defakepy 0.1.0

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 -e .

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.