Detection rules › Splunk

Azure AD Concurrent Sessions From Different Ips

Status
production
Severity
medium
Group by
_time, aws::recipientAccountId, category, user, vendor_product
Author
Mauricio Velazco, Bhavin Patel, Splunk
Source
github.com/splunk/security_content

The following analytic detects an Azure AD account with concurrent sessions originating from multiple unique IP addresses within a 5-minute window. It leverages Azure Active Directory NonInteractiveUserSignInLogs to identify this behavior by analyzing successful authentication events and counting distinct source IPs. This activity is significant as it may indicate session hijacking, where an attacker uses stolen session cookies to access corporate resources from a different location. If confirmed malicious, this could lead to unauthorized access to sensitive information and potential data breaches.

MITRE ATT&CK coverage

TacticTechniques
CollectionT1185 Browser Session Hijacking

Rules detecting the same action

Other rules on this platform that filter on the same API call or operation.

Rule body splunk

name: Azure AD Concurrent Sessions From Different Ips
id: a9126f73-9a9b-493d-96ec-0dd06695490d
version: 15
creation_date: '2023-01-24'
modification_date: '2026-05-13'
author: Mauricio Velazco, Bhavin Patel, Splunk
status: production
type: TTP
description: The following analytic detects an Azure AD account with concurrent sessions originating from multiple unique IP addresses within a 5-minute window. It leverages Azure Active Directory NonInteractiveUserSignInLogs to identify this behavior by analyzing successful authentication events and counting distinct source IPs. This activity is significant as it may indicate session hijacking, where an attacker uses stolen session cookies to access corporate resources from a different location. If confirmed malicious, this could lead to unauthorized access to sensitive information and potential data breaches.
data_source:
    - Azure Active Directory
search: |-
    `azure_monitor_aad` properties.authenticationDetails{}.succeeded=true category=NonInteractiveUserSignInLogs action=success
      | rename properties.* as *
      | bucket span=5m _time
      | rename userAgent as user_agent
      | fillnull
      | stats count min(_time) as firstTime max(_time) as lastTime dc(src) as unique_ips values(dest) as dest values(src) as src values(user_agent) as user_agent
        BY user _time vendor_account
           vendor_product category
      | where unique_ips > 1
      | `security_content_ctime(firstTime)`
      | `security_content_ctime(lastTime)`
      | `azure_ad_concurrent_sessions_from_different_ips_filter`
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: A user with concurrent sessions 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. Also consider the geographic location of the IP addresses and filter out IP space that belong to your organization.
references:
    - https://attack.mitre.org/techniques/T1185/
    - https://breakdev.org/evilginx-2-next-generation-of-phishing-2fa-tokens/
    - https://github.com/kgretzky/evilginx2
drilldown_searches:
    - name: View the detection results for - "$user$"
      search: '%original_detection_search% | search  user = "$user$"'
      earliest_offset: $info_min_time$
      latest_offset: $info_max_time$
    - name: View risk events for the last 7 days for - "$user$"
      search: '| from datamodel Risk.All_Risk | search normalized_risk_object IN ("$user$") | stats count min(_time) as firstTime max(_time) as lastTime values(search_name) as "Search Name" values(risk_message) as "Risk Message" values(analyticstories) as "Analytic Stories" values(annotations._all) as "Annotations" values(annotations.mitre_attack.mitre_tactic) as "ATT&CK Tactics" by normalized_risk_object | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`'
      earliest_offset: 7d
      latest_offset: "0"
finding:
    title: User $user$ has concurrent sessions from more than one unique IP address in the span of 5 minutes.
    entity:
        field: user
        type: user
        score: 50
threat_objects:
    - field: src
      type: ip_address
analytic_story:
    - Compromised User Account
    - Azure Active Directory Account Takeover
    - Scattered Lapsus$ Hunters
asset_type: Azure Tenant
mitre_attack_id:
    - T1185
product:
    - Splunk Enterprise
    - Splunk Enterprise Security
    - Splunk Cloud
category: cloud
security_domain: threat
tests:
    - name: True Positive Test
      attack_data:
        - data: https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/attack_techniques/T1185/azure_ad_concurrent_sessions_from_different_ips/azuread.log
          source: Azure AD
          sourcetype: azure:monitor:aad
      test_type: unit

Stages and Predicates

Stage 1: search

`azure_monitor_aad` properties.authenticationDetails{}.succeeded=true category=NonInteractiveUserSignInLogs action=success

Stage 2: rename

| rename properties.* as *

Stage 3: bucket

| bucket span=5m _time

Stage 4: rename

| rename userAgent as user_agent

Stage 5: fillnull

| fillnull

Stage 6: stats

| stats count min(_time) as firstTime max(_time) as lastTime dc(src) as unique_ips values(dest) as dest values(src) as src values(user_agent) as user_agent
    BY user _time vendor_account
       vendor_product category

Stage 7: where

| where unique_ips > 1

Stage 8: search

| `security_content_ctime(firstTime)`

Stage 9: search

| `security_content_ctime(lastTime)`

Stage 10: search

| `azure_ad_concurrent_sessions_from_different_ips_filter`

Indicators

Each row is a field, operator, and value that the rule matches. The corpus column counts how many other rules in the catalog look for the same combination: high numbers point to widely-used, community-vetted indicators. Blank or 1 shows that the indicator is specific to this rule.

FieldKindValues
actioneq
  • success
categoryeq
  • NonInteractiveUserSignInLogs
properties.authenticationDetails{}.succeededeq
  • true
sourcetypeeq
  • azure:monitor:aad
unique_ipsgt
  • 1