| --- |
| model_name: Canstralian/CySec_Known_Exploit_Analyzer |
| tags: |
| - cybersecurity |
| - exploit-detection |
| - network-security |
| - machine-learning |
| license: mit |
| datasets: |
| - cysec-known-exploit-dataset |
| metrics: |
| - accuracy |
| - f1 |
| - precision |
| - recall |
| library_name: transformers |
| language: |
| - en |
| model_type: neural-network |
| base_model: |
| - replit/replit-code-v1_5-3b |
| --- |
| |
| # CySec Known Exploit Analyzer |
|
|
| ## Overview |
|
|
| - The CySec Known Exploit Analyzer is developed to: |
| - Detect and assess known cybersecurity exploits. |
| - Identify vulnerabilities and exploit attempts in network traffic. |
| - Provide real-time threat detection and analysis. |
|
|
| ## Model Details |
|
|
| - **Type:** Neural Network |
| - **Input:** |
| - Network traffic logs |
| - Exploit payloads |
| - Related security information |
| - **Output:** |
| - Classification of known exploits |
| - Anomaly detection |
| - **Training Data:** |
| - Based on the [cysec-known-exploit-dataset](#datasets) |
| - Includes real-world exploit samples and traffic data. |
| - **Architecture:** |
| - Custom Neural Network with attention layers to identify exploit signatures in packet data. |
| - **Metrics:** |
| - Accuracy |
| - F1 Score |
| - Precision |
| - Recall |
|
|
| ## Getting Started |
|
|
| **Installation** |
|
|
| 1. Clone the repository: `git clone https://huggingface.co/Canstralian/CySec_Known_Exploit_Analyzer` |
| 2. Navigate to the directory: `cd CySec_Known_Exploit_Analyzer` |
| 3. Install the necessary dependencies: `pip install -r requirements.txt` |
|
|
| **Usage** |
|
|
| - To analyze a network traffic log: `python analyze_exploit.py --input [input-file]` |
| - **Example Command:** `python analyze_exploit.py --input data/sample_log.csv` |
|
|
| ## Model Inference |
|
|
| - **Input:** Network traffic logs in CSV format |
| - **Output:** Classification of potential exploits with confidence scores |
|
|
| ## License |
|
|
| - This project is licensed under the [MIT License](LICENSE.md). |
|
|
| ## Datasets |
|
|
| - The model is trained on the cysec-known-exploit-dataset, featuring exploit data from actual network traffic. |
|
|
| ## Contributing |
|
|
| - Contributions are encouraged! Please refer to CONTRIBUTING.md for details. |
|
|
| ## Contact |
|
|
| - For inquiries or feedback, please open an issue or contact [distortedprojection@gmail.com](mailto:distortedprojection@gmail.com). |
