AI Summary: HackGPT Enterprise is an AI-powered penetration testing platform tailored for enterprise security teams, designed to deliver comprehensive cybersecurity assessments through its advanced AI and machine learning capabilities. Key features include multi-model support for AI engines, automated reporting, robust compliance frameworks, and a cloud-native microservices architecture that enhances performance and scalability. Its tools for zero-day detection, risk intelligence, and extensive reporting ensure that organizations maintain a proactive stance against security threats.

README

🚀 HackGPT Enterprise

AI-Powered Penetration Testing Platform

HackGPT Enterprise is a production-ready, cloud-native AI-powered penetration testing platform designed for enterprise security teams. It combines advanced AI, machine learning, microservices architecture, and comprehensive security frameworks to deliver professional-grade cybersecurity assessments.

Created by Yashab Alam, Founder & CEO of ZehraSec

💰 Support the Project: Donate to HackGPT Development | Help us build the future of AI-powered penetration testing!

🏢 Enterprise Features

🤖 Advanced AI Engine

• Multi-Model Support: OpenAI GPT-4, Local LLM (Ollama), TensorFlow, PyTorch
• Machine Learning: Pattern recognition, anomaly detection, behavioral analysis
• Zero-Day Detection: ML-powered vulnerability discovery and correlation
• Risk Intelligence: CVSS scoring, impact assessment, exploit prioritization
• Automated Reporting: Executive summaries, technical details, compliance mapping

🛡️ Enterprise Security & Compliance

• Authentication: RBAC + LDAP/Active Directory integration
• Authorization: Role-based permissions (Admin, Lead, Senior, Pentester, Analyst)
• Compliance: OWASP, NIST, ISO27001, SOC2, PCI-DSS frameworks
• Audit Logging: Comprehensive activity tracking and forensics
• Data Protection: AES-256-GCM encryption, JWT tokens, secure sessions

🏗️ Cloud-Native Architecture

• Microservices: Docker containers with Kubernetes orchestration
• Service Discovery: Consul-based service registry
• Load Balancing: Nginx reverse proxy with auto-scaling
• Multi-Cloud: AWS, Azure, GCP deployment support
• High Availability: Circuit breakers, health checks, failover

⚡ Performance & Scalability

• Parallel Processing: Celery-based distributed task execution
• Multi-Layer Caching: Redis + memory caching with TTL management
• Database: PostgreSQL with connection pooling and replication
• Real-Time: WebSocket dashboards with live updates
• Auto-Scaling: Worker pools adapt to workload demands

📊 Enterprise Reporting & Analytics

• Dynamic Reports: HTML, PDF, JSON, XML, CSV export formats
• Real-Time Dashboards: Prometheus + Grafana monitoring stack
• Log Analytics: ELK stack (Elasticsearch + Kibana) integration
• Executive Summaries: AI-generated business impact assessments
• Compliance Reports: Framework-specific compliance documentation

🚀 Quick Start

Prerequisites

• Operating System: Linux (Ubuntu/Debian/RHEL/CentOS), macOS, or Windows WSL2
• Python: 3.8+ with pip and virtual environment support
• Docker: For containerized deployment (recommended)
• Resources: Minimum 4GB RAM, 20GB disk space

Enterprise Installation

# Clone the repository
git clone https://github.com/yashab-cyber/HackGPT.git
cd HackGPT

# Run enterprise installer (sets up all services)
chmod +x install.sh
./install.sh

# Configure environment
cp .env.example .env
# Edit .env with your API keys and settings
nano .env

# Verify installation
python3 test_installation.py

Deployment Options

1. Standalone Enterprise Mode

# Activate virtual environment
source venv/bin/activate

# Run enterprise application
python3 hackgpt_v2.py

2. API Server Mode

# Start REST API server
python3 hackgpt_v2.py --api

# API available at: http://localhost:8000
# Health check: http://localhost:8000/api/health

3. Web Dashboard Mode

# Start web dashboard
python3 hackgpt_v2.py --web

# Dashboard available at: http://localhost:8080

4. Full Enterprise Stack (Recommended)

# Deploy complete microservices stack
docker-compose up -d

# Services:
# - API Server: http://localhost:8000
# - Web Dashboard: http://localhost:8080  
# - Monitoring: http://localhost:9090 (Prometheus)
# - Analytics: http://localhost:3000 (Grafana)
# - Logs: http://localhost:5601 (Kibana)

5. Direct Assessment Mode

# Run immediate assessment
python3 hackgpt_v2.py \
  --target example.com \
  --scope "Web application and API" \
  --auth-key "ENTERPRISE-2025-AUTH" \
  --assessment-type black-box \
  --compliance OWASP

