| | --- |
| | 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). |
