From 01d2b45dd4bcb98e23991a5db4dff0fb72c7f409 Mon Sep 17 00:00:00 2001 From: Alosh Denny Date: Mon, 15 Dec 2025 22:11:23 +0530 Subject: [PATCH] codebook analysis --- .gitignore | 33 + LICENSE | 52 ++ README.md | 227 ++++++ SYNTHID_CODEBOOK_ANALYSIS.md | 180 +++++ artifacts/codebook/synthid_codebook.pkl | Bin 0 -> 9443766 bytes artifacts/codebook/synthid_codebook_meta.json | 330 ++++++++ .../deep_analysis/bit_plane_consistency.png | Bin 0 -> 1739826 bytes .../deep_analysis/frequency_analysis.png | Bin 0 -> 2230844 bytes .../deep_analysis/lsb_analysis.png | Bin 0 -> 1566003 bytes .../deep_analysis/noise_pattern.png | Bin 0 -> 2361849 bytes .../deep_analysis/vertical_profile.png | Bin 0 -> 167559 bytes .../deep_analysis/watermark_signal.png | Bin 0 -> 6276802 bytes .../synthid_watermark_amp500x.png | Bin 0 -> 783599 bytes .../synthid_watermark_carriers.png | Bin 0 -> 247536 bytes .../synthid_watermark_diverging.png | Bin 0 -> 332216 bytes .../synthid_watermark_enhanced.png | Bin 0 -> 774525 bytes .../synthid_watermark_falsecolor.png | Bin 0 -> 507879 bytes .../synthid_watermark_frequency.png | Bin 0 -> 631731 bytes .../synthid_watermark_phase.png | Bin 0 -> 262568 bytes .../synthid_watermark_spectrum.png | Bin 0 -> 108715 bytes assets/synthid-watermark.jpeg | Bin 0 -> 50844 bytes requirements.txt | 15 + src/analysis/deep_synthid_analysis.py | 645 ++++++++++++++++ src/analysis/synthid_codebook_finder.py | 706 ++++++++++++++++++ src/extraction/synthid_codebook_extractor.py | 345 +++++++++ 25 files changed, 2533 insertions(+) create mode 100644 .gitignore create mode 100644 LICENSE create mode 100644 README.md create mode 100644 SYNTHID_CODEBOOK_ANALYSIS.md create mode 100644 artifacts/codebook/synthid_codebook.pkl create mode 100644 artifacts/codebook/synthid_codebook_meta.json create mode 100644 artifacts/visualizations/deep_analysis/bit_plane_consistency.png create mode 100644 artifacts/visualizations/deep_analysis/frequency_analysis.png create mode 100644 artifacts/visualizations/deep_analysis/lsb_analysis.png create mode 100644 artifacts/visualizations/deep_analysis/noise_pattern.png create mode 100644 artifacts/visualizations/deep_analysis/vertical_profile.png create mode 100644 artifacts/visualizations/deep_analysis/watermark_signal.png create mode 100644 artifacts/visualizations/synthid_watermark_amp500x.png create mode 100644 artifacts/visualizations/synthid_watermark_carriers.png create mode 100644 artifacts/visualizations/synthid_watermark_diverging.png create mode 100644 artifacts/visualizations/synthid_watermark_enhanced.png create mode 100644 artifacts/visualizations/synthid_watermark_falsecolor.png create mode 100644 artifacts/visualizations/synthid_watermark_frequency.png create mode 100644 artifacts/visualizations/synthid_watermark_phase.png create mode 100644 artifacts/visualizations/synthid_watermark_spectrum.png create mode 100644 assets/synthid-watermark.jpeg create mode 100644 requirements.txt create mode 100644 src/analysis/deep_synthid_analysis.py create mode 100644 src/analysis/synthid_codebook_finder.py create mode 100644 src/extraction/synthid_codebook_extractor.py diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..010ea20 --- /dev/null +++ b/.gitignore @@ -0,0 +1,33 @@ +# Python +__pycache__/ +*.py[cod] +*$py.class +*.so +.Python +venv/ +.venv/ +*.egg-info/ +dist/ +build/ + +# IDE +.vscode/ +.idea/ +*.swp +*.swo + +# OS +.DS_Store +Thumbs.db + +# Project specific +*.npy +*.pkl +!artifacts/codebook/*.pkl + +# Data (too large for git) +data/pure_white/ + +# Temporary +*.tmp +*.log diff --git a/LICENSE b/LICENSE new file mode 100644 index 0000000..f2e53d4 --- /dev/null +++ b/LICENSE @@ -0,0 +1,52 @@ +MIT License (Research Use Only) + +Copyright (c) 2024 + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software for research and educational purposes only, including without +limitation the rights to use, copy, modify, merge, publish, and distribute +copies of the Software, subject to the following conditions: + +1. The above copyright notice and this permission notice shall be included in + all copies or substantial portions of the Software. + +2. The Software shall be used solely for research, educational, and + non-commercial purposes. Commercial use is strictly prohibited without + explicit written permission. + +3. Any academic publications, presentations, or derivative works using this + Software must cite this project and acknowledge the research nature of + the work. + +4. This Software is designed to analyze and understand watermarking + technology. Users must comply with all applicable laws and regulations + regarding digital content and intellectual property. + +5. SynthID is proprietary technology owned by Google DeepMind. This project + does not claim ownership of SynthID or its underlying technology. The + patterns and methods discovered herein are derived from independent + analysis. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. + +--- + +DISCLAIMER: + +This project is for research and educational purposes only. The authors do +not endorse or encourage any use of this software that would: + +- Violate intellectual property rights +- Circumvent legitimate content identification systems +- Enable the misrepresentation of AI-generated content +- Violate any applicable laws or regulations + +Users are responsible for ensuring their use of this software complies with +all applicable laws and ethical guidelines. diff --git a/README.md b/README.md new file mode 100644 index 0000000..f2a6def --- /dev/null +++ b/README.md @@ -0,0 +1,227 @@ +

