yashab-cyber/HackGpt

HackPilot 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.

Python

1,268

289 commits

updated Oct 12, 2026

See the code

README

HackPilot Enterprise Logo

πŸš€ HackPilot Enterprise

AI-Powered Penetration Testing Platform

Python 3.8+ Multi-Platform MIT License AI Multi-Provider

Microservices Cloud Native Version 2026.09.26 Production Ready Discord Server

HackPilot 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

πŸ’° Support the Project: Donate to HackPilot Development | Help us build the future of AI-powered penetration testing!

🏒 Enterprise Features

πŸ€– Advanced AI Engine β€” 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

πŸ›‘οΈ 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

πŸ›‘οΈ 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

πŸ—οΈ 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

πŸ“Š 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

πŸš€ 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/hackpilot.git
cd hackpilot

# 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_hackpilot.py

2. API Server Mode

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

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

3. Web Dashboard Mode

# Start web dashboard
python3 advance_hackpilot.py --web

# Dashboard available at: http://localhost:8080
# 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_hackpilot.py \
  --target example.com \
  --scope "Web application and API" \
  --auth-key "ENTERPRISE-2025-AUTH" \
  --assessment-type black-box \
  --compliance OWASP

πŸ—οΈ Enterprise Architecture

Core Components

graph TD
    A[Load Balancer/Nginx] --> B[HackPilot 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

ServicePurposePortTechnology
hackpilot-appMain application8000, 8080Python/Flask
hackpilot-socSOC & SIEM Correlation Engine-Python / Log Normalizer
hackpilot-workerBackground tasks-Celery
hackpilot-databaseData persistence5432PostgreSQL 15
hackpilot-redisCache & queues6379Redis 7
prometheusMetrics collection9090Prometheus
grafanaMonitoring dashboard3000Grafana
elasticsearchLog aggregation9200Elasticsearch
kibanaLog visualization5601Kibana
consulService discovery8500Consul
nginxLoad balancer80, 443Nginx

πŸ”§ 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://hackpilot:hackpilot123@localhost:5432/hackpilot
pool_size = 20
backup_enabled = true

[ai]
default_model = gpt-5
default_provider = 
openai_api_key = your_key_here
anthropic_api_key = your_key_here
google_api_key = your_key_here
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://hackpilot:hackpilot123@localhost:5432/hackpilot
REDIS_URL=redis://localhost:6379/0

# AI Configuration β€” Multi-Provider
HACKPILOT_MODEL=gpt-5              # (HACKPILOT_MODEL also supported)               # Any model from ai_engine/model_registry.py
OPENAI_API_KEY=your_openai_api_key
ANTHROPIC_API_KEY=your_anthropic_api_key
GOOGLE_API_KEY=your_google_api_key
DEEPSEEK_API_KEY=your_deepseek_api_key
GLM_API_KEY=your_glm_api_key
OPENROUTER_API_KEY=your_openrouter_api_key
LOCAL_LLM_ENDPOINT=http://localhost:11434

# 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

πŸ“Š Enterprise Interfaces

1. Command Line Interface (CLI)

# Interactive enterprise mode
python3 advance_hackpilot.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_hackpilot.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_hackpilot.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_hackpilot.py --voice

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

πŸ” 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

FrameworkCoverageReportsAutomation
OWASP Top 10βœ… Fullβœ… Yesβœ… Automated
NIST Cybersecurity Frameworkβœ… Fullβœ… Yesβœ… Automated
ISO 27001βœ… Partialβœ… Yesβœ… Semi-automated
SOC 2βœ… Partialβœ… Yesβœ… Semi-automated
PCI DSSβœ… Partialβœ… Yesβœ… Manual

πŸ“ˆ 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 / hackpilot123

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

πŸ› οΈ Advanced Usage

Multi-Provider AI Models

from ai_engine import get_advanced_ai_engine, list_all_models, get_available_providers

# Initialize with a specific model
engine = get_advanced_ai_engine(model_id='claude-sonnet-5')

# Switch models at runtime
engine.set_model('gemini-3.5-flash')

# List all 26+ available models
for model in engine.list_available_models():
    status = "βœ…" if model['available'] else "❌"
    print(f"{status} {model['display_name']} ({model['provider']})")

# Check available providers
for provider in get_available_providers():
    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_hackpilot.py --deploy aws

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

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

πŸ§ͺ 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 .

πŸ“¦ Enterprise Deployment

Docker Swarm

# Initialize swarm
docker swarm init

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

Kubernetes

# Create namespace
kubectl create namespace hackpilot

# Deploy applications
kubectl apply -f k8s/

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

Cloud Platforms

AWS Deployment

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

Azure Deployment

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

GCP Deployment

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

πŸ”§ Troubleshooting

Common Enterprise Issues

Database Connection Issues

# Check PostgreSQL status
systemctl status postgresql
docker logs hackpilot-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 hackpilot-redis

# Clear cache
redis-cli FLUSHALL

AI Engine Issues

# List available AI models and providers
python3 -c "from ai_engine import list_all_models; [print(m.display_name, m.provider.value) for m in list_all_models()]"

# Test provider connectivity
python3 -c "from ai_engine.providers import ProviderFactory; print(ProviderFactory.get_available_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 hackpilot-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 hackpilot-worker=10

