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Description

The following analytic identifies one source IP failing to authenticate into the Google Workspace with multiple valid users. This behavior could represent an adversary performing a Password Spraying attack against a Google Workspace enviroment to obtain initial access or elevate privileges. The detection calculates the standard deviation for source IP and leverages the 3-sigma statistical rule to identify an unusual number of failed authentication attempts. To customize this analytic, users can try different combinations of the bucket span time and the calculation of the upperBound field. This logic can be used for real time security monitoring as well as threat hunting exercises. While looking for anomalies using statistical methods like the standard deviation can have benefits, we also recommend using threshold-based detections to complement coverage. A similar analytic following the threshold model is GCP Multiple Users Failing To Authenticate From Ip

  • Type: Anomaly

  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud

  • Last Updated: 2022-10-13
  • Author: Bhavin Patel, Splunk
  • ID: bd8097ed-958a-4873-87d9-44f2b4d85705

Annotations

ATT&CK

ATT&CK

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
Kill Chain Phase
  • Exploitation
NIST
  • DE.CM
CIS20
  • CIS 3
  • CIS 5
  • CIS 16
CVE 


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`gws_reports_login` event.type = login event.name = login_failure
| bucket span=5m _time 
| stats  dc(user_name) AS unique_accounts values(user_name) as tried_accounts values(authentication_method) AS authentication_method by _time, src 
| eventstats  avg(unique_accounts) as ip_avg , stdev(unique_accounts) as ip_std by _time 
| eval  upperBound=(ip_avg+ip_std*3) 
| eval  isOutlier=if(unique_accounts > 10 and unique_accounts >= upperBound, 1, 0) 
| where isOutlier =1
| `gcp_unusual_number_of_failed_authentications_from_ip_filter`

Macros

The SPL above uses the following Macros:

:information_source: gcp_unusual_number_of_failed_authentications_from_ip_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
  • event.name
  • src
  • event.type
  • user_name

How To Implement

You must install the latest version of Splunk Add-on for Google Workspace from Splunkbase (https://splunkbase.splunk.com/app/5556) which allows Splunk administrators to collect Google Workspace event data in Splunk using Google Workspace APIs. We would also recommend tuning the detection by adjusting the window span and unique_accounts threshold values according to your environment. Specifically, this analytic leverages the User log events.

Known False Positives

No known false positives for this detection. Please review this alert

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
54.0 60 90 Unusual number of failed console login attempts against users $tried_accounts$ seen from $src_ip$

: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: 1