Detection rules › Splunk
O365 Multiple AppIDs and UserAgents Authentication Spike
The following analytic identifies unusual authentication activity in an O365 environment, where a single user account experiences more than 8 authentication attempts using 3 or more unique application IDs and over 5 unique user agents within a short timeframe. It leverages O365 audit logs, focusing on authentication events and applying statistical thresholds. This behavior is significant as it may indicate an adversary probing for multi-factor authentication weaknesses. If confirmed malicious, it suggests a compromised account, potentially leading to unauthorized access, privilege escalation, and data exfiltration. Early detection is crucial to prevent further exploitation.
MITRE ATT&CK coverage
| Tactic | Techniques |
|---|---|
| Initial Access | T1078 Valid Accounts |
| Persistence | T1078 Valid Accounts |
| Privilege Escalation | T1078 Valid Accounts |
| Stealth | T1078 Valid Accounts |
Rules detecting the same action
Other rules on this platform that filter on the same API call or operation.
- High Number of Login Failures from a single source (Splunk)
- M365 Identity Login from Atypical Region (Elastic)
- M365 Identity Login from Impossible Travel Location (Elastic)
- M365 Identity User Account Lockouts (Elastic)
- M365 Identity User Brute Force Attempted (Elastic)
- O365 Concurrent Sessions From Different Ips (Splunk)
- O365 Excessive SSO logon errors (Splunk)
- O365 High Number Of Failed Authentications for User (Splunk)
Rule body splunk
name: O365 Multiple AppIDs and UserAgents Authentication Spike
id: 66adc486-224d-45c1-8e4d-9e7eeaba988f
version: 11
creation_date: '2023-12-06'
modification_date: '2026-05-13'
author: Mauricio Velazco, Splunk
status: production
type: Anomaly
description: The following analytic identifies unusual authentication activity in an O365 environment, where a single user account experiences more than 8 authentication attempts using 3 or more unique application IDs and over 5 unique user agents within a short timeframe. It leverages O365 audit logs, focusing on authentication events and applying statistical thresholds. This behavior is significant as it may indicate an adversary probing for multi-factor authentication weaknesses. If confirmed malicious, it suggests a compromised account, potentially leading to unauthorized access, privilege escalation, and data exfiltration. Early detection is crucial to prevent further exploitation.
data_source:
- O365 UserLoggedIn
- O365 UserLoginFailed
search: |-
`o365_management_activity` Workload=AzureActiveDirectory (Operation=UserLoggedIn OR Operation=UserLoginFailed)
| bucket span=5m _time
| stats dc(_raw) as failed_attempts dc(ApplicationId) as unique_app_ids dc(UserAgent) as unique_user_agents values(ApplicationId) values(OS) values(signature) as signature
BY _time user src
vendor_account vendor_product dest
| where failed_attempts > 5 and unique_user_agents > 5 and unique_app_ids > 2
| `o365_multiple_appids_and_useragents_authentication_spike_filter`
how_to_implement: You must install the Splunk Microsoft Office 365 Add-on and ingest Office 365 management activity events.
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.
references:
- https://attack.mitre.org/techniques/T1078/
- https://www.blackhillsinfosec.com/exploiting-mfa-inconsistencies-on-microsoft-services/
- https://github.com/dafthack/MFASweep
- https://www.youtube.com/watch?v=SK1zgqaAZ2E
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"
intermediate_findings:
entities:
- field: user
type: user
score: 20
message: $user$ authenticated in a short period of time with more than 5 different user agents across 3 or more unique application ids.
threat_objects:
- field: src
type: ip_address
analytic_story:
- Office 365 Account Takeover
asset_type: O365 Tenant
mitre_attack_id:
- T1078
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/o365_multiple_appids_and_useragents_auth/o365_multiple_appids_and_useragents_auth.log
source: o365
sourcetype: o365:management:activity
test_type: unit
Stages and Predicates
Stage 1: search
`o365_management_activity` Workload=AzureActiveDirectory (Operation=UserLoggedIn OR Operation=UserLoginFailed)
Stage 2: bucket
| bucket span=5m _time
Stage 3: stats
| stats dc(_raw) as failed_attempts dc(ApplicationId) as unique_app_ids dc(UserAgent) as unique_user_agents values(ApplicationId) values(OS) values(signature) as signature
BY _time user src
vendor_account vendor_product dest
Stage 4: where
| where failed_attempts > 5 and unique_user_agents > 5 and unique_app_ids > 2
Stage 5: search
| `o365_multiple_appids_and_useragents_authentication_spike_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 |
|---|---|---|
Operation | eq |
|
Workload | eq |
|
failed_attempts | gt |
|
sourcetype | eq |
|
unique_app_ids | gt |
|
unique_user_agents | gt |
|