πŸ“„ 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

πŸ†˜ Enterprise Support

Support Channels

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

πŸ“Š Project Statistics

MetricValue
Total Lines of Code15,000+
Enterprise Dependencies90+
Configuration Options200+
Environment Variables100+
Docker Services12
Supported Compliance Frameworks5
Penetration Testing Tools50+
API Endpoints25+
Deployment Platforms6+

πŸ—ΊοΈ Roadmap

Version 2.1 (Q3 2025)

  • Multi-provider AI support (OpenAI, Anthropic, Google, DeepSeek, GLM, Local, OpenRouter)
  • 26+ model catalog with runtime switching
  • 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

πŸ™ Contributors

Core Development Team

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

πŸ’° Support HackPilot Development

Your support accelerates development, research infrastructure, and frontier AI model integrations:

Sponsor

  • πŸ’– GitHub Sponsors (Active): Sponsor @yashab-cyber on GitHub
  • πŸͺ™ Cryptocurrency Donations: For transfers (Solana, Bitcoin, Ethereum, USDT, etc.), please email [email protected]
  • πŸ“„ Full Sponsorship & Donation Guide: See DONATE.md for tier perks, transparency reports, and roadmap goals

⚠️ IMPORTANT LEGAL NOTICE

HackPilot Enterprise is designed for authorized security testing only:

  • βœ… Authorized Use: Only use against systems you own or have explicit written permission
  • βœ… Compliance: Follow all applicable laws, regulations, and industry standards
  • βœ… Responsible Disclosure: Report vulnerabilities through proper channels
  • βœ… 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.



HackPilot Enterprise

πŸš€ HackPilot Enterprise - Transforming Cybersecurity Through AI πŸš€

Made with ❀️ by Yashab Alam for enterprise security teams worldwide

⭐ Star us on GitHub | πŸ’° Support Development | πŸ“ž Get Support | 🀝 Contribute | πŸ“„ License

πŸ”— Connect with Yashab Alam

ai
cybersecurity
ethical-hacking
pentesting
pentest-tool
research

yashab-cyber/HackGpt

HackPilot 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.

Python

1,268

289 commits

updated Oct 12, 2026

See the code

README

HackPilot Enterprise Logo

πŸš€ HackPilot Enterprise

AI-Powered Penetration Testing Platform

Python 3.8+ Multi-Platform MIT License AI Multi-Provider

Microservices Cloud Native Version 2026.09.26 Production Ready Discord Server

HackPilot 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

πŸ’° Support the Project: Donate to HackPilot Development | Help us build the future of AI-powered penetration testing!

🏒 Enterprise Features

πŸ€– Advanced AI Engine β€” 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

πŸ›‘οΈ 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

πŸ›‘οΈ 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

πŸ—οΈ 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

πŸ“Š 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

πŸš€ 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/hackpilot.git
cd hackpilot

# 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_hackpilot.py

2. API Server Mode

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

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

3. Web Dashboard Mode

# Start web dashboard
python3 advance_hackpilot.py --web

# Dashboard available at: http://localhost:8080
# 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_hackpilot.py \
  --target example.com \
  --scope "Web application and API" \
  --auth-key "ENTERPRISE-2025-AUTH" \
  --assessment-type black-box \
  --compliance OWASP

πŸ—οΈ Enterprise Architecture

Core Components

graph TD
    A[Load Balancer/Nginx] --> B[HackPilot 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

ServicePurposePortTechnology
hackpilot-appMain application8000, 8080Python/Flask
hackpilot-socSOC & SIEM Correlation Engine-Python / Log Normalizer
hackpilot-workerBackground tasks-Celery
hackpilot-databaseData persistence5432PostgreSQL 15
hackpilot-redisCache & queues6379Redis 7
prometheusMetrics collection9090Prometheus
grafanaMonitoring dashboard3000Grafana
elasticsearchLog aggregation9200Elasticsearch
kibanaLog visualization5601Kibana
consulService discovery8500Consul
nginxLoad balancer80, 443Nginx

πŸ”§ 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://hackpilot:hackpilot123@localhost:5432/hackpilot
pool_size = 20
backup_enabled = true

[ai]
default_model = gpt-5
default_provider = 
openai_api_key = your_key_here
anthropic_api_key = your_key_here
google_api_key = your_key_here
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://hackpilot:hackpilot123@localhost:5432/hackpilot
REDIS_URL=redis://localhost:6379/0

# AI Configuration β€” Multi-Provider
HACKPILOT_MODEL=gpt-5              # (HACKPILOT_MODEL also supported)               # Any model from ai_engine/model_registry.py
OPENAI_API_KEY=your_openai_api_key
ANTHROPIC_API_KEY=your_anthropic_api_key
GOOGLE_API_KEY=your_google_api_key
DEEPSEEK_API_KEY=your_deepseek_api_key
GLM_API_KEY=your_glm_api_key
OPENROUTER_API_KEY=your_openrouter_api_key
LOCAL_LLM_ENDPOINT=http://localhost:11434

# 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

πŸ“Š Enterprise Interfaces

1. Command Line Interface (CLI)

# Interactive enterprise mode
python3 advance_hackpilot.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_hackpilot.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_hackpilot.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_hackpilot.py --voice

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

πŸ” 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

FrameworkCoverageReportsAutomation
OWASP Top 10βœ… Fullβœ… