Jashwanth33/FINALYEAR-PROJECT

# VULNSecure - 混合漏洞检测系统 [](https://python.org) [](https://flask.palletsprojects.com/) [](https://www.tensorflow.org/) [](LICENSE) [](http://makeapullrequest.com) ## 架构 `mermaid graph TB subgraph "Frontend" UI[React Dashboard] API_Client[API Client] end ``` subgraph "Backend Services" Flask[Flask Server] Scanner[Scanner Engine] ML[ML Risk Analyzer] DarkWeb[Dark Web Monitor] end subgraph "Data Layer" MongoDB[(MongoDB)] Redis[(Redis Cache)] CVE_DB[(CVE Database)] end subgraph "External APIs" OWASP[OWASP API] Shodan[Shodan API] end UI --> Flask API_Client --> Flask Flask --> Scanner Flask --> ML Flask --> DarkWeb Scanner --> CVE_DB Scanner --> OWASP Scanner --> Shodan ML --> MongoDB DarkWeb --> MongoDB Flask --> Redis ``` ` ## 系统流程 `mermaid flowchart TD A[User Submits Target URL] --> B{Input Validation} B -->|Invalid| C[Return Error] B -->|Valid| D[Initialize Scanner] D --> E[Port Scanning] D --> F[Service Detection] D --> G[Vulnerability Check] E --> H[Aggregate Results] F --> H G --> H H --> I[ML Risk Assessment] I --> J{Risk Level} J -->|Critical| K[Immediate Alert] J -->|High| L[Priority Report] J -->|Medium| M[Standard Report] J -->|Low| N[Info Report] K --> O[Generate Report] L --> O M --> O N --> O O --> P[Send Notification] O --> Q[Store in Database] ` ## 项目结构 ` FINALYEAR-PROJECT/ ├── app.py # Main Flask application entry point ├── config.py # Configuration settings ├── requirements.txt # Python dependencies │ ├── scanner/ # Vulnerability scanning modules │ ├── __init__.py │ ├── web_scanner.py # Web application vulnerability scanner │ ├── network_scanner.py # Network port & service scanner │ ├── port_scanner.py # TCP/UDP port scanning │ ├── ssl_scanner.py # SSL/TLS vulnerability detection │ └── cve_checker.py # CVE database lookup │ ├── ml_model/ # Machine learning components │ ├── __init__.py │ ├── trainer.py # Model training pipeline │ ├── predictor.py # Risk prediction engine │ ├── feature_extractor.py # Feature extraction from scan results │ └── models/ # Saved ML models │ ├── risk_classifier.pkl │ └── severity_model.pkl │ ├── dark_web/ # Dark web monitoring │ ├── __init__.py │ ├── monitor.py # Dark web crawler │ ├── credential_checker.py # Leaked credential detection │ └── alert_system.py # Alert notification system │ ├── reports/ # Report generation │ ├── __init__.py │ ├── generator.py # PDF/HTML report generator │ ├── templates/ # Report templates │ │ ├── executive_summary.html │ │ └── technical_detail.html │ └── exports/ # Generated reports │ ├── api/ # REST API endpoints │ ├── __init__.py │ ├── routes.py # API route definitions │ ├── auth.py # Authentication endpoints │ └── validators.py # Input validation │ ├── templates/ # Frontend HTML templates │ ├── base.html │ ├── dashboard.html │ ├── scan_results.html │ └── reports.html │ ├── static/ # Static assets │ ├── css/ │ │ └── style.css │ ├── js/ │ │ ├── dashboard.js │ │ └── charts.js │ └── images/ │ ├── tests/ # Test suite │ ├── test_scanner.py │ ├── test_ml_model.py │ └── test_api.py │ ├── docs/ # Documentation │ ├── architecture.md │ ├── api_reference.md │ └── deployment.md │ ├── docker/ # Docker configuration │ ├── Dockerfile │ └── docker-compose.yml │ └── scripts/ # Utility scripts ├── setup.sh └── train_model.py ` ## 功能 | 功能 | 描述 | 状态 | |---------|-------------|--------| | Web 漏洞扫描 | OWASP Top 10 检测 | 完成 | | 端口扫描 | TCP/UDP 端口发现 | 完成 | | SSL/TLS 分析 | 证书和协议检查 | 完成 | | ML 风险评估 | AI 驱动的威胁评分 | 完成 | | 暗网监控 | 凭据泄露检测 | 完成 | | 自动化报告 | 生成 PDF/HTML | 完成 | | 实时仪表盘 | 实时扫描监控 | 完成 | | API 集成 | RESTful API endpoint | 完成 | ## 技术栈 ` ┌─────────────────────────────────────────────────────────┐ │ TECH STACK │ ├─────────────────┬─────────────────┬─────────────────────┤ │ Frontend │ Backend │ Database │ ├─────────────────┼─────────────────┼─────────────────────┤ │ React.js │ Python │ MongoDB │ │ HTML5/CSS3 │ Flask │ Redis │ │ Chart.js │ Celery │ SQLite (dev) │ │ Bootstrap 5 │ Gunicorn │ │ ├─────────────────┴─────────────────┴─────────────────────┤ │ ML & Security │ ├─────────────────┬─────────────────┬─────────────────────┤ │ TensorFlow │ scikit-learn │ pandas │ │ NumPy │ OWASP ZAP │ Nmap │ │ Shodan API │ CVE Database │ requests │ └─────────────────┴─────────────────┴─────────────────────┘ ` ## 安装 `ash # 克隆 repository git clone https://github.com/Jashwanth33/FINALYEAR-PROJECT.git cd FINALYEAR-PROJECT # 创建虚拟环境 python -m venv venv source venv/bin/activate # Linux/Mac # venv\Scripts\activate # Windows # 安装依赖项 pip install -r requirements.txt # 设置环境变量 cp .env.example .env # 使用你的 API keys 编辑 .env # 初始化数据库 python scripts/setup.py # 运行应用程序 python app.py ` ## API Endpoint | 方法 | Endpoint | 描述 | |--------|----------|-------------| | POST | /api/v1/scan | 开始新的漏洞扫描 | | GET | /api/v1/scan/:id | 获取扫描状态 | | GET | /api/v1/scan/:id/results | 获取扫描结果 | | GET | /api/v1/reports | 列出所有报告 | | POST | /api/v1/reports/generate | 生成报告 | | GET | /api/v1/dashboard/stats | 仪表盘统计信息 | ## 使用示例 `python from scanner import WebScanner from ml_model import RiskPredictor # 初始化 scanner scanner = WebScanner(target="https://example.com") # 运行 scan results = scanner.scan() # 获取 ML risk assessment predictor = RiskPredictor() risk_score = predictor.predict(results) print(f"Risk Score: {risk_score}/10") print(f"Vulnerabilities Found: {len(results)}") ` ## 许可证 基于 MIT 许可证分发。查看 LICENSE 获取更多信息。 ## 作者 **Jashwanth** - [GitHub](https://github.com/Jashwanth33) | [LinkedIn](https://linkedin.com/in/jashwanth)

标签：Apex, CTI, Flask, Python, 威胁情报, 密码管理, 开发者工具, 插件系统, 搜索引擎查询, 无后门, 暗网监控, 机器学习, 自定义脚本, 请求拦截, 逆向工具