ID | Technique | Tactic |
---|---|---|
T1586 | Compromise Accounts | Resource Development |
T1586.003 | Cloud Accounts | Resource Development |
T1110 | Brute Force | Credential Access |
T1110.003 | Password Spraying | Credential Access |
T1110.004 | Credential Stuffing | Credential Access |
Detection: Azure AD Multi-Source Failed Authentications Spike
Description
The following analytic detects potential distributed password spraying attacks in an Azure AD environment. It identifies a spike in failed authentication attempts across various user-and-IP combinations from multiple source IPs and countries, using different user agents. This detection leverages Azure AD SignInLogs, focusing on error code 50126 for failed authentications. This activity is significant as it indicates an adversary's attempt to bypass security controls by distributing login attempts. If confirmed malicious, this could lead to unauthorized access, data breaches, privilege escalation, and lateral movement within the organization's infrastructure.
Search
1`azure_monitor_aad` category=SignInLogs properties.status.errorCode=50126 properties.authenticationDetails{}.succeeded=false
2| rename properties.* as *
3| bucket span=5m _time
4| eval uniqueIPUserCombo = src_ip . "-" . user
5| stats count min(_time) as firstTime max(_time) as lastTime dc(uniqueIPUserCombo) as uniqueIpUserCombinations, dc(user) as uniqueUsers, dc(src_ip) as uniqueIPs, dc(user_agent) as uniqueUserAgents, dc(location.countryOrRegion) as uniqueCountries values(user) as user, values(src_ip) as ips, values(user_agent) as user_agents, values(location.countryOrRegion) as countries
6| where uniqueIpUserCombinations > 20 AND uniqueUsers > 20 AND uniqueIPs > 20 AND uniqueUserAgents = 1
7| `security_content_ctime(firstTime)`
8| `security_content_ctime(lastTime)`
9| `azure_ad_multi_source_failed_authentications_spike_filter`
Data Source
Name | Platform | Sourcetype | Source |
---|---|---|---|
Azure Active Directory | Azure | 'azure:monitor:aad' |
'Azure AD' |
Macros Used
Name | Value |
---|---|
azure_monitor_aad | sourcetype=azure:monitor:aad |
azure_ad_multi_source_failed_authentications_spike_filter | search * |
azure_ad_multi_source_failed_authentications_spike_filter
is an empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
Annotations
Default Configuration
This detection is configured by default in Splunk Enterprise Security to run with the following settings:
Setting | Value |
---|---|
Disabled | true |
Cron Schedule | 0 * * * * |
Earliest Time | -70m@m |
Latest Time | -10m@m |
Schedule Window | auto |
Creates Risk Event | False |
Implementation
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 SignInLogs log category. The thresholds set within the analytic (such as unique IPs, unique users, etc.) are initial guidelines and should be customized based on the organization's user behavior and risk profile. Security teams are encouraged to adjust these thresholds to optimize the balance between detecting genuine threats and minimizing false positives, ensuring the detection is tailored to their specific environment.
Known False Positives
This detection may yield false positives in scenarios where legitimate bulk sign-in activities occur, such as during company-wide system updates or when users are accessing resources from varying locations in a short time frame, such as in the case of VPNs or cloud services that rotate IP addresses. Filter as needed.
Associated Analytic Story
Risk Based Analytics (RBA)
Risk Message | Risk Score | Impact | Confidence |
---|---|---|---|
An anomalous multi source authentication spike ocurred at $_time$ | 42 | 70 | 60 |
References
-
https://docs.microsoft.com/en-us/security/compass/incident-response-playbook-password-spray
-
https://docs.microsoft.com/azure/active-directory/reports-monitoring/reference-sign-ins-error-codes
Detection Testing
Test Type | Status | Dataset | Source | Sourcetype |
---|---|---|---|---|
Validation | ✅ Passing | N/A | N/A | N/A |
Unit | ✅ Passing | Dataset | Azure AD |
azure:monitor:aad |
Integration | ✅ Passing | Dataset | Azure AD |
azure:monitor:aad |
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: GitHub | Version: 5