# PYAS: Python & C++ Antivirus with ML and Behavioral Monitoring

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PYAS is an advanced antivirus software developed using a hybrid approach of Python and C++. It leverages machine learning and behavioral monitoring to effectively detect and block various threats. This project offers comprehensive security for Windows systems, combining user-mode scanning with kernel-mode protection.

GitHub: https://github.com/87owo/PYAS
OSRepos URL: https://osrepos.com/repo/87owo-pyas

## Summary

PYAS is an advanced antivirus software developed using a hybrid approach of Python and C++. It leverages machine learning and behavioral monitoring to effectively detect and block various threats. This project offers comprehensive security for Windows systems, combining user-mode scanning with kernel-mode protection.

## Topics

- antivirus
- python
- cpp
- security
- machine learning
- windows
- kernel
- yara

## Repository Information

Last analyzed by OSRepos: Sat Jun 13 2026 16:53:25 GMT+0100 (Western European Summer Time)
Detail views: 1
GitHub clicks: 1

## Safety Notice

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## Content

## Introduction

PYAS is an innovative antivirus solution built with a powerful combination of Python and C++. It stands out by integrating machine learning models and behavioral monitoring techniques to provide robust protection against modern threats. Designed for Windows, PYAS offers a multi-layered security approach, operating in both user and kernel modes to safeguard your system.

## Installation

To get started with PYAS, Python 3.10 is recommended. You can install the necessary dependencies using pip:

bash
pip install pystray pefile requests pywebview Pillow yara-python numpy onnxruntime


For model training or other non-essential functions, additional packages are required:

bash
pip install pandas scikit-learn lightgbm onnxmltools orjson


## Examples

PYAS employs a sophisticated architecture to deliver its protective capabilities. In user mode, the Python core manages the web UI and various scanning engines, including PE/ML, YARA, Cloud, and Signature verification. These engines analyze potential threats using machine learning models and predefined rules.

 The system extends its reach into kernel mode with a C++ minifilter driver. This driver provides real-time protection for files, processes, and the registry, and also handles boot protection. Communication between user and kernel modes is facilitated through an ALPC port, ensuring seamless threat detection and mitigation. The integration of LightGBM models further enhances its ability to identify malicious patterns with high accuracy.

## Why Use

PYAS offers several compelling reasons for its use:

*   **Hybrid Protection:** Combines the flexibility of Python for user-mode operations with the performance and deep system access of C++ for kernel-mode protection.
*   **Advanced Threat Detection:** Utilizes machine learning (LightGBM) and YARA rules for highly accurate and adaptive threat identification.
*   **Behavioral Monitoring:** Monitors system behavior to detect and block suspicious activities in real-time.
*   **Comprehensive Coverage:** Protects critical system components, including files, processes, registry, and boot sectors.
*   **Open Source:** Provides transparency and allows community contributions.
*   **Modern Interface:** Features a web-based user interface via pywebview for ease of use.

## Links

Explore PYAS further through these official resources:

*   [GitHub Repository](https://github.com/87owo/PYAS){:target="_blank"}
*   [Official Website](https://pyas-security.com/antivirus){:target="_blank"}
*   [Online Analysis Tool](https://pyas-security.com/analyze){:target="_blank"}
*   [Packaged Downloads](https://github.com/87owo/PYAS/releases){:target="_blank"}
*   [Report Issues](https://github.com/87owo/PYAS/issues){:target="_blank"}