Reverse Engineering: Yehuda Lab-Grown Diamond Detection Device
Through reverse engineering, we analyzed Yehuda’s lab-grown diamond detection device, extracting its Node.js software, emulating it locally, and documenting its algorithms.
Technologies Used
- Raspberry Pi – Extracted and analyzed the device’s software.
- Node.js – Reverse-engineered the backend logic.
- Computer Vision – Reproduced and documented the diamond analysis algorithm.
- Custom Emulation Environment – Simulated hardware behavior for testing.
Introduction
Yehuda’s diamond detection devices are widely used to differentiate natural diamonds from factory-grown ones. However, the proprietary nature of its software and algorithms limits transparency and external verification. Our team conducted a full reverse engineering process to extract, emulate, and document its detection methodology.
Project Overview
Our reverse engineering project involved:
- Extracting the Node.js-based software from the Raspberry Pi device.
- Running the software in a controlled emulation environment.
- Reproducing and analyzing the algorithm used for diamond classification.
- Documenting the internal methodology for further research and validation.
Implementation
1. Extracting the Device’s Software
- Accessed the Raspberry Pi storage to retrieve firmware and application files.
- Decrypted and analyzed the Node.js backend, identifying key logic components.
- Investigated dependencies, system calls, and embedded hardware interactions.
2. Emulating the Software Locally
- Created a controlled emulation environment that simulated the Raspberry Pi.
- Replicated sensor inputs and photo data to observe software responses.
- Debugged internal logic to understand the image-processing workflow.
3. Reconstructing the Detection Algorithm
- Analyzed the computer vision techniques used for diamond classification.
- Examined how the system processed images under different lighting spectrums.
- Documented the decision-making process for detecting natural vs. factory-grown diamonds.
Results & Benefits
- Successfully emulated Yehuda’s detection software outside of its hardware.
- Reproduced and documented the proprietary algorithm for analysis.
- Enabled further research and validation of the diamond classification method.
- Provided transparency into an otherwise closed-source detection process.
Conclusion
This reverse engineering project demonstrates our ability to extract, analyze, and document complex embedded systems. By uncovering Yehuda’s diamond detection algorithm, we enabled greater understanding, verification, and potential enhancements to diamond classification technology.
Looking for professional reverse engineering expertise? Contact GoodGuySoft today!