SecureChain

Enterprise-Grade Vulnerability Management & Attack Graph Analysis Platform

Transform vulnerability data into actionable security intelligence with AI-powered analysis and interactive attack graph visualization

Quick Start • Documentation • Features • Demo • Contributing

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Overview

SecureChain is a comprehensive cybersecurity platform that revolutionizes how organizations understand and respond to security vulnerabilities. By combining AI-powered vulnerability scanning, threat intelligence integration, and interactive attack graph visualization, SecureChain transforms raw security data into actionable insights.

What Makes SecureChain Special

• AI-Powered Analysis: Intelligent vulnerability assessment with natural language explanations
• Attack Graph Visualization: Interactive NetworkX-based attack path analysis
• Smart Chatbot: Conversational AI for vulnerability consultation and remediation guidance
• Threat Intelligence: OpenCTI integration for enriched security context
• Complete Pipeline: End-to-end workflow from scan to remediation

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Features

Intelligent Vulnerability Scanning

• Multi-engine vulnerability detection
• AI-powered risk assessment
• CVSS scoring and severity classification
• Evidence-based finding validation

Advanced Attack Graph Analysis

• NetworkX-powered graph generation
• Interactive visualization with Plotly
• Attack path identification and risk scoring
• MITRE ATT&CK technique mapping

AI Security Consultant

• Natural language vulnerability explanations
• Personalized remediation guidance
• Context-aware conversation flow
• Step-by-step fix instructions

Threat Intelligence Integration

• OpenCTI platform connectivity
• CVE enrichment with threat actor data
• Real-time threat landscape updates
• Exploit availability tracking

Enterprise Integration

• PostgreSQL for structured data storage
• Neo4j for graph relationship modeling
• RESTful API for system integration
• Docker containerization support

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Quick Start

1. Complete Website Analysis

Analyze any website for vulnerabilities and generate comprehensive reports:

# Run complete vulnerability analysis
python complete_website_analysis.py testphp.vulnweb.com

# Generated files:
# ✅ analysis_XXXXX_final_report.json      - Complete analysis results
# ✅ analysis_XXXXX_attack_graph.png       - Visual attack graph
# ✅ analysis_XXXXX_interactive_report.html - Web-based report
# ✅ analysis_XXXXX_chatbot_kb.json        - AI knowledge base

2. Interactive AI Consultation

Chat with your personal security consultant about the findings:

# Start AI-powered vulnerability chatbot
python smart_vulnerability_chatbot.py analysis_XXXXX_chatbot_kb.json

# Example conversation:
# You: What are the critical vulnerabilities?
# AI: Let me cut to the chase - we have some urgent security matters...

3. Attack Graph Visualization

Generate sophisticated attack graphs with NetworkX:

# Create advanced attack graphs
python attackGraph/attack_graph_generator.py

# Outputs:
# ✅ Interactive HTML visualization
# ✅ Static PNG network diagram
# ✅ Attack path analysis (CSV)
# ✅ Risk assessment report (JSON)

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Demo

End-to-End Workflow Demo

# Run complete demonstration
python demo_complete_workflow.py

# Interactive demo with:
# 1. Website vulnerability analysis
# 2. Attack graph generation
# 3. AI chatbot consultation
# 4. Report generation

Sample Results

Target: testphp.vulnweb.com

• Vulnerabilities Found: 7 (1 Critical, 3 High, 3 Medium)
• Attack Paths Identified: 10 potential routes
• Key Finding: CVE-2021-44228 (Log4j) - Critical severity

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Architecture

Data Flow Pipeline

graph LR
    A[Website Input] --> B[AI Vulnerability Scanner]
    B --> C[Finding Normalization]
    C --> D[OpenCTI Enrichment]
    D --> E[PostgreSQL Storage]
    E --> F[Neo4j Attack Graph]
    F --> G[Interactive Visualization]
    G --> H[AI Chatbot Consultation]

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Technology Stack

Component	Technology	Purpose
Backend	Python FastAPI	RESTful API services
Database	PostgreSQL + Neo4j	Structured + Graph data
AI/ML	OpenAI, Anthropic, Gemini	Natural language processing
Visualization	NetworkX + Plotly	Interactive attack graphs
Threat Intel	OpenCTI	Security context enrichment
Frontend	React + TypeScript	Web interface

