Module development

Commix supports modular design, making it easy to extend its capabilities or tailor its behavior by creating and integrating custom Python modules. This flexibility is useful for penetration testers, researchers, and developers who want to experiment with new exploitation techniques or automate specific tasks.

Creating a new module

Assume we want to create a simple custom module named new_module.py that prints the message:

Hello world from the new module!

Step 1: Define the module

Create a new file named new_module.py and place it in the following directory:

/src/core/modules/

Inside this file, define the main() function as follows:

def main():
    print("Hello world from the new module!")
    # Additional logic can be added here.

This function serves as the module's entry point and can include any Python logic relevant to your testing needs.

Integrating the module with commix

After creating the module, you must import and invoke it from within the commix codebase.

Step 2: Modify module_handler.py

Open the file located at:

/src/core/module_handler.py

Locate the load_modules() function and modify it as follows:

def load_modules(url, http_request_method):
    # Existing code...

    from src.core.modules import new_module  # Import your module
    new_module.main()                        # Execute your module's entry point

    # Existing code...

This ensures your module is loaded and executed during Commix's module-handling phase.

Summary

To add a new module to Commix:

1. Create a Python script (e.g., new_module.py) in /src/core/modules/.
2. Define a main() function or any other callable function you plan to use.
3. Import the module and invoke it inside load_modules() in module_handler.py.

This pattern supports rapid development and testing of new capabilities without deeply modifying the core logic of Commix. It also encourages clean separation of concerns and modular reuse of code.

Example use cases for custom modules

• Custom payload generation
• Target-specific vulnerability fingerprinting
• Extended reporting or output formatting
• Integration with external tools or platforms
• Automated post-exploitation routines

By leveraging this extensibility, users can adapt Commix to fit specialized workflows or research requirements.