This repository simulates a complete enterprise vulnerability management lifecycle from initial discovery through remediation tracking. It demonstrates practical vulnerability assessment, risk prioritization, and remediation planning skills using industry-standard tools and methodologies.

The simulation replicates realistic scenarios encountered in security operations centers, including vulnerability scanning, CVE mapping, CVSS scoring, remediation planning, and stakeholder reporting.

This project showcases proficiency in:

• Vulnerability scanning and assessment methodologies
• Risk-based vulnerability prioritization
• CVE database mapping and tracking
• Remediation planning and documentation
• Security metrics and reporting
• Python automation for vulnerability management
• Enterprise security operations workflows

Vulnerability scans are conducted using automated scanning tools to identify security weaknesses across the enterprise infrastructure. Scans cover multiple asset types including:

• Windows servers and workstations
• Linux servers
• Network devices (routers, firewalls, VPN appliances)
• Application servers
• Database servers

Each identified vulnerability is assessed for:

• CVSS base score (Common Vulnerability Scoring System)
• CVE identification (Common Vulnerabilities and Exposures)
• Exploit availability
• Asset criticality
• Business impact

Vulnerabilities are prioritized based on multiple factors:

• CVSS severity rating (Critical, High, Medium, Low)
• Existence of public exploits
• Asset exposure (internet-facing vs internal)
• Business criticality of affected systems
• Remediation complexity

Remediation activities are planned and tracked:

• Assignment to appropriate technical teams
• Target remediation dates based on severity
• Remediation verification procedures
• Exception handling for systems requiring extended timelines
• Compensating controls for vulnerabilities pending remediation

Comprehensive reporting for stakeholders:

• Executive summaries with risk metrics
• Technical remediation guidance
• Status tracking and trending
• Compliance reporting

Industry-leading vulnerability scanner used for comprehensive network and application vulnerability assessments. Nessus provides:

• Authenticated and unauthenticated scanning
• Plugin-based vulnerability detection
• Compliance checking
• Web application scanning
• Cloud infrastructure assessment

Open-source vulnerability scanner providing:

• Network vulnerability testing
• Comprehensive CVE coverage
• Regular vulnerability feed updates
• Flexible scanning configurations

Automation scripting for:

• Scan report parsing
• Priority list generation
• Risk metrics calculation
• Report generation
• Data transformation and analysis

Vulnerability-Management-Simulation/
├── scan-reports/
│   ├── nessus-basic-scan-2024-02.csv      # Basic vulnerability scan results
│   └── nessus-advanced-scan-2024-02.csv   # Advanced scan with exploit data
├── cve-mappings/
│   ├── vulnerability-tracking.csv          # CVE tracking database (CSV format)
│   └── vulnerability-tracking.json         # CVE tracking database (JSON format)
├── remediation-docs/
│   ├── critical-remediation-report.md      # Critical severity remediation plan
│   └── high-remediation-report.md          # High severity remediation plan
├── scripts/
│   ├── parse_scan_report.py                # Parse and summarize scan reports
│   ├── generate_priority_list.py           # Generate remediation priority lists
│   └── generate_risk_metrics.py            # Generate risk metrics reports
├── assets/
└── README.md

• Python 3.7 or higher
• No external dependencies required (uses Python standard library)

Parses vulnerability scan CSV files and generates summary statistics.

python scripts/parse_scan_report.py scan-reports/nessus-basic-scan-2024-02.csv

Optional: Filter by severity

python scripts/parse_scan_report.py scan-reports/nessus-basic-scan-2024-02.csv Critical

Output includes:

• Total vulnerability count
• Breakdown by severity level
• Top affected assets
• CVE listing

Creates a prioritized remediation list based on CVSS scores, exploit availability, and asset criticality.

python scripts/generate_priority_list.py cve-mappings/vulnerability-tracking.csv

Output includes:

• Ranked vulnerability list
• Priority scoring
• Detailed remediation guidance for top priorities
• Assignment tracking

Produces comprehensive risk metrics for management reporting.

python scripts/generate_risk_metrics.py cve-mappings/vulnerability-tracking.csv

Output includes:

• Executive summary with key metrics
• Vulnerability distribution by severity
• Remediation status breakdown
• CVSS score statistics
• Asset type vulnerability analysis
• Team workload distribution
• Risk-based recommendations

This project demonstrates comprehensive understanding of:

1. Risk-Based Prioritization: Not all vulnerabilities are equal. Prioritization must consider CVSS scores, exploit availability, asset criticality, and business impact.

2. Service Level Agreements: Different severity levels require different response times:

   • Critical: 24 hours
   • High: 7 days
   • Medium: 30 days
   • Low: 60 days

3. Stakeholder Communication: Effective vulnerability management requires clear communication with:

   • Executive leadership (risk and compliance focus)
   • Technical teams (detailed remediation guidance)
   • Compliance and audit teams (tracking and documentation)

4. Continuous Process: Vulnerability management is not a one-time activity but a continuous cycle of:

   • Regular scanning
   • Assessment and prioritization
   • Remediation planning and execution
   • Verification and validation
   • Metrics and reporting

5. Compensating Controls: When immediate remediation is not possible, compensating controls reduce risk:

   • Network segmentation
   • Additional monitoring and alerting
   • Access restrictions
   • Enhanced logging

• Vulnerability assessment methodologies
• CVE database research and mapping
• CVSS scoring interpretation
• Risk analysis and prioritization
• Python scripting for security automation
• CSV and JSON data manipulation
• Report generation and formatting
• Security operations documentation

This simulation reflects actual enterprise vulnerability management practices:

• Realistic vulnerability distributions and CVSS scores
• Authentic CVE identifiers from recent security advisories
• Industry-standard remediation timelines
• Practical compensating control recommendations
• Professional documentation standards

This project aligns with industry frameworks including:

• NIST Cybersecurity Framework (Identify, Protect, Detect, Respond, Recover)
• CIS Critical Security Controls (Continuous Vulnerability Management)
• ISO 27001 (Vulnerability Management Requirements)
• PCI DSS (Vulnerability Scanning and Patching Requirements)

Potential additions to extend this simulation:

• Integration with vulnerability databases (NVD, MITRE)
• Automated patch management workflow
• Vulnerability trend analysis over time
• Risk scoring algorithm refinement
• Integration with ticketing systems
• Compliance reporting templates
• Dashboard visualizations

This project is part of a cybersecurity portfolio demonstrating practical security operations skills. For questions about implementation, methodologies, or consulting opportunities, please reach out through GitHub.

Disclaimer: This is a simulation for educational and portfolio purposes. All vulnerability data is synthesized for demonstration. No actual organizational data or security information is included.

MIT License - This project is open source and available for educational use.