Detection rules › Splunk
Azure Runbook Webhook Created
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
| Tactic | Techniques |
|---|---|
| Initial Access | T1078.004 Valid Accounts: Cloud Accounts |
| Persistence | T1078.004 Valid Accounts: Cloud Accounts |
| Privilege Escalation | T1078.004 Valid Accounts: Cloud Accounts |
| Stealth | T1078.004 Valid Accounts: Cloud Accounts |
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.
| Field | Kind | Values |
|---|---|---|
operationName.value | eq |
|
sourcetype | eq |
|
status.value | eq |
|