NVD CVE Database Explorer

Overview

NVD CVE Database Explorer is a powerful web application for managing, analyzing, and visualizing security vulnerabilities from the National Vulnerability Database (NVD). The application provides a user-friendly interface for security experts to assess vulnerabilities and identify risks in digital environments.

Key Features

• Intuitive Search Interface: Quick search for CVE IDs, vendors, products, or keywords
• Comprehensive Data Visualization: Graphical representation of severity distributions and temporal trends
• Local Database: SQLite database for offline access to CVE information
• Automatic Updates: Regular synchronization with official NVD feeds
• Detailed Vulnerability Analysis: Comprehensive information on vulnerabilities with CVSS ratings
• Vendor-specific Analyses: Deep insights into vulnerability patterns of specific vendors
• REST API: Programmatic access options for integrations with other tools
• Category-based Filtering: Focused search for specific vulnerability types
• Monthly Summaries: Overview of vulnerability trends over time

Installation

# Clone repository
git clone https://github.com/jensbecker-dev/nvd-cve-database-explorer.git
cd nvd-cve-database-explorer

# Install dependencies
pip install -r requirements.txt

Usage

Web Interface

Start the Flask application and access via browser:

python app.py

Then open your browser and navigate to http://localhost:8080

API Access

The application provides RESTful API endpoints:

GET /api/cve/<cve_id> - Retrieve details about a specific CVE
GET /db_status - Check database status

Programmatic Access

You can also use the NVDApi module directly in your Python code:

from modules.nvdapi import NVDApi

# Initialize API client
nvd = NVDApi()

# Search for a specific CVE
cve_details = nvd.get_cve("CVE-2021-44228")

# Search for vulnerabilities for specific products
apache_vulns = nvd.search_by_product("apache", "log4j")

Vendor Analyses

Detailed insights into the security situation of specific vendors:

• Top vendors by number of vulnerabilities
• Severity distribution per vendor
• Product-specific analyses
• Temporal development of vulnerabilities

Category-based Views

Focused analyses of specific vulnerability types:

• SQL Injection
• Remote Code Execution
• Cross-Site Scripting
• Authentication Bypass
• Denial of Service
• Information Disclosure
• Buffer Overflow

Monthly Overviews

Comprehensive time series analyses:

• Monthly distribution of new CVEs
• Severity development over time
• Identification of outliers and trends

Dependencies

• Flask 2.3.3+
• SQLAlchemy 2.0.23+
• Requests 2.31.0+
• Python 3.8+

For complete list see requirements.txt

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgements

• National Vulnerability Database

Disclaimer

This tool is intended for legitimate security research and penetration testing with appropriate authorization. The authors assume no responsibility for misuse or damage caused by this program.