An ESP8266/NodeMCU-based tool that spoofs multiple fake drone RemoteID broadcasts for testing and educational purposes.
RemoteIDSpoofer is an open-source tool that generates fake drone RemoteID broadcasts using ESP8266/NodeMCU or ESP32 microcontrollers. It simulates multiple virtual drones flying around a specified GPS location, allowing users to test RemoteID detection systems without needing actual drones. The project addresses the need for accessible testing tools in the growing drone identification ecosystem.
Drone enthusiasts, researchers, and developers working with RemoteID systems who need to test detection capabilities without physical drone hardware. Educational institutions and hobbyists exploring aviation identification technologies.
Provides a low-cost, accessible way to test RemoteID detection systems using common microcontroller hardware. Unlike commercial testing solutions, it's open-source, customizable, and built on widely available ESP8266/ESP32 platforms with persistent configuration settings.
NodeMCU RemoteID Spoofer
Spawns up to 16 fake drones with random flight patterns around a configurable GPS location, enabling comprehensive testing of detection systems without physical drones.
Provides a wireless access point and web interface at 192.168.4.1 for easy setup of GPS coordinates and parameters, accessible from any smartphone.
Configuration parameters are saved onboard and remembered across power cycles, eliminating the need for repeated setup after initial configuration.
Compatible with both ESP8266 and ESP32 microcontrollers, as confirmed in the to-do list, offering options for different performance and cost points.
The disclaimer states broadcasting fake RemoteID packets is likely illegal in public airspace, similar to ADS-B spoofing, restricting safe and legal use to controlled, educational environments.
Requires installation of Arduino IDE and manual board configuration, which can be a barrier for users not familiar with microcontroller programming or development environments.
Lacks support for valid RemoteID formats and region selection, as noted in the to-do list, reducing accuracy for simulations that mimic real-world drone identification.
DroneSecurity (NDSS 2023)
This is official repository of our paper "RFUAV: A Benchmark Dataset for Unmanned Aerial Vehicle Detection and Identification". Codes include a two stage model to achieve drone detection and classification using some FFT/STFT analytical method. The Raw data will be free to use after our paper is accept. Star us!!!!, if you think this is useful♥
Web application to monitor drones based on the Remote ID technology over WiFi and Bluetooth.
Robot Vulnerability Database. An archive of robot vulnerabilities and bugs.
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