defakepy 0.1.3

A powerful open source library for detecting deepfakes and AI-generated content.

🛡️ Defakepy: Open Source Deepfake & AI Detection Library

Defakepy is a powerful open-source forensic suite designed to detect AI-generated content across text, audio, and video. It provides a deterministic and statistical "Trust Score" to help verify digital reality.

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✨ Key Features

• Text Forensics: Analyzes Perplexity and Burstiness to detect LLM-generated prose (GPT-4, Llama 3, Claude 3.5).
• Video Biological Tells: Uses Computer Vision to track Eye Aspect Ratio (EAR) for unnatural blinking patterns.
• Audio Spectral Analysis: Detects "robotic" frequency signatures in cloned voices using Mel-Frequency Cepstral Coefficients (MFCCs).
• C2PA Metadata: Native support for reading digital provenance signatures and manifests.
• Lazy Loading: High-performance CLI that only loads heavy ML models on demand.

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🚀 Quick Start

Installation

Install the core library via pip:

pip install defakepy

To include support for C2PA provenance and digital signatures (requires ~90MB download):

pip install "defakepy[provenance]"

To include support for Video/Vision analysis (requires dlib and CMake on Windows):

pip install "defakepy[vision]"

🛠️ Troubleshooting

Installation Timeout (ReadTimeoutError)

If you encounter a ReadTimeoutError during installation, it's usually due to a slow network connection while downloading large dependencies (like torch or c2pa-python). You can increase the timeout limit:

pip install --default-timeout=1000 defakepy

dlib Installation Failure (Windows)

If installing defakepy[vision] fails while building dlib, it's likely because CMake is missing.

1. Download CMake from cmake.org.
2. Run the installer and ensure you select "Add CMake to the system PATH".
3. Restart your terminal and try again.

Basic Usage (CLI)

Scan any file directly from your terminal:

defakepy-scan --input suspicious_video.mp4

Python API

Integrate Defakepy into your own application:

from defakepy import ForensicScanner

scanner = ForensicScanner()
report = scanner.scan_file("document.pdf")

print(f"Trust Score: {report['trust_score']}/100")

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📊 How it Works

Defakepy uses an Ensemble Approach:

1. Statistical Layer: Checks for patterns AI cannot easily hide (rhythm, entropy).
2. Biological Layer: Checks for human-specific involuntary movements (blinking).
3. Cryptographic Layer: Verifies digital watermarks and C2PA signatures.

⚖️ Legal & Ethical Disclaimer: Detection is probabilistic, not absolute. Defakepy is a tool to assist human verification, not replace it.

🤝 Contributing: We welcome contributions! Please see CONTRIBUTING.md for details.

📄 License: Distributed under the MIT License. See LICENSE for more information.