🏗️ Enterprise Architecture

Core Components

graph TD
    A[Load Balancer/Nginx] --> B[HackGPT API Gateway]
    B --> C[Authentication Service]
    B --> D[AI Engine Service] 
    B --> E[Exploitation Service]
    B --> F[Reporting Service]
    
    C --> G[LDAP/AD]
    D --> H[OpenAI API]
    D --> I[Local LLM]
    D --> J[ML Models]
    
    E --> K[Parallel Processor]
    F --> L[Report Generator]
    
    K --> M[Celery Workers]
    M --> N[Redis Queue]
    
    B --> O[PostgreSQL]
    B --> P[Redis Cache]
    
    Q[Prometheus] --> R[Grafana]
    S[Elasticsearch] --> T[Kibana]

Service Stack

🔧 Configuration

Enterprise Configuration (config.ini)

The configuration file supports 200+ options across multiple categories:

[app]
debug = false
environment = production
max_sessions = 100

[database]
url = postgresql://hackgpt:hackgpt123@localhost:5432/hackgpt
pool_size = 20
backup_enabled = true

[ai]
openai_api_key = your_key_here
openai_model = gpt-4
enable_local_fallback = true
confidence_threshold = 0.8

[security]
secret_key = your_secret_here
jwt_algorithm = HS256
rate_limit_enabled = true

[ldap]
server = ldaps://your-ldap-server.com:636
bind_dn = cn=admin,dc=example,dc=com

[compliance]
frameworks = OWASP,NIST,ISO27001,SOC2,PCI-DSS
auto_compliance_check = true

[cloud]
docker_host = unix:///var/run/docker.sock
service_registry_backend = consul

Environment Variables (.env)

Over 100 environment variables for enterprise deployment:

# Core Services
DATABASE_URL=postgresql://hackgpt:hackgpt123@localhost:5432/hackgpt
REDIS_URL=redis://localhost:6379/0
OPENAI_API_KEY=your_openai_api_key

# Security
SECRET_KEY=your_secret_key
JWT_SECRET_KEY=your_jwt_secret
LDAP_SERVER=ldaps://your-ldap.com:636

# Cloud Providers
AWS_ACCESS_KEY_ID=your_aws_key
AZURE_SUBSCRIPTION_ID=your_azure_id
GCP_PROJECT_ID=your_gcp_project

# Monitoring
PROMETHEUS_ENDPOINT=http://localhost:9090
GRAFANA_API_KEY=your_grafana_key
ELASTICSEARCH_ENDPOINT=http://localhost:9200

🎯 Enterprise Penetration Testing

Enhanced 6-Phase Methodology

Phase 1: Intelligence Gathering & Reconnaissance

Enterprise Features:

• AI-powered OSINT automation
• Multi-source data aggregation
• Threat intelligence correlation
• Cloud asset discovery (AWS, Azure, GCP)
• Tools: theHarvester, Amass, Subfinder, Shodan API

Phase 2: Advanced Scanning & Enumeration

Enterprise Features:

• Parallel distributed scanning
• Service fingerprinting with ML classification
• Vulnerability correlation across assets
• Zero-day pattern detection
• Tools: Nmap, Masscan, Nuclei, HTTPx, Naabu

Phase 3: Vulnerability Assessment

Enterprise Features:

• CVSS v3.1 automated scoring
• Business impact analysis
• Exploit availability assessment
• Compliance framework mapping
• Tools: OpenVAS, Nexpose integration, custom scanners

Phase 4: Exploitation & Post-Exploitation

Enterprise Features:

• Safe-mode exploitation with approval workflows
• Privilege escalation enumeration
• Lateral movement mapping
• Data exfiltration simulation
• Tools: Metasploit, CrackMapExec, BloodHound, custom exploits

Phase 5: Enterprise Reporting & Analytics

Enterprise Features:

• Executive dashboard with KPIs
• Technical vulnerability details
• Compliance gap analysis
• Risk prioritization matrix
• Outputs: HTML, PDF, JSON, XML, compliance reports

Phase 6: Verification & Retesting

Enterprise Features:

• Automated remediation verification
• Regression testing for fixes
• Continuous security monitoring
• Trend analysis and metrics
• Features: Scheduled retests, delta reporting

📊 Enterprise Interfaces

1. Command Line Interface (CLI)

# Interactive enterprise mode
python3 hackgpt_v2.py

# Available options:
# 1. Full Enterprise Pentest (All 6 Phases)
# 2. Run Specific Phase
# 3. Custom Assessment Workflow
# 4. View Reports & Analytics
# 5. Real-time Dashboard
# 6. User & Permission Management
# 7. System Configuration
# 8. Compliance Management
# 9. Cloud & Container Management
# 10. AI Engine Configuration

