Ethical Hacking Automation

Automate Recon and scanning process with Vidoc. All security teams in one place

Apache Superset Login Panel - Detect

By kannthu

Informative
Vidoc logoVidoc Module
#panel#superset
Description

Apache Superset Login Panel - Detect

What is the "Apache Superset Login Panel - Detect?"

The "Apache Superset Login Panel - Detect" module is designed to detect the presence of the Apache Superset login panel. Apache Superset is a data exploration and visualization platform that allows users to create interactive dashboards and reports. This module focuses on identifying the login panel specifically.

The severity of this module is classified as informative, meaning it provides valuable information but does not indicate a vulnerability or misconfiguration.

This module was authored by DhiyaneshDk.

Impact

This module does not have a direct impact on the security of the Apache Superset application. It simply detects the presence of the login panel, providing information about the application's configuration.

How does the module work?

The module works by sending an HTTP GET request to the "/login" path of the target website. It then applies a series of matching conditions to determine if the Apache Superset login panel is present.

The matching conditions include:

- Checking if the response body contains the string "alt="Superset"" - Verifying that the response header includes the string "text/html" - Ensuring that the response status code is 200 (OK)

If all of these conditions are met, the module reports a successful detection of the Apache Superset login panel.

For example, the module might send the following HTTP request:

GET /login HTTP/1.1
Host: example.com

Please note that this is a simplified example and the actual HTTP request may contain additional headers or parameters.

Module preview

Concurrent Requests (1)
1. HTTP Request template
GET/login
Matching conditions
word: alt="Superset"and
word: text/htmland
status: 200
Passive global matcher
No matching conditions.
On match action
Report vulnerability