Try in Splunk Security Cloud

Description

The following analytic identifies an excessive number of authentication failures, including failed attempts against MFA prompt codes. It uses data from the o365_management_activity dataset, focusing on events where the authentication status is marked as failure. This behavior is significant as it may indicate a brute force attack or an attempt to compromise user accounts. If confirmed malicious, this activity could lead to unauthorized access, data breaches, or further exploitation within the environment.

  • Type: Anomaly
  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
  • Datamodel: Authentication
  • Last Updated: 2024-05-18
  • Author: Rod Soto, Splunk
  • ID: d441364c-349c-453b-b55f-12eccab67cf9

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1110 Brute Force Credential Access
Kill Chain Phase
  • Exploitation
NIST
  • DE.AE
CIS20
  • CIS 10
CVE 


1
2
3
4
5
6



`o365_management_activity` Workload=AzureActiveDirectory UserAuthenticationMethod=* status=failure 
| stats count earliest(_time) AS firstTime latest(_time) AS lastTime values(UserAuthenticationMethod) AS UserAuthenticationMethod values(UserAgent) AS UserAgent values(status) AS status values(src_ip) AS src_ip by user 
| where count > 10 
| `security_content_ctime(firstTime)` 
| `security_content_ctime(lastTime)` 
| `o365_excessive_authentication_failures_alert_filter`

Macros

The SPL above uses the following Macros:

:information_source: o365_excessive_authentication_failures_alert_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
  • Workload
  • UserAuthenticationMethod
  • status
  • UserAgent
  • src_ip
  • user

How To Implement

You must install splunk Microsoft Office 365 add-on. This search works with o365:management:activity

Known False Positives

The threshold for alert is above 10 attempts and this should reduce the number of false positives.

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
64.0 80 80 User $user$ has caused excessive number of authentication failures from $src_ip$ using UserAgent $UserAgent$.

:information_source: 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

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: 3