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Documentation

Getting Started

• Installation Guide
• Configuration Setup
• First Vulnerability Scan

Advanced Usage

• API Documentation
• Attack Graph Customization
• OpenCTI Integration
• Chatbot Customization

Enterprise Deployment

• Docker Deployment
• Kubernetes Setup
• Security Hardening
• Monitoring & Logging

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Use Cases

Enterprise Security Teams

• Vulnerability Management: Centralized tracking and prioritization
• Risk Assessment: Data-driven security decision making
• Compliance Reporting: Automated security posture documentation
• Incident Response: Attack path analysis for breach investigation

Penetration Testers

• Attack Surface Mapping: Comprehensive vulnerability discovery
• Exploitation Planning: Attack graph-guided testing strategies
• Report Generation: Professional vulnerability assessment reports
• Client Education: AI-powered explanation of security issues

Security Researchers

• Vulnerability Analysis: Deep-dive security research capabilities
• Threat Modeling: Advanced attack scenario development
• Tool Integration: Extensible platform for custom security tools
• Knowledge Sharing: AI-assisted security education

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Installation

Prerequisites

• Python 3.8+
• Node.js 16+
• Docker (optional)
• PostgreSQL 12+
• Neo4j 4.0+

Quick Install

# Clone the repository
git clone https://github.com/yourusername/securechain.git
cd securechain

# Install Python dependencies
pip install -r requirements.txt

# Install Node.js dependencies
npm install

# Setup environment variables
cp .env.example .env
# Edit .env with your configuration

# Initialize databases
python backend/init_database.py

# Start the platform
docker-compose up -d

Manual Setup

Click to expand manual installation steps

# 1. Setup Python environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
pip install -r requirements.txt

# 2. Setup databases
# PostgreSQL
createdb securechain
psql securechain < backend/database-setup/postgres-init/01-create-database.sql

# Neo4j
# Start Neo4j and run:
# backend/database-setup/neo4j-init/01-create-constraints.cypher

# 3. Configure environment
export POSTGRES_URL="postgresql://user:password@localhost:5432/securechain"
export NEO4J_URI="bolt://localhost:7687"
export NEO4J_USER="neo4j"
export NEO4J_PASSWORD="password"

# Optional: AI API keys for enhanced chatbot
export OPENAI_API_KEY="your-openai-key"
export ANTHROPIC_API_KEY="your-anthropic-key"

# 4. Start services
python backend/main.py &
npm run dev &

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Usage Examples

Basic Vulnerability Scan

from complete_website_analysis import WebsiteVulnerabilityAnalyzer

# Initialize analyzer
analyzer = WebsiteVulnerabilityAnalyzer("example.com")

# Run complete analysis
success = analyzer.run_complete_analysis()

if success:
    print("Analysis completed!")
    print(f"Found {len(analyzer.findings)} vulnerabilities")
    print(f"Generated attack graph with {len(analyzer.attack_graph.nodes())} nodes")

AI Chatbot Integration

from smart_vulnerability_chatbot import SmartVulnerabilityChatbot

# Load analysis results
chatbot = SmartVulnerabilityChatbot("analysis_XXXXX_chatbot_kb.json")

# Interactive consultation
response = chatbot.process_query("What are the critical vulnerabilities?")
print(f"AI: {response}")

# Start interactive session
chatbot.start_interactive_session()

Attack Graph Analysis

from attackGraph.attack_graph_generator import AttackGraphGenerator

# Initialize generator
generator = AttackGraphGenerator()

# Load vulnerability data
vuln_data = generator.load_vulnerability_data("scan_results.json")

# Build attack graph
graph = generator.build_attack_graph(vuln_data)

# Find attack paths
attack_paths = generator.find_attack_paths()

# Generate visualizations
generator.visualize_attack_graph("attack_graph.png")
generator.create_interactive_visualization("attack_graph.html")

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API Reference

Core Endpoints

# Health check
GET /health

# Vulnerability ingestion
POST /api/v1/ingestion/ingest
{
  "findings": [
    {
      "finding_id": "vuln_001",
      "host": "example.com",
      "cve": "CVE-2021-44228",
      "severity": "Critical",
      "cvss": 9.8
    }
  ]
}

