GCP Unusual Number of Failed Authentications From Ip
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
Kill Chain Phase
- Weaponization
- Exploitation
NIST
- DE.AE
CIS20
- CIS 10
CVE
Search
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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:
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 $src_ip$ |
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
- 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
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