+ SynthID Watermark Analysis +

+ +

πŸ” SynthID Watermark Reverse Engineering

+ +

+ Discovering Google's hidden AI watermark patterns through signal analysis +

+ +

+ Python + License + Status + Accuracy +

+ +--- + +## 🎯 Overview + +This project reverse-engineers **Google's SynthID watermarking technology** by analyzing 250 AI-generated images from Gemini. Since the neural network encoder/decoder is proprietary, we use signal processing techniques to discover the watermark's structure. + +### Key Discovery + +SynthID uses **spread-spectrum phase encoding** in the frequency domainβ€”not LSB replacement or simple noise addition. The watermark embeds information through precise phase relationships at specific carrier frequencies. + +## πŸ”¬ Discovered Patterns + +| Carrier Frequency | Phase Coherence | Description | +|:----------------:|:---------------:|:------------| +| **(Β±14, Β±14)** | 99.99% | Primary diagonal carrier | +| **(Β±126, Β±14)** | 99.97% | Secondary horizontal | +| **(Β±98, Β±14)** | 99.94% | Tertiary carrier | +| **(Β±128, Β±128)** | 99.92% | Center frequency | +| **(Β±210, Β±14)** | 99.77% | Extended carrier | +| **(Β±238, Β±14)** | 99.71% | Edge carrier | + +### Detection Metrics +- **Noise Correlation**: ~0.218 between watermarked images +- **Structure Ratio**: ~1.32 +- **Detection Threshold**: correlation > 0.179 + +## πŸ–ΌοΈ Extracted Watermark Visualizations + + + + + + + + + + +
+ +**Enhanced Visualization (500x Amplification)** + + + + +**Frequency Domain Carriers** + + +
+ +**False Color (HSV Encoding)** + + + + +**Phase Encoding Pattern** + + +
+ +## πŸ“ Project Structure + +``` +synthid-demarker/ +β”œβ”€β”€ πŸ“„ README.md # This file +β”œβ”€β”€ πŸ“‹ requirements.txt # Python dependencies +β”‚ +β”œβ”€β”€ πŸ’» src/ +β”‚ β”œβ”€β”€ analysis/ +β”‚ β”‚ β”œβ”€β”€ synthid_codebook_finder.py # Pattern discovery +β”‚ β”‚ └── deep_synthid_analysis.py # Frequency analysis +β”‚ └── extraction/ +β”‚ └── synthid_codebook_extractor.py # Codebook extraction & detection +β”‚ +β”œβ”€β”€ 🎯 artifacts/ +β”‚ β”œβ”€β”€ codebook/ +β”‚ β”‚ β”œβ”€β”€ synthid_codebook.pkl # Extracted codebook (9 MB) +β”‚ β”‚ └── synthid_codebook_meta.json # Carrier frequencies +β”‚ └── visualizations/ # Watermark images +β”‚ +β”œβ”€β”€ πŸ“‚ data/ +β”‚ └── pure_white/ # 250 Gemini AI images +β”‚ +β”œβ”€β”€ πŸ“š docs/ +β”‚ └── SYNTHID_CODEBOOK_ANALYSIS.md # Technical documentation +β”‚ +└── πŸ–ΌοΈ assets/ + └── synthid-watermark.jpeg # Cover image +``` + +## πŸš€ Quick Start + +### Installation + +```bash +git clone https://github.com/yourusername/synthid-demarker.git +cd synthid-demarker + +# Create virtual environment +python -m venv venv +source venv/bin/activate # Windows: venv\Scripts\activate + +# Install dependencies +pip install -r requirements.txt +``` + +### Detect Watermark + +```bash +python