Azure AD Successful Single-Factor Authentication
Description
The following analytic identifies a successful authentication event against Azure Active Directory for an account without Multi-Factor Authentication enabled. This could be evidence of a missconfiguration, a policy violation or an account take over attempt that should be investigated
- Type: TTP
- Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Datamodel: Authentication
- Last Updated: 2022-07-12
- Author: Mauricio Velazco, Gowthamaraj Rajendran, Splunk
- ID: a560e7f6-1711-4353-885b-40be53101fcd
Annotations
ATT&CK
Kill Chain Phase
- Weaponization
- Exploitation
- Installation
- Delivery
NIST
- DE.CM
CIS20
- CIS 10
CVE
Search
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`azuread` category=SignInLogs properties.authenticationRequirement=singleFactorAuthentication properties.authenticationDetails{}.succeeded=true
| rename properties.* as *
| stats values(userPrincipalName) as userPrincipalName by _time, ipAddress, appDisplayName, authenticationRequirement
| `azure_ad_successful_single_factor_authentication_filter`
Macros
The SPL above uses the following Macros:
azure_ad_successful_single-factor_authentication_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
Required fields
List of fields required to use this analytic.
- _time
- category
- properties.authenticationRequirement
- properties.authenticationDetails
- properties.userPrincipalName
- properties.ipAddress
- properties.appDisplayName
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. Specifically, this analytic leverages the SignInLogs log category.
Known False Positives
Although not recommended, certain users may be required without multi-factor authentication. Filter as needed
Associated Analytic Story
RBA
Risk Score | Impact | Confidence | Message |
---|---|---|---|
45.0 | 50 | 90 | Successful authentication for user $userPrincipalName$ without MFA |
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.
Reference
- https://attack.mitre.org/techniques/T1078/004/
- [https://docs.microsoft.com/en-us/azure/active-directory/authentication/concept-mfa-howitworks](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
Test Dataset
Replay any dataset to Splunk Enterprise by using our replay.py
tool or the UI.
Alternatively you can replay a dataset into a Splunk Attack Range
source | version: 1