Detection rules › Splunk

Azure Runbook Webhook Created

Status
production
Severity
medium
Group by
object, object_path, resourceGroupName, src_ip, user
Author
Mauricio Velazco, Brian Serocki, Splunk
Source
github.com/splunk/security_content

The following analytic detects the creation of a new Automation Runbook Webhook within an Azure tenant. It leverages Azure Audit events, specifically the "Create or Update an Azure Automation webhook" operation, to identify this activity. This behavior is significant because Webhooks can trigger Automation Runbooks via unauthenticated URLs exposed to the Internet, posing a security risk. If confirmed malicious, an attacker could use this to execute code, create users, or maintain persistence within the environment, potentially leading to unauthorized access and control over Azure resources.

MITRE ATT&CK coverage

Rule body splunk

name: Azure Runbook Webhook Created
id: e98944a9-92e4-443c-81b8-a322e33ce75a
version: 15
creation_date: '2022-08-23'
modification_date: '2026-05-13'
author: Mauricio Velazco, Brian Serocki, Splunk
status: production
type: TTP
description: The following analytic detects the creation of a new Automation Runbook Webhook within an Azure tenant. It leverages Azure Audit events, specifically the "Create or Update an Azure Automation webhook" operation, to identify this activity. This behavior is significant because Webhooks can trigger Automation Runbooks via unauthenticated URLs exposed to the Internet, posing a security risk. If confirmed malicious, an attacker could use this to execute code, create users, or maintain persistence within the environment, potentially leading to unauthorized access and control over Azure resources.
data_source:
    - Azure Audit Create or Update an Azure Automation webhook
search: |-
    `azure_audit` operationName.value="Microsoft.Automation/automationAccounts/webhooks/write" status.value=Succeeded
      | dedup object
      | rename claims.ipaddr as src_ip
      | rename caller as user
      | stats count min(_time) as firstTime max(_time) as lastTime values(dest) as dest
        BY object user, src_ip,
           resourceGroupName, object_path
      | `security_content_ctime(firstTime)`
      | `security_content_ctime(lastTime)`
      | `azure_runbook_webhook_created_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 Audit events into your Splunk environment. Specifically, this analytic leverages the Azure Activity log category.
known_false_positives: Administrators may legitimately create Azure Runbook Webhooks. Filter as needed.
references:
    - https://docs.microsoft.com/en-us/azure/automation/overview
    - https://docs.microsoft.com/en-us/azure/automation/automation-runbook-types
    - https://docs.microsoft.com/en-us/azure/automation/automation-webhooks?tabs=portal
    - https://www.inversecos.com/2021/12/how-to-detect-malicious-azure.html
    - https://www.netspi.com/blog/technical/cloud-penetration-testing/maintaining-azure-persistence-via-automation-accounts/
    - https://microsoft.github.io/Azure-Threat-Research-Matrix/Persistence/AZT503/AZT503-3/
    - https://attack.mitre.org/techniques/T1078/004/
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: A new Azure Runbook Webhook $object$ was created by $user$
    entity:
        field: user
        type: user
        score: 50
analytic_story:
    - Azure Active Directory Persistence
asset_type: Azure Tenant
mitre_attack_id:
    - T1078.004
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/T1078.004/azure_runbook_webhook/azure-activity.log
          source: mscs:azure:audit
          sourcetype: mscs:azure:audit
      test_type: unit

Stages and Predicates

Stage 1: search

`azure_audit` operationName.value="Microsoft.Automation/automationAccounts/webhooks/write" status.value=Succeeded

Stage 2: dedup

| dedup object

Stage 3: rename

| rename claims.ipaddr as src_ip

Stage 4: rename

| rename caller as user

Stage 5: stats

| stats count min(_time) as firstTime max(_time) as lastTime values(dest) as dest
    BY object user, src_ip,
       resourceGroupName, object_path

Stage 6: search

| `security_content_ctime(firstTime)`

Stage 7: search

| `security_content_ctime(lastTime)`

Stage 8: search

| `azure_runbook_webhook_created_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
operationName.valueeq
  • "Microsoft.Automation/automationAccounts/webhooks/write"
sourcetypeeq
  • mscs:azure:audit
status.valueeq
  • Succeeded