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--- |
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license: mit |
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tags: |
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- cybersecurity |
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- threat-detection |
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- malware |
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- phishing |
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- anomaly-detection |
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library_name: sklearn |
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pipeline_tag: tabular-classification |
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--- |
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# CyberForge AI Security Models |
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Production-ready machine learning models for real-time cybersecurity threat detection. |
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## Models Included |
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| Model | Task | Accuracy | F1 Score | Inference | |
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|-------|------|----------|----------|-----------| |
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| phishing_detection | Detect phishing URLs | 98.9% | 0.989 | 0.02ms | |
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| malware_detection | Identify malware | 99.8% | 0.998 | 0.001ms | |
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| anomaly_detection | Network anomalies | 99.9% | 0.999 | 0.007ms | |
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| web_attack_detection | Web attacks | 100% | 1.000 | 0.03ms | |
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## Quick Start |
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```python |
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from cyberforge_inference import CyberForgePredictor |
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# Initialize |
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predictor = CyberForgePredictor() |
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# Predict |
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result = predictor.predict("phishing_detection", features) |
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print(f"Threat: {result['prediction']}, Confidence: {result['confidence']}") |
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``` |
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## API Usage |
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```python |
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import requests |
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response = requests.post( |
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"https://your-api-endpoint/predict", |
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json={ |
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"model": "phishing_detection", |
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"features": {...} |
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} |
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) |
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``` |
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## Features |
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- **Real-time inference** < 1ms per prediction |
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- **Multiple threat types**: Phishing, Malware, Anomalies, Web Attacks |
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- **Production-ready**: Optimized for high-throughput |
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- **Backend integration**: Compatible with Node.js/Python backends |
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## Training Data |
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Models trained on 50,000+ samples from: |
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- [CyberForge Datasets](https://huggingface.co/datasets/Che237/cyberforge-datasets) |
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## License |
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MIT License - Free for commercial and personal use. |
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