VirtualPyDetector (VPD) 🔍

VirtualPyDetector (VPD) is a Python library designed to detect virtualized and sandboxed environments. It uses a multi-layered approach, combining several techniques to improve detection accuracy. This tool is useful for security analysis, malware research, and other applications requiring robust environment detection.

Currently, VPD focuses on detecting:

• Virtual Machines (VMs)
• Debuggers

Future development may include detection of:

• Sandboxes (Currently, limited checks are present)

Features ✨

• Multi-Layered Analysis: Employs various detection techniques (see below) for enhanced accuracy.
• Cross-Platform Compatibility: Supports Windows, macOS, and Linux (with varying levels of completeness). Some features may not function on all platforms.
• Simple API: Easy to integrate into existing Python projects.

Installation 📦

Currently, the simplest way to use VirtualPyDetector is to copy VirtualPyDetector.py into your project directory. (Future versions may offer a more formal installation method via pip).

Usage 🚀

see this file in example.py for examples.

Detection Techniques 🛠️

VPD uses a combination of the following techniques:

• CPU Information: Checks for known virtual machine CPU vendor strings.
• MAC Address Analysis: Examines MAC addresses for known virtual machine OUI prefixes.
• Device Driver Enumeration: Identifies known virtual machine device drivers.
• System Processes: Checks for known virtual machine processes.
• Timing Anomalies: Detects timing differences that may indicate virtualization.
• Debugger Detection: Checks for the presence of debuggers.
• Registry Analysis: Checks for known virtual machine registry keys.
• File System Analysis: Checks for known virtual machine files.

Limitations ⚠️

• Evasion: Advanced virtualization environments may be able to evade detection.
• False Positives: It's possible to get false positives in some cases.
• Platform Specificity: Some detection methods are platform-specific.
• Ongoing Development: This project is under active development, and detection methods may change.

Contributing 🤝

Contributions are welcome! Please feel free to submit pull requests or open issues to discuss potential improvements.