Ethical Hacking Automation

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

Dolibarr Login Panel - Detect

By kannthu

Informative
Vidoc logoVidoc Module
#panel#dolibarr
Description

What is the "Dolibarr Login Panel - Detect?" module?

The "Dolibarr Login Panel - Detect" module is a test case designed to detect the presence of the Dolibarr login panel. Dolibarr is a popular open-source ERP and CRM software used by businesses for managing various aspects of their operations. 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 pikpikcu and daffainfo.

Impact

This module does not have any direct impact on the target system. It simply detects the presence of the Dolibarr login panel, providing information about its existence.

How does the module work?

The "Dolibarr Login Panel - Detect" module works by sending HTTP requests to the target system and analyzing the responses based on predefined matching conditions. It uses the following matching conditions:

- Header: The module looks for the presence of the "Set-Cookie: DOLSESSID_" header in the response. - Body: It searches for the HTML meta tag with the attribute "name" set to "author" and the content set to "Dolibarr Development Team". - Status: The module expects a response status code of 200, indicating a successful request.

If all of these conditions are met, the module reports the detection of the Dolibarr login panel.

Here is an example of an HTTP request that the module might send:

GET / HTTP/1.1
Host: example.com
User-Agent: Vidoc

Please note that the above example is a simplified representation and may not reflect the exact request used by the module.

Module preview

Concurrent Requests (0)
Passive global matcher
word: Set-Cookie: DOLSESSID_and
word: <meta name="author" content="Dolibarr De...and
status: 200
On match action
Report vulnerability