What Programming Languages Are Used in Z4nzu/hackingtool?

The Z4nzu/hackingtool repository is built primarily in Python, supplemented by Bash scripts, Dockerfile configurations, YAML workflow files, and Markdown documentation.

The Z4nzu/hackingtool project is a comprehensive penetration testing framework that demonstrates how modern security tools combine multiple programming languages for optimal functionality. Understanding the programming languages used in Z4nzu/hackingtool reveals its architecture as a Python-centric application with strategic use of shell scripting and configuration languages for deployment, system operations, and documentation.

Primary Language: Python

Python serves as the backbone of the hackingtool framework, driving all core functionality from the user interface to individual attack modules. The main entry point hackingtool.py initializes the application using the Rich library for terminal formatting, while core.py defines the HackingToolsCollection class that abstracts tool categories. The installer script install.py leverages Python's cross-platform capabilities to handle dependencies, and the entire tools/ package contains Python modules like xss_attack.py and wireless_attack_tools.py that implement specific penetration testing features.

# Main entry point structure (hackingtool.py)

from rich.console import Console
from core import HackingToolsCollection

# Example tool module structure

class XSSAttackTools:
    def show_options(self):
        # Tool logic invoking external utilities via RUN_COMMANDS

        pass

Supporting Languages and Configuration Files

While Python handles the application logic, several other languages manage system operations, deployment, and documentation.

Bash for System-Level Operations

Bash scripts manage installation helpers, update mechanisms, and system commands that Python delegates to the shell. The update.sh script checks internet connectivity and manages repository updates, while many Python modules store shell commands in RUN_COMMANDS strings for execution.

#!/usr/bin/env bash

# From update.sh - connectivity check

echo "[*] Checking internet connectivity..."
curl -s -m 10 https://www.google.com > /dev/null || { echo "No internet"; exit 1; }

Dockerfile for Containerization

The repository includes a Dockerfile written in Docker's domain-specific language (DSL) to enable containerized deployment. This configuration uses a Python 3.10 slim base image and defines the runtime environment for the hacking toolkit.

FROM python:3.10-slim
COPY . /app
WORKDIR /app
RUN pip install -r requirements.txt
ENTRYPOINT ["python", "hackingtool.py"]

YAML for CI/CD Automation

Continuous integration pipelines stored in .github/workflows/*.yml use YAML syntax to define automated testing and installation verification workflows. These files orchestrate GitHub Actions runners to validate the tool's functionality across different environments.

Markdown for Documentation

Project documentation including README.md and README_template.md utilizes Markdown formatting to provide installation instructions, usage guides, and contribution guidelines. These files render the project's documentation layer without executable code.

External Language Dependencies

While the repository contains no native C source files, the framework orchestrates external C programs at runtime. For example, tools/wordlist_generator.py references wlcreator.c for compilation during execution, indicating that the Python application acts as a wrapper for compiled C utilities even though the C source resides outside the main repository.

Summary

• Python powers the entire application stack including hackingtool.py, core.py, install.py, and all modules in the tools/ directory.
• Bash handles system operations through update.sh and inline shell command execution via RUN_COMMANDS.
• Dockerfile DSL enables containerized deployment with Python 3.10 base images.
• YAML configures GitHub Actions workflows in .github/workflows/ for automated testing.
• Markdown formats documentation in README.md and related template files.
• C programs are invoked externally (though not stored in the repo) for performance-critical operations like wordlist generation.

Frequently Asked Questions

Is Z4nzu/hackingtool written entirely in Python?

No, while Python is the primary language used for the core application and all attack modules, the repository also includes Bash scripts for system operations, Dockerfile for containerization, and YAML for CI/CD workflows. Additionally, some Python modules compile and run external C programs at runtime.

What Python version does hackingtool require?

According to the Dockerfile configuration, the project targets Python 3.10 as its base runtime environment. The container definition explicitly uses python:3.10-slim as the foundation for deployment.

Does the repository contain compiled C code?

No, the repository does not include .c source files or compiled binaries within its version control. However, certain tools like the wordlist generator reference external C files (e.g., wlcreator.c) that are compiled during runtime execution, indicating optional C dependencies for specific attack modules.

How does the project use Bash if it's a Python tool?

Bash serves as a glue language for system-level operations that Python handles less efficiently. The update.sh script manages repository updates and connectivity checks, while Python modules store Bash command strings in variables like RUN_COMMANDS to execute shell utilities and external security tools.

{
  "mcpServers": {
    "instagit": {
      "command": "npx",
      "args": ["-y", "instagit@latest"]
    }
  }
}