2. REST API Server

# Start API server
python3 hackgpt_v2.py --api

# Available endpoints:
# GET  /api/health - Health check
# POST /api/pentest/start - Start assessment
# GET  /api/sessions - List sessions
# GET  /api/reports/{id} - Get report
# POST /api/users - User management
# GET  /api/compliance - Compliance status

3. Web Dashboard

# Start web dashboard
python3 hackgpt_v2.py --web

# Features:
# - Real-time assessment monitoring
# - Interactive vulnerability management
# - Executive summary dashboard
# - User and role management
# - System configuration
# - Compliance reporting

4. Voice Commands (Enterprise)

# Voice command mode
python3 hackgpt_v2.py --voice

# Supported commands:
# "Start enterprise assessment of example.com"
# "Show compliance dashboard"
# "Generate executive report"
# "Scale worker pool to 10"

🔐 Enterprise Security

Authentication & Authorization

• Multi-Factor Authentication: LDAP/AD + JWT tokens
• Role-Based Access Control: Granular permissions matrix
• Session Management: Secure session handling with timeout
• API Security: Rate limiting, CORS, input validation

Data Protection

• Encryption: AES-256-GCM for data at rest
• Transport Security: TLS 1.3 for data in transit
• Key Management: Automated key rotation
• Audit Logging: Comprehensive activity tracking

Compliance Frameworks

📈 Monitoring & Analytics

Real-Time Monitoring

• System Metrics: CPU, memory, disk, network utilization
• Application Metrics: Request rates, response times, error rates
• Security Metrics: Vulnerability counts, risk scores, remediation rates
• Business Metrics: Assessment coverage, compliance scores

Alerting

• Email Alerts: Critical vulnerabilities, system issues
• Slack Integration: Real-time notifications to security teams
• Webhook Support: Custom integrations with SIEM systems
• Dashboard Alerts: Visual indicators and notifications

Analytics Dashboard

# Access Grafana dashboard
http://localhost:3000
# Login: admin / hackgpt123

# Pre-configured dashboards:
# - HackGPT System Overview
# - Assessment Performance Metrics  
# - Vulnerability Trend Analysis
# - User Activity Dashboard
# - Compliance Status Overview

🛠️ Advanced Usage

Custom AI Models

# Configure custom AI endpoints
config['ai']['custom_model_endpoint'] = 'http://your-llm:8000'
config['ai']['model_type'] = 'custom'

Custom Compliance Frameworks

# Add custom compliance framework
from security.compliance import ComplianceFrameworkMapper

mapper = ComplianceFrameworkMapper()
mapper.add_framework('CUSTOM', {
    'sql_injection': 'SEC-01',
    'xss': 'SEC-02',
    # ... custom mappings
})

Kubernetes Deployment

# Deploy to Kubernetes cluster
kubectl apply -f k8s/

Multi-Cloud Deployment

# Deploy to AWS
python3 hackgpt_v2.py --deploy aws

# Deploy to Azure  
python3 hackgpt_v2.py --deploy azure

# Deploy to GCP
python3 hackgpt_v2.py --deploy gcp

🧪 Testing & Development

Running Tests

# Unit tests
pytest tests/unit/

# Integration tests  
pytest tests/integration/

# End-to-end tests
pytest tests/e2e/

# Security tests
bandit -r .
safety check

Development Setup

# Install development dependencies
pip install -r requirements-dev.txt

# Pre-commit hooks
pre-commit install

# Code formatting
black .
flake8 .
mypy .

📦 Enterprise Deployment

Docker Swarm

# Initialize swarm
docker swarm init

# Deploy stack
docker stack deploy -c docker-compose.yml hackgpt

Kubernetes

# Create namespace
kubectl create namespace hackgpt

# Deploy applications
kubectl apply -f k8s/

# Scale workers
kubectl scale deployment hackgpt-worker --replicas=10

Cloud Platforms

AWS Deployment

# ECS deployment
aws ecs create-cluster --cluster-name hackgpt
aws ecs create-service --service-name hackgpt-api

Azure Deployment

# ACI deployment
az container create --resource-group hackgpt --name hackgpt-api

GCP Deployment

# GKE deployment
gcloud container clusters create hackgpt-cluster
kubectl apply -f k8s/

🔧 Troubleshooting

Common Enterprise Issues

Database Connection Issues

# Check PostgreSQL status
systemctl status postgresql
docker logs hackgpt-database

# Test connection
python3 -c "from database import get_db_manager; print(get_db_manager().test_connection())"

Redis Cache Issues

# Check Redis status
redis-cli ping
docker logs hackgpt-redis

# Clear cache
redis-cli FLUSHALL

AI Engine Issues

# Test OpenAI connectivity
python3 -c "import openai; print(openai.Model.list())"

# Check local LLM
ollama list
ollama run llama2:7b

Worker Pool Issues

# Check Celery workers
celery -A performance.parallel_processor inspect active

# Restart workers
docker-compose restart hackgpt-worker

Performance Optimization

# Database optimization
python3 -c "from database import optimize_database; optimize_database()"

# Cache warming
python3 -c "from performance.cache_manager import warm_cache; warm_cache()"

# Worker scaling
docker-compose up --scale hackgpt-worker=10

📄 Enterprise License

This project is licensed under the MIT License with additional enterprise terms:

• Commercial Use: Permitted with attribution
• Enterprise Support: Available through support channels
• Compliance: Tool usage must comply with applicable laws
• Liability: Limited liability for enterprise deployments

🆘 Enterprise Support

Support Channels

• Enterprise Support: yashabalam707@gmail.com
• Technical Issues: https://github.com/yashab-cyber/HackGPT/issues
• Feature Requests: https://github.com/yashab-cyber/HackGPT/discussions
• Security Issues: yashabalam707@gmail.com
• WhatsApp Business: Join Channel

Professional Services

• Implementation: Custom deployment and configuration
• Training: Security team training and certification
• Custom Development: Feature development and integration
• 24/7 Support: Enterprise support packages available

Connect with the Team

• Yashab Alam: GitHub | Instagram | LinkedIn
• ZehraSec: Website | Instagram | LinkedIn

📊 Project Statistics

🗺️ Roadmap

Version 2.1 (Q3 2025)

• Advanced threat hunting capabilities
• ML-based false positive reduction
• Integration with popular SIEM systems
• Mobile application for executives

Version 2.2 (Q4 2025)

• Automated penetration testing workflows
• Advanced cloud security assessments
• Integration with CI/CD pipelines
• Enhanced compliance reporting

Version 3.0 (Q1 2026)

• Fully autonomous security assessments
• Advanced AI attack simulation
• Quantum-safe cryptography
• Next-generation threat detection

🙏 Contributors

Core Development Team

• Lead Developer & Founder: Yashab Alam - @yashab.alam | LinkedIn
• Company: ZehraSec - Cybersecurity Solutions & Research
• AI/ML Engineer: Enterprise AI Team
• Security Engineer: Enterprise Security Team
• DevOps Engineer: Enterprise Infrastructure Team

ZehraSec Social Media

• 🌐 Website: www.zehrasec.com
• 📸 Instagram: @_zehrasec
• 📘 Facebook: ZehraSec Official
• 🐦 X (Twitter): @zehrasec
• 💼 LinkedIn: ZehraSec Company
• 💬 WhatsApp: Business Channel

Acknowledgments

• OpenAI for GPT-4 API access
• Ollama team for local LLM support
• Docker & Kubernetes communities
• Security research community
• Open source tool developers

💰 Support HackGPT Development

Your donations help accelerate development and support the growing cybersecurity community:

Cryptocurrency Donations (Recommended):

• Solana (SOL): 5pEwP9JN8tRCXL5Vc9gQrxRyHHyn7J6P2DCC8cSQKDKT
• Bitcoin (BTC): bc1qmkptg6wqn9sjlx6wf7dk0px0yq4ynr4ukj2x8c

Traditional Payment:

• PayPal: yashabalam707@gmail.com
• Email: yashabalam707@gmail.com

📄 Full Donation Information: DONATE.md - Support tiers, funding goals, and recognition programs

⚖️ Legal & Compliance

⚠️ IMPORTANT LEGAL NOTICE

HackGPT Enterprise is designed for authorized security testing only:

• ✅ Authorized Use: Only use against systems you own or have explicit written permission
• ✅ Compliance: Follow all applicable laws, regulations, and industry standards
• ✅ Responsible Disclosure: Report vulnerabilities through proper channels
• ✅ Documentation: Maintain audit trails and documentation
• ❌ Unauthorized Use: Never use against systems without permission
• ❌ Malicious Activity: Not for criminal or malicious purposes

The developers and contributors are not liable for misuse of this platform.

🚀 HackGPT Enterprise - Transforming Cybersecurity Through AI 🚀

Made with ❤️ by Yashab Alam & ZehraSec for enterprise security teams worldwide

⭐ Star us on GitHub | 💰 Support Development | 📞 Get Support | 🤝 Contribute | 📄 License

🔗 Connect with ZehraSec & Yashab Alam