How to install HoneyPy on Ubuntu?

Follow the QuickStart Guide in the documentation; it's designed for easy deployment on Debian-based systems using Python 2.7.9. Ensure dependencies are met and use the provided setup steps.

HoneyPy vs Cowrie: which honeypot is better for beginners?

HoneyPy offers a modular plugin system for various services, while Cowrie is specialized for SSH. For beginners wanting a general-purpose honeypot, HoneyPy's extensibility might be beneficial, but Cowrie could be simpler for SSH-focused monitoring.

Does HoneyPy work with Python 3?

No, HoneyPy is written in Python 2.7.9 and is not compatible with Python 3, as stated in the README. This limits its use in modern development environments.

How to create a custom plugin for HoneyPy?

Refer to the plugin architecture documentation; you can extend existing plugins or create new ones by emulating UDP or TCP services. The modular design allows for easy integration through the configuration files.

Is HoneyPy still being updated?

The project is no longer in active development, but the repository remains open for community contributions. The author recommends using honeydb-agent instead for newer features.

Can HoneyPy log to a custom database?

Yes, through its logger system; you can configure it to send data to web service endpoints like HoneyDB, or modify existing loggers. File logging is default, but it's extensible for integration with other systems.

Open-Awesome

HoneyPy

GPL-2.0Python0.7.0

A low to medium interaction honeypot written in Python, designed for easy deployment and extensibility.

GitHub

475 stars91 forks0 contributors

What is HoneyPy?

HoneyPy is a low to medium interaction honeypot written in Python that simulates network services to detect and log malicious activity. It helps security professionals monitor unauthorized access attempts and analyze attack patterns in their network environments. The project is designed for easy deployment and extensibility through plugins and loggers.

Target Audience

Security researchers, network administrators, and cybersecurity enthusiasts who need a customizable honeypot for monitoring and analyzing network threats.

Value Proposition

Developers choose HoneyPy for its modular plugin architecture, which allows easy extension of emulated services, and its multiple logging options that enable real-time data sharing and analysis.

Overview

A low to medium interaction honeypot.

Use Cases

Best For

Monitoring unauthorized network access attempts in a lab environment
Analyzing attack patterns and malware behavior on simulated services
Extending honeypot functionality with custom UDP or TCP service plugins
Logging honeypot data to external services like Twitter or HoneyDB
Deploying a lightweight honeypot on Debian or Ubuntu systems
Educational purposes for learning about network security and intrusion detection

Not Ideal For

Production environments requiring active maintenance and security updates
Teams using modern Python 3.x stacks or needing compatibility with latest libraries
Cross-platform deployments on Windows or macOS without Linux-based systems
High-interaction honeypot scenarios needing deep service emulation beyond low-medium interaction

Pros & Cons

Pros

Modular Plugin Architecture

Extensible with plugins for UDP or TCP services, allowing customization of interaction levels as mentioned in the README's overview.

Flexible Logging Options

Supports multiple loggers including files, Twitter, and web services like HoneyDB, enabling real-time data sharing and analysis per the features.

Easy Deployment

Designed for straightforward installation and configuration, primarily tested on Debian and Ubuntu, making it quick to set up in supported environments.

Community-Driven Development

Open to contributions with an active issue tracker and pull request support, encouraging extensions and improvements.

Cons

Outdated Python Dependency

Built on Python 2.7.9, which is no longer supported, posing security risks and compatibility issues with modern software.

Inactive Project Status

The README states it is no longer in active development, limiting updates, bug fixes, and long-term viability.

Limited Operating System Support

Primarily tested on Debian and Ubuntu, which may require extra effort for deployment on other systems or cloud platforms.

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