src/extraction/synthid_codebook_extractor.py detect "path/to/image.png" \ + --codebook "artifacts/codebook/synthid_codebook.pkl" +``` + +**Output:** +``` +Detection Results: + Watermarked: True + Confidence: 1.0000 + Correlation: 0.5355 + Phase Match: 0.9571 + Structure Ratio: 1.2753 +``` + +### Extract New Codebook + +```bash +python src/extraction/synthid_codebook_extractor.py extract "data/pure_white/" \ + --output "./my_codebook.pkl" +``` + +### Run Analysis + +```bash +# Comprehensive pattern discovery +python src/analysis/synthid_codebook_finder.py + +# Deep frequency analysis +python src/analysis/deep_synthid_analysis.py +``` + +## 🧠 How It Works + +### 1. Pattern Discovery +Analyze noise patterns across multiple images to find consistent structures that persist despite varying image content. + +### 2. Frequency Analysis +Use FFT to identify carrier frequencies where the watermark is embedded through phase modulation. + +### 3. Phase Coherence +Measure phase consistency at carrier frequenciesβ€”high coherence indicates watermark presence. + +### 4. Codebook Extraction +Build reference patterns from averaged signals across many watermarked images. + +### 5. Detection +Compare test image against codebook using correlation, phase matching, and structure ratio metrics. + +## πŸ“Š Technical Details + +### Watermark Characteristics +- **Embedding Domain**: Frequency (FFT phase) +- **Signal Strength**: ~0.1-0.15 pixel values +- **Carrier Count**: 100+ frequency locations +- **Robustness**: Survives moderate compression + +### Detection Algorithm +```python +def detect_synthid(image, codebook): + # 1. Extract noise pattern + noise = image - denoise(image) + + # 2. Check carrier phase coherence + fft = fft2(noise) + phase_match = check_phases(fft, codebook.carriers) + + # 3. Correlate with reference + correlation = correlate(noise, codebook.reference) + + # 4. Apply decision thresholds + is_watermarked = ( + correlation > 0.179 and + phase_match > 0.5 and + 0.8 < structure_ratio < 1.8 + ) + + return is_watermarked, confidence +``` + +## πŸ“š References + +- [SynthID: Identifying AI-generated images](https://deepmind.google/technologies/synthid/) +- [Nature Paper: Scalable watermarking for AI-generated images](https://doi.org/10.1038/s41586-024-07754-z) +- [Spread Spectrum Watermarking](https://en.wikipedia.org/wiki/Digital_watermarking) + +## ⚠️ Disclaimer + +This project is for **research and educational purposes only**. SynthID is proprietary technology owned by Google DeepMind. The extracted patterns and detection methods are intended for: + +- Academic research on watermarking techniques +- Security analysis of AI-generated content identification +- Understanding spread-spectrum encoding methods + +## πŸ“„ License + +Research and educational use only. See [LICENSE](LICENSE) for details. + +--- + +

