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de4py

⚠️ de4py is FREE & OPEN SOURCE (CC BY-NC 4.0).
Any paid versions sold elsewhere or commercial use are NOT permitted.
If you paid for de4py, you were misled.

De4py is an advanced Python deobfuscator with a beautiful UI (PySide6) and a robust set of features for malware analysts and reverse engineers. It supports both automatic deobfuscation of common packers and manual analysis tools.

Maintained by Fadi002 and AdvDebug.

🚀 Features

Feature	Function
Onyx Engine (AI)	Advanced deobfuscation utilizing local LLMs (Ollama) combined with AST cleaning, control-flow flattening recovery, and pattern matching.
Legacy Deobfuscation	Direct support for popular obfuscators: Jawbreaker, BlankOBF, PlusOBF, Wodx, Hyperion, pyobfuscate.
File Analyzer	Detection of packers (PyInstaller, unpy2exe), dynamic hash calculation, suspicious string lookup, and metadata extraction.
Pyshell GUI & Code Execution	Custom GUI to execute Python code inside external target processes (useful for dynamic analysis and licensing bypasses).
Modern UI	Built with PySide6 and a custom dark theme for a premium look and feel. CLI mode also supported.
Global Localization	Support for over 18+ languages out of the box, powered by a community-driven localization engine.
Plugin Architecture & API	Extensible plugin system to create custom analyzers. You can also use de4py directly as a programmable library in your own tools.
Behavior Monitor	Monitor process handles, memory access, and sockets. Built-in developer tools for real-time inspection.

📦 Installation & Usage

Prerequisites

• Python 3.10+
• Windows (recommended for full feature support)

Installation

You can install de4py as a package:

bashCopy
git clone https://github.com/Fadi002/de4py.git
cd de4py
pip install .

Running

GUI Mode:

bashCopy
python -m de4py
# OR
python main.py

CLI Mode:

bashCopy
python -m de4py --cli

🧠 Onyx Engine & Ollama Setup

To use the advanced Onyx-Alpha Deobfuscator (which utilizes local LLMs for heavily obfuscated code), you need to set up Ollama:

1. Download and install Ollama.
2. Open your terminal and pull the required model (default is qwen2.5-coder:1.5b):

   bashCopy
   ollama run qwen2.5-coder:1.5b

3. Once the model is downloaded and running, the Onyx engine in de4py will automatically connect to it for AI-assisted deobfuscation. You can change the model and thresholds in the UI settings.

🛠 Project Structure

The project has been refactored for clarity:

de4py/
├── de4py/               # Main Package
│   ├── core/            # Core logic (EngineManager, Interfaces)
│   ├── engines/         # Deobfuscators and Analyzers
│   ├── ui/              # PySide6 User Interface
│   ├── config/          # Configuration management
│   └── utils/           # Utilities (RPC, TUI, etc.)
├── plugins/             # External Plugins folder (Root)
├── main.py              # Entry point
└── pyproject.toml       # Project configuration

🤝 Contributions

All contributions are welcome!

🔗 Community

• Matrix: Join our Matrix room 🔒 (recommended)
• Signal: Join our Signal room
• Discord: Join here 💬

🌐 Help Translate de4py

We use Crowdin for translations.

• Select a language you want to translate.
• Use the Crowdin web editor.
• Submit translations for review.

⚠️ Disclaimer

This tool is for educational purposes only. Never deobfuscate software without permission. The developers are not responsible for misuse.

📄 License

Licensed under Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0).

📝 Attribution Notice

This project was created by Fadi002.

If you fork or redistribute this project, you must retain the original copyright notices
and provide appropriate attribution according to the CC BY-NC 4.0 license.
Commercial use is not permitted without explicit permission from the author.