Detection: GCP Unusual Number of Failed Authentications From Ip

Description

The following analytic identifies a single source IP failing to authenticate into Google Workspace with multiple valid users, potentially indicating a Password Spraying attack. It uses Google Workspace login failure events and calculates the standard deviation for source IPs, applying the 3-sigma rule to detect unusual failed authentication attempts. This activity is significant as it may signal an adversary attempting to gain initial access or elevate privileges. If confirmed malicious, this could lead to unauthorized access, data breaches, or further exploitation within the environment.

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

Data Source

Name Platform Sourcetype Source Supported App
Google Workspace login_failure N/A 'gws:reports:admin' 'gws:reports:admin' N/A

Macros Used

Name Value
gws_reports_login sourcetype=gws:reports:login
gcp_unusual_number_of_failed_authentications_from_ip_filter search *
gcp_unusual_number_of_failed_authentications_from_ip_filter is an empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Annotations

- MITRE ATT&CK
+ Kill Chain Phases
+ NIST
+ CIS
- Threat Actors
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
KillChainPhase.EXPLOITAITON
KillChainPhase.WEAPONIZATION
NistCategory.DE_AE
Cis18Value.CIS_10
APT29
APT28
APT38
APT39
DarkVishnya
Dragonfly
FIN5
Fox Kitten
HEXANE
OilRig
Turla
APT28
APT29
APT33
Chimera
HEXANE
Lazarus Group
Leafminer
Silent Librarian
Chimera

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 True
This configuration file applies to all detections of type anomaly. These detections will use Risk Based Alerting.

Implementation

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

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
Unusual number of failed console login attempts (Count: $unique_accounts$) against users from IP Address - $src$ 54 60 90
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.

References

Detection Testing

Test Type Status Dataset Source Sourcetype
Validation Passing N/A N/A N/A
Unit Passing Dataset gws_login gws:reports:login
Integration ✅ Passing Dataset gws_login gws:reports:login

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: 2