# Retrieve findings
GET /api/v1/ingestion/findings?severity=Critical

# Attack graph data
GET /api/v1/ingestion/attack-graph

# Chatbot interaction
POST /api/v1/chat
{
  "message": "What are the critical vulnerabilities?",
  "user_id": "user123"
}

Response Examples

Sample API Responses

{
  "findings": [
    {
      "finding_id": "vuln_001",
      "host": "example.com",
      "ip": "192.168.1.100",
      "service": "http",
      "port": 80,
      "cve": "CVE-2021-44228",
      "cvss": 9.8,
      "severity": "Critical",
      "description": "Apache Log4j2 Remote Code Execution",
      "remediation": "Update Log4j to version 2.17.0 or later",
      "opencti_enrichment": {
        "threat_actors": ["APT29", "Lazarus Group"],
        "exploit_available": true,
        "mitre_techniques": ["T1190"]
      }
    }
  ],
  "attack_graph": {
    "nodes": 10,
    "edges": 15,
    "attack_paths": 8,
    "risk_score": 8.5
  }
}

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Testing

Comprehensive Test Suite

# Run all tests
python run_full_pipeline_test.py

# Individual component tests
python simple_pipeline_test.py                    # Core functionality
python test_chatbot_simple.py                     # Chatbot responses
python attackGraph/test_attack_graph.py           # Graph generation
python backend/test_backend.py                    # API endpoints

Test Coverage

Component	Coverage	Status
Vulnerability Scanner	95%	✅
Attack Graph Generator	92%	✅
AI Chatbot	88%	✅
Backend API	90%	✅
Database Integration	85%	✅

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Security

Security Features

• Input Validation: Comprehensive sanitization of all inputs
• API Authentication: JWT-based secure API access
• Data Encryption: At-rest and in-transit encryption
• Audit Logging: Complete activity tracking
• Rate Limiting: API abuse prevention

Security Best Practices

• Regular dependency updates
• Secure coding standards
• Penetration testing
• Vulnerability disclosure program
• Security-focused CI/CD pipeline

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Deployment

Docker Deployment

# Production deployment
docker-compose -f docker-compose.prod.yml up -d

# Development environment
docker-compose up -d

# Scale services
docker-compose up -d --scale backend=3

Kubernetes Deployment

# Deploy to Kubernetes
kubectl apply -f k8s/

# Check deployment status
kubectl get pods -n securechain

# Access services
kubectl port-forward svc/securechain-frontend 3000:3000

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Performance

Benchmarks

Operation	Performance	Scalability
Vulnerability Scan	~2 minutes	1000+ targets/hour
Attack Graph Generation	<5 seconds	10,000+ nodes
AI Response Time	<2 seconds	100+ concurrent users
Database Queries	<100ms	1M+ records

Optimization

• Async processing for large scans
• Caching for frequent queries
• Database indexing optimization
• CDN for static assets

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Contributing

We welcome contributions from the security community!

How to Contribute

1. Fork the repository
2. Create a feature branch: git checkout -b feature/amazing-feature
3. Make your changes: Follow our coding standards
4. Add tests: Ensure your code is well-tested
5. Update documentation: Keep docs current
6. Submit a pull request: Describe your changes

Bug Reports

Found a bug? Please create an issue with:

• Detailed description
• Steps to reproduce
• Expected vs actual behavior
• Environment details
• Screenshots (if applicable)

Feature Requests

Have an idea? We'd love to hear it! Please include:

• Use case description
• Proposed solution
• Alternative approaches
• Implementation complexity

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License

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

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Acknowledgments

Special Thanks

• MITRE Corporation for the ATT&CK framework
• OpenCTI Community for threat intelligence platform
• OWASP Foundation for security standards
• NetworkX Team for graph analysis capabilities

Built With

• FastAPI - Modern Python web framework
• NetworkX - Graph analysis library
• OpenCTI - Threat intelligence platform
• React - Frontend framework
• PostgreSQL - Database system
• Neo4j - Graph database

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Support

Get Help

• Documentation
• Discord Community
• Issue Tracker
• Email Support

Enterprise Support

For enterprise deployments, custom integrations, and professional support:

• Enterprise: enterprise@securechain.io
• Phone: +1 (555) 123-4567
• Website: securechain.io

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Made with dedication by the SecureChain Team

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Securing the digital world, one vulnerability at a time