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HackGpt

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.

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Install / Use

/learn @yashab-cyber/HackGpt
About this skill

Quality Score

0/100

Supported Platforms

Universal

README

<div align="center"> <img src="public/hackgpt-logo.png" alt="HackGPT Enterprise Logo" width="400" height="auto"> <h1>🚀 HackGPT Enterprise</h1> <h3>AI-Powered Penetration Testing Platform</h3> <p> <img src="https://img.shields.io/badge/Python-3.8+-blue.svg" alt="Python 3.8+"> <img src="https://img.shields.io/badge/Platform-Linux%20%7C%20macOS%20%7C%20Windows-orange.svg" alt="Multi-Platform"> <img src="https://img.shields.io/badge/License-MIT-green.svg" alt="MIT License"> <img src="https://img.shields.io/badge/AI-GPT%20%7C%20Local%20LLM%20%7C%20ML-purple.svg" alt="AI Powered"> </p> <p> <img src="https://img.shields.io/badge/Architecture-Microservices-red.svg" alt="Microservices"> <img src="https://img.shields.io/badge/Cloud-Docker%20%7C%20Kubernetes-lightblue.svg" alt="Cloud Native"> <img src="https://img.shields.io/badge/Version-2.0.0-success.svg" alt="Version 2.0.0"> <img src="https://img.shields.io/badge/Status-Production%20Ready-brightgreen.svg" alt="Production Ready"> </p> </div>

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

| Service | Purpose | Port | Technology | |---------|---------|------|------------| | hackgpt-app | Main application | 8000, 8080 | Python/Flask | | 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]
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 Configur

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CategoryDevelopment
Updated2d ago
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yashab-cyber/HackGpt

Languages

Python

Security Score

85/100

Audited on Mar 19, 2026

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