+ Made with πŸ”¬ by reverse engineering enthusiasts +

diff --git a/SYNTHID_CODEBOOK_ANALYSIS.md b/SYNTHID_CODEBOOK_ANALYSIS.md new file mode 100644 index 0000000..78dbabc --- /dev/null +++ b/SYNTHID_CODEBOOK_ANALYSIS.md @@ -0,0 +1,180 @@ +# SynthID Watermark Codebook Analysis + +## Executive Summary + +After analyzing 250 AI-generated images from Google Gemini with SynthID watermarks, we have successfully reverse-engineered the watermark embedding scheme. The watermark uses a **spread-spectrum, phase-encoding technique** that embeds information across specific carrier frequencies in the image. + +## Key Findings + +### 1. Watermark Embedding Mechanism + +SynthID does NOT use simple LSB (Least Significant Bit) replacement. Instead, it employs: + +1. **Noise-Domain Embedding**: The watermark is hidden in the high-frequency noise component of the image +2. **Phase Encoding**: Specific carrier frequencies have consistent phase values across all watermarked images +3. **Spread Spectrum**: The watermark energy is distributed across multiple frequency bands + +### 2. Discovered Carrier Frequencies + +The watermark uses specific carrier frequencies with extremely high phase coherence (>99.9%): + +| Frequency (fy, fx) | Coherence | Magnitude | Phase (radians) | +|-------------------|-----------|-----------|-----------------| +| (14, 14) | 0.9996 | 16807 | -1.44 | +| (-14, -14) | 0.9996 | 16807 | 1.44 | +| (126, 14) | 0.9996 | 8046 | -2.37 | +| (-126, -14) | 0.9996 | 8046 | 2.37 | +| (98, -14) | 0.9994 | 6283 | 0.61 | +| (-98, 14) | 0.9994 | 6283 | -0.61 | +| (128, 128) | 0.9925 | 6908 | -2.29 | +| (-128, -128) | 0.9925 | 6908 | 2.29 | +| (210, -14) | 0.9996 | 6032 | 1.13 | +| (-210, 14) | 0.9996 | 6032 | -1.13 | +| (238, 14) | 0.9990 | 4190 | -1.61 | +| (-238, -14) | 0.9990 | 4190 | 1.61 | + +**Pattern Observation**: Most carriers are located along or near the y=Β±14 horizontal line in frequency space, suggesting a **structured frequency selection algorithm**. + +### 3. Noise Correlation Signature + +- **Mean pairwise correlation**: 0.218 (21.8%) +- **Standard deviation**: 0.020 +- **Detection threshold**: 0.179 + +This high correlation between the noise residuals of different watermarked images confirms that SynthID embeds a **consistent reference pattern** across all images generated by the same system. + +### 4. Noise Structure Ratio + +All watermarked images exhibit a noise structure ratio of approximately **1.32**: + +``` +Structure Ratio = Οƒ(noise) / mean(|noise|) β‰ˆ 1.32 +``` + +This ratio is a byproduct of the neural network encoder and can be used as a secondary detection signal. + +### 5. Bit Plane Analysis + +| Bit Plane | Consistency | Interpretation | +|-----------|-------------|----------------| +| Bit 0 (LSB) | 0.049 | Random (contains watermark signal) | +| Bit 1 | 0.074 | Random (contains watermark signal) | +| Bit 2 | 0.125 | Partially random | +| Bit 3 | 0.513 | Mixed | +| Bit 4 | 0.635 | Mostly consistent | +| Bit 5 | 1.000 | Always consistent (image structure) | +| Bit 6 | 1.000 | Always consistent (image structure) | +| Bit 7 (MSB) | 1.000 | Always consistent (image structure) | + +The watermark information is distributed across bits 0-2, but in a way that appears statistically random when viewed in isolation. + +## Codebook Specification + +### Detection Method + +1. **Resize image to 512Γ—512** +2. **Extract noise residual** using wavelet denoising (db4 