirement=singleFactorAuthentication AND "properties.authenticationDetails{}.succeeded"=true) 
| bucket span=5m _time 
| rename properties.* as * 
| stats count min(_time) as firstTime max(_time) as lastTime dc(appId) as unique_app_ids dc(userAgent) as unique_user_agents values(appDisplayName) values(deviceDetail.operatingSystem) by user, src_ip 
| where count > 5 and unique_app_ids > 2 and unique_user_agents > 5 
| `security_content_ctime(firstTime)` 
| `security_content_ctime(lastTime)` 
| `azure_ad_multiple_appids_and_useragents_authentication_spike_filter`

Macros

The SPL above uses the following Macros:

:information_source: azure_ad_multiple_appids_and_useragents_authentication_spike_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Required fields

List of fields required to use this analytic.

  • _time
  • category
  • user
  • src_ip
  • operationName
  • properties.authenticationRequirement
  • properties.status.additionalDetails
  • properties.authenticationDetails{}.succeeded
  • properties.userAgent
  • properties.appDisplayName

How To Implement

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 SignInLogs log category.

Known False Positives

Rapid authentication from the same user using more than 5 different user agents and 3 application IDs is highly unlikely under normal circumstances. However, there are potential scenarios that could lead to false positives.

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
48.0 60 80 $user$ authenticated in a short periof of time with more than 5 different user agents across 3 or more unique application ids.

:information_source: The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.

Reference

Test Dataset

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 | version: 3