Detection rules › Splunk
GCP Unusual Number of Failed Authentications From Ip
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.
Known false positives
- No known false positives for this detection. Please review this alert
MITRE ATT&CK coverage
| Tactic | Techniques |
|---|---|
| Resource Development | |
| Credential Access |
Telemetry coverage
| Platform | Record / event type |
|---|---|
| Google Workspace | login_failure: Login Failure |
Rules detecting the same action
These rules filter on the same operation.
Rule body
name: GCP Unusual Number of Failed Authentications From Ip
id: bd8097ed-958a-4873-87d9-44f2b4d85705
version: 11
creation_date: '2022-09-26'
modification_date: '2026-05-13'
author: Bhavin Patel, Splunk
status: production
type: Anomaly
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.
data_source:
- Google Workspace
search: |-
`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`
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
references:
- https://cloud.google.com/blog/products/identity-security/how-google-cloud-can-help-stop-credential-stuffing-attacks
- https://www.slideshare.net/dafthack/ok-google-how-do-i-red-team-gsuite
- https://attack.mitre.org/techniques/T1110/003/
- https://www.blackhillsinfosec.com/wp-content/uploads/2020/05/Breaching-the-Cloud-Perimeter-Slides.pdf
intermediate_findings:
entities:
- field: tried_accounts
type: user
score: 20
message: 'Unusual number of failed console login attempts (Count: $unique_accounts$) against users from IP Address - $src$'
threat_objects:
- field: src
type: ip_address
analytic_story:
- GCP Account Takeover
asset_type: Google Cloud Platform tenant
mitre_attack_id:
- T1110.003
- T1110.004
- T1586.003
product:
- Splunk Enterprise
- Splunk Enterprise Security
- Splunk Cloud
category: cloud
security_domain: threat
Stages and Predicates
Stage 1: search
`gws_reports_login` event.type = login event.name = login_failure
Stage 2: bucket
| bucket span=5m _time
Stage 3: stats
| stats dc(user_name) AS unique_accounts values(user_name) as tried_accounts values(authentication_method) AS authentication_method
BY _time, src
Stage 4: eventstats
| eventstats avg(unique_accounts) as ip_avg , stdev(unique_accounts) as ip_std
BY _time
Stage 5: eval
| eval upperBound=(ip_avg+ip_std*3)
Stage 6: eval
| eval isOutlier=if(unique_accounts > 10 and unique_accounts >= upperBound, 1, 0)
isOutlier =if
unique_accounts > 10 AND unique_accounts >= upperBound1else
0Stage 7: where
| where isOutlier =1
Stage 8: search
| `gcp_unusual_number_of_failed_authentications_from_ip_filter`
Indicators
These rows show field, operator, and value matches.
| Field | Kind | Values | Search |
|---|---|---|---|
event.name | eq |
| field:"event.name" kind:eq value:"login_failure" |
event.type | eq |
| field:"event.type" kind:eq value:"login" |
isOutlier | eq |
| field:"isOutlier" kind:eq value:"1" |
sourcetype | eq |
| field:"sourcetype" kind:eq value:"gws:reports:login" |