Detection rules › Splunk

Azure AD Successful Single-Factor Authentication

Status
production
Severity
medium
Group by
aws::recipientAccountId, aws::userAgent, dest, signature, src, user, vendor_product
Author
Mauricio Velazco, Gowthamaraj Rajendran, Splunk
Source
github.com/splunk/security_content

The following analytic identifies a successful single-factor authentication event against Azure Active Directory. It leverages Azure SignInLogs data, specifically focusing on events where single-factor authentication succeeded. This activity is significant as it may indicate a misconfiguration, policy violation, or potential account takeover attempt. If confirmed malicious, an attacker could gain unauthorized access to the account, potentially leading to data breaches, privilege escalation, or further exploitation within the environment.

MITRE ATT&CK coverage

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 Successful Single-Factor Authentication
id: a560e7f6-1711-4353-885b-40be53101fcd
version: 13
creation_date: '2022-07-12'
modification_date: '2026-05-13'
author: Mauricio Velazco, Gowthamaraj Rajendran, Splunk
status: production
type: TTP
description: The following analytic identifies a successful single-factor authentication event against Azure Active Directory. It leverages Azure SignInLogs data, specifically focusing on events where single-factor authentication succeeded. This activity is significant as it may indicate a misconfiguration, policy violation, or potential account takeover attempt. If confirmed malicious, an attacker could gain unauthorized access to the account, potentially leading to data breaches, privilege escalation, or further exploitation within the environment.
data_source:
    - Azure Active Directory
search: |-
    `azure_monitor_aad` category=SignInLogs properties.authenticationRequirement=singleFactorAuthentication properties.authenticationDetails{}.succeeded=true
      | rename properties.* as *
      | rename userAgent as user_agent
      | fillnull
      | stats count min(_time) as firstTime max(_time) as lastTime
        BY dest user src
           vendor_account vendor_product user_agent
           signature
      | `security_content_ctime(firstTime)`
      | `security_content_ctime(lastTime)`
      | `azure_ad_successful_single_factor_authentication_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 Signin log category.
known_false_positives: Although not recommended, certain users may be required without multi-factor authentication. Filter as needed
references:
    - https://attack.mitre.org/techniques/T1078/004/
    - https://docs.microsoft.com/en-us/azure/active-directory/authentication/concept-mfa-howitworks*
    - https://www.forbes.com/sites/daveywinder/2020/07/08/new-dark-web-audit-reveals-15-billion-stolen-logins-from-100000-breaches-passwords-hackers-cybercrime/?sh=69927b2a180f
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: Successful authentication for user $user$ without MFA
    entity:
        field: user
        type: user
        score: 50
threat_objects:
    - field: src
      type: ip_address
analytic_story:
    - Azure Active Directory Account Takeover
asset_type: Azure Active Directory
mitre_attack_id:
    - T1078.004
    - T1586.003
product:
    - Splunk Enterprise
    - Splunk Enterprise Security
    - Splunk Cloud
category: cloud
security_domain: identity
tests:
    - name: True Positive Test
      attack_data:
        - data: https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/attack_techniques/T1078.004/azuread/azure-audit.log
          source: Azure AD
          sourcetype: azure:monitor:aad
      test_type: unit

Stages and Predicates

Stage 1: search

`azure_monitor_aad` category=SignInLogs properties.authenticationRequirement=singleFactorAuthentication properties.authenticationDetails{}.succeeded=true

Stage 2: rename

| rename properties.* as *

Stage 3: rename

| rename userAgent as user_agent

Stage 4: fillnull

| fillnull

Stage 5: stats

| stats count min(_time) as firstTime max(_time) as lastTime
    BY dest user src
       vendor_account vendor_product user_agent
       signature

Stage 6: search

| `security_content_ctime(firstTime)`

Stage 7: search

| `security_content_ctime(lastTime)`

Stage 8: search

| `azure_ad_successful_single_factor_authentication_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
categoryeq
  • SignInLogs
properties.authenticationDetails{}.succeededeq
  • true
properties.authenticationRequirementeq
  • singleFactorAuthentication
sourcetypeeq
  • azure:monitor:aad