Discovering, detecting, and surgically removing Google's AI watermark

Reverse-Engineering SynthID

Discovering, detecting, and surgically removing Google's AI watermark through spectral analysis

Overview

This project reverse-engineers Google's SynthID watermarking system - the invisible watermark embedded into every image generated by Google Gemini. Using only signal processing and spectral analysis (no access to the proprietary encoder/decoder), we:

Discovered the watermark's resolution-dependent carrier frequency structure Built a detector that identifies SynthID watermarks with 90% accuracy Developed a multi-resolution spectral bypass (V3) that achieves 75% carrier energy drop, 91% phase coherence drop, and 43+ dB PSNR on any image resolution

🚨 Contributors Wanted: Help Expand the Codebook

We're actively collecting pure black and pure white images generated by Nano Banana Pro to improve multi-resolution watermark extraction.

If you can generate these:

Resolution: any (higher variety = better)

Content: fully black (#000000) or fully white (#FFFFFF)

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