A modular Python framework for auditing and penetration testing of IoT devices, supporting WiFi, NFC, and BLE technologies.
HomePwn is a Python-based framework for penetration testing and security auditing of IoT devices. It helps security professionals discover devices in home or office networks and exploit vulnerabilities to assess security levels. The tool supports multiple wireless technologies like WiFi, NFC, and BLE through a modular architecture.
Security researchers, ethical hackers, and IoT penetration testers who need to audit the security of connected devices in local environments. It's also suitable for developers and IT professionals assessing IoT device vulnerabilities.
Developers choose HomePwn for its modular design, which allows easy extension to new technologies, and its comprehensive feature set covering device discovery and exploitation across multiple IoT protocols. It provides a unified tool for wireless IoT pentesting without requiring multiple specialized utilities.
HomePwn - Swiss Army Knife for Pentesting of IoT Devices
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Allows easy extension with custom modules for new IoT technologies, as highlighted in the README's description of specific technology modules and discovery modules.
Covers a wide range of wireless protocols including WiFi, BLE, NFC, SSDP, and mDNS for comprehensive device discovery and auditing, as stated in the key features.
Built with Prompt Toolkit, providing a user-friendly command-line experience for executing complex pentesting workflows, enhancing usability over raw scripts.
Implements known vulnerabilities to test IoT device security, with practical examples demonstrated in the attached YouTube videos for techniques like BLE spoofing and NFC cloning.
Requires Linux (Ubuntu/Debian) and specific hardware setups, as per the prerequisites, making it inaccessible for users on other operating systems without significant workarounds.
Involves running installation scripts, setting up virtual environments, and configuring external hardware like Alpha Cards, which can be time-consuming and error-prone for newcomers.
Documentation is provided only as PDF papers, which may not be as easily updated, searchable, or interactive as online wikis or API references, limiting accessibility.