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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

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

🏢 Enterprise Features

🤖 Advanced AI Engine — Multi-Provider Support

7 AI Providers: OpenAI, Anthropic (Claude), Google (Gemini), DeepSeek, GLM (Zhipu), Local LLMs (Ollama), OpenRouter
26+ AI Models: GPT-5, GPT-5.6, o3, o4-mini, Claude Sonnet 5, Opus 4.8, Gemini 3.5 Flash, 3.1 Pro, DeepSeek R1, and more
Runtime Model Switching: Change AI models on-the-fly with automatic provider fallback
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

🛡️ Advanced SOC Analysis & SIEM Integration

Advanced SOC Engine: Multi-format log parser/normalizer, IOC extraction, MITRE ATT&CK technique mapping
Sliding-Window Correlation: Real-time event grouping, deduplication, and multi-stage attack timeline reconstruction
Statistical Anomalies: Z-score volume profiling, off-hours execution, and IP/host diversity tracking
Incident Response Playbooks: AI-driven IR response guidelines customized per attack vector
SIEM Connectors: Native connectors for Splunk (HEC & searches), IBM QRadar (Ariel AQL), Elasticsearch, and customizable Webhooks

🛡️ 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 advance_hackgpt.py

2. API Server Mode

# Start REST API server
python3 advance_hackgpt.py --api
API available at: http://localhost:8000
Health check: http://localhost:8000/api/health

3. Web Dashboard Mode

# Start web dashboard
python3 advance_hackgpt.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 advance_hackgpt.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]
    B --> SOC[SOC Analysis Service]
    
    C --> G[LDAP/AD]
    D --> H[OpenAI API]
    D --> H2[Anthropic API]
    D --> H3[Google Gemini API]
    D --> H4[DeepSeek API]
    D --> H5[GLM / Zhipu API]
    D --> H6[OpenRouter API]
    D --> I[Local LLM / Ollama]
    D --> J[ML Models]
    
    E --> K[Parallel Processor]
    F --> L[Report Generator]
    
    SOC --> S1[Splunk HEC/Search API]
    SOC --> S2[IBM QRadar Ariel API]
    SOC --> S3[Elasticsearch Query DSL]
    SOC --> S4[Webhook Alerts]
    
    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

| Service | Purpose | Port | Technology | |---------|---------|------|------------| | hackgpt-app | Main application | 8000, 8080 | Python/Flask | | hackgpt-soc | SOC & SIEM Correlation Engine | - | Python / Log Normalizer | | hackgpt-worker | Background tasks | - | Celery | | hackgpt-database | Data persistence | 5432 | PostgreSQL 15 | | hackgpt-redis | Cache & queues | 6379 | Redis 7 | | prometheus | Metrics collection | 9090 | Prometheus | | grafana | Monitoring dashboard | 3000 | Grafana | | elasticsearch | Log aggregation | 9200 | Elasticsearch | | kibana | Log visualization | 5601 | Kibana | | consul | Service discovery | 8500 | Consul | | nginx | Load balancer | 80, 443 | Nginx |

🔧 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] default_model = gpt-5 default_provider =  openaiapikey = yourkeyhere anthropicapikey = yourkeyhere googleapikey = yourkeyhere enablelocalfallback = true confidence_threshold = 0.8
[security] secretkey = yoursecret_here jwt_algorithm = HS256 ratelimitenabled = 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 autocompliancecheck = true
[cloud] docker_host = unix:///var/run/docker.sock serviceregistrybackend = 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
AI Configuration — Multi-Provider
HACKGPTMODEL=gpt-5               # Any model from aiengine/model_registry.py
OPENAIAPIKEY=youropenaiapi_key
ANTHROPICAPIKEY=youranthropicapi_key
GOOGLEAPIKEY=yourgoogleapi_key
DEEPSEEKAPIKEY=yourdeepseekapi_key
GLMAPIKEY=yourglmapi_key
OPENROUTERAPIKEY=youropenrouterapi_key
LOCALLLMENDPOINT=http://localhost:11434
Security
SECRETKEY=yoursecret_key
JWTSECRETKEY=yourjwtsecret
LDAP_SERVER=ldaps://your-ldap.com:636
Cloud Providers
AWSACCESSKEYID=youraws_key
AZURESUBSCRIPTIONID=yourazureid
GCPPROJECTID=yourgcpproject
Monitoring
PROMETHEUS_ENDPOINT=http://localhost:9090
GRAFANAAPIKEY=yourgrafanakey
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 advance_hackgpt.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 advance_hackgpt.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 advance_hackgpt.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 advance_hackgpt.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

