Detection: Web Fraud - Password Sharing Across Accounts

REMOVED DETECTION

This detection has been removed from the Splunk Threat Research content library and is no longer maintained or supported.

Reason: Detection deprecated as it no longer effectively identifies the intended malicious activity

Removed in version: 5.2.0

If you have any questions or concerns, please reach out to us at research@splunk.com.

Updated Date: 2026-05-13 ID: 31337a1a-53b9-4e05-96e9-55c934cb71d3 Author: Jim Apger, Splunk Type: Anomaly Product: Splunk Enterprise Security

Description

This search is used to identify user accounts that share a common password.

Search

1`stream_http` http_content_type=text* uri=/magento2/customer/account/loginPost*  
2| rex field=form_data "login\[username\]=(?<Username>[^&
3|^$]+)" 
4| rex field=form_data "login\[password\]=(?<Password>[^&
5|^$]+)" 
6| stats dc(Username) as UniqueUsernames values(Username) as user list(src_ip) as src_ip by Password
7|where UniqueUsernames>5 
8| `web_fraud___password_sharing_across_accounts_filter`

Data Source

No data sources specified for this detection.

Macros Used

Name	Value
stream_http	`sourcetype=stream:http`
web_fraud___password_sharing_across_accounts_filter	``

web_fraud___password_sharing_across_accounts_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

Default Configuration

This detection is configured by default in Splunk Enterprise Security to run with the following settings:

Setting	Value
Disabled	true
Cron Schedule	`N/A`
Earliest Time	`N/A`
Latest Time	`N/A`
Schedule Window	`N/A`
Creates Finding (Notable)	No
Creates Intermediate Finding (Risk Event)	No

Anomaly detections generate Intermediate Findings (Risk Events). They do not generate a Finding (Notable) directly.

Implementation

We need to start with a dataset that allows us to see the values of usernames and passwords that users are submitting to the website hosting the Magento2 e-commerce platform (commonly found in the HTTP form_data field). A tokenized or hashed value of a password is acceptable and certainly preferable to a clear-text password. Common data sources used for this detection are customized Apache logs, customized IIS, and Splunk Stream.

Known False Positives

As is common with many fraud-related searches, we are usually looking to attribute risk or synthesize relevant context with loosely written detections that simply detect anamoluous behavior.

Associated Analytic Story

Web Fraud Detection

References

Detection Testing

Test Type	Status	Dataset	Source	Sourcetype
Validation	Not Applicable	N/A	N/A	N/A
Unit	Not Applicable	N/A	`N/A`	`N/A`
Integration	Not Applicable	N/A	`N/A`	`N/A`

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: 4