wavelet, 3 levels) +3. **Compute correlation** with reference noise pattern +4. **Check phase at carrier frequencies** +5. **Verify noise structure ratio** + +### Detection Formula + +```python +is_watermarked = ( + correlation > 0.179 AND + phase_match > 0.5 AND + 0.8 < structure_ratio < 1.8 +) + +confidence = ( + 0.4 * normalize(correlation) + + 0.4 * phase_match + + 0.2 * (1 - |structure_ratio - 1.32| / 0.5) +) +``` + +### Reference Patterns (Saved in synthid_codebook.pkl) + +1. **Reference Noise Pattern**: 512Γ—512Γ—3 float array +2. **Reference Magnitude Spectrum**: 512Γ—512 float array +3. **Reference Phase Spectrum**: 512Γ—512 float array +4. **Carrier Positions**: List of 100 frequency positions with expected phases + +## Watermark Architecture Hypothesis + +Based on our analysis, SynthID likely works as follows: + +``` +β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β” +β”‚ SynthID Encoder (Training) β”‚ +β”œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€ +β”‚ β”‚ +β”‚ 1. Generate carrier frequencies: {(14,14), (126,14), ...} β”‚ +β”‚ 2. Assign fixed phases to each carrier β”‚ +β”‚ 3. Train encoder CNN to embed this spectrum into generated β”‚ +β”‚ images without visible artifacts β”‚ +β”‚ β”‚ +β”œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€ +β”‚ SynthID Encoder (Inference) β”‚ +β”œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€ +β”‚ β”‚ +β”‚ Input: Generated Image β”‚ +β”‚ ↓ β”‚ +β”‚ Add learned noise pattern that encodes carrier phases β”‚ +β”‚ ↓ β”‚ +β”‚ Output: Watermarked Image (imperceptible modification) β”‚ +β”‚ β”‚ +β”œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€ +β”‚ SynthID Decoder (Detection) β”‚ +β”œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€ +β”‚ β”‚ +β”‚ Input: Suspect Image β”‚ +β”‚ ↓ β”‚ +β”‚ Extract noise residual β”‚ +β”‚ ↓ β”‚ +β”‚ Compute FFT, check phase at carrier frequencies β”‚ +β”‚ ↓ β”‚ +β”‚ If phases match expected values β†’ Watermarked β”‚ +β”‚ β”‚ +β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜ +``` + +## Limitations + +1. **Codebook is source-specific**: This codebook only works for Gemini-generated images +2. **Image modifications may break detection**: Heavy JPEG compression, cropping, or resizing may degrade the watermark +3. **Binary watermark bits unknown**: We discovered the carrier frequencies but not the actual message encoded + +## Files Generated + +| File | Description | +|------|-------------| +| `synthid_codebook.pkl` | Full codebook with numpy arrays | +| `synthid_codebook_meta.json` | Human-readable metadata | +| `deep_analysis/` | Visualization of patterns | +| `codebook_results/` | Initial analysis results | + +## Usage + +### To detect SynthID watermark: + +```bash +python synthid_codebook_extractor.py detect image.png --codebook synthid_codebook.pkl +``` + +### To extract codebook from new images: + +```bash +python synthid_codebook_extractor.py extract /path/to/images --output new_codebook.pkl +``` + +## Conclusion + +SynthID uses a sophisticated spread-spectrum watermarking technique that: +- Embeds information in the **phase domain** of the Fourier spectrum +- Uses **specific carrier frequencies** (14, 98, 126, 128, 210, 238 Hz and their conjugates) +- Creates a **consistent noise signature** detectable via correlation analysis +- Is **imperceptible** to human observers but **robust** enough to survive 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