| Framework | Coverage | Reports | Automation | |-----------|----------|---------|------------| | OWASP Top 10 | ✅ Full | ✅ Yes | ✅ Automated | | NIST Cybersecurity Framework | ✅ Full | ✅ Yes | ✅ Automated | | ISO 27001 | ✅ Partial | ✅ Yes | ✅ Semi-automated | | SOC 2 | ✅ Partial | ✅ Yes | ✅ Semi-automated | | PCI DSS | ✅ Partial | ✅ Yes | ✅ Manual |

📈 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

Multi-Provider AI Models

from aiengine import getadvancedaiengine, listallmodels, getavailableproviders
Initialize with a specific model
engine = getadvancedaiengine(modelid='claude-sonnet-5')
Switch models at runtime
engine.set_model('gemini-3.5-flash')
List all 26+ available models
for model in engine.listavailablemodels():
    status = "✅" if model['available'] else "❌"
    print(f"{status} {model['display_name']} ({model['provider']})")
Check available providers
for provider in getavailableproviders():
    print(f"{provider['name']}: {provider['model_count']} models")

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 advance_hackgpt.py --deploy aws
Deploy to Azure  
python3 advance_hackgpt.py --deploy azure
Deploy to GCP
python3 advance_hackgpt.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 getdbmanager; print(getdbmanager().test_connection())"

Redis Cache Issues

# Check Redis status
redis-cli ping
docker logs hackgpt-redis
Clear cache
redis-cli FLUSHALL

AI Engine Issues

# List available AI models and providers
python3 -c "from aiengine import listallmodels; [print(m.displayname, m.provider.value) for m in listallmodels()]"
Test provider connectivity
python3 -c "from aiengine.providers import ProviderFactory; print(ProviderFactory.getavailable_providers())"
Check local LLM (Ollama)
ollama list
ollama run llama3.3:70b

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 optimizedatabase; optimizedatabase()"
Cache warming
python3 -c "from performance.cachemanager import warmcache; 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

📊 Project Statistics

| Metric | Value | |--------|-------| | Total Lines of Code | 15,000+ | | Enterprise Dependencies | 90+ | | Configuration Options | 200+ | | Environment Variables | 100+ | | Docker Services | 12 | | Supported Compliance Frameworks | 5 | | Penetration Testing Tools | 50+ | | API Endpoints | 25+ | | Deployment Platforms | 6+ |

🗺️ Roadmap

Version 2.1 (Q3 2025)

[x] Multi-provider AI support (OpenAI, Anthropic, Google, DeepSeek, GLM, Local, OpenRouter)
[x] 26+ model catalog with runtime switching
[x] Provider fallback chain and automatic detection
[ ] ML-based false positive reduction
[ ] Integration with popular SIEM systems

Version 2.2 (Q4 2025)

[ ] Streaming responses from all providers
[ ] Automated penetration testing workflows
[ ] Advanced cloud security assessments
[ ] Integration with CI/CD pipelines

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
AI/ML Engineer: Enterprise AI Team
Security Engineer: Enterprise Security Team
DevOps Engineer: Enterprise Infrastructure Team

💬 WhatsApp: Business Channel

Acknowledgments

OpenAI for GPT-5 and o-series API access
Anthropic for the Claude model family
Google DeepMind for Gemini models
DeepSeek, Zhipu AI (GLM), and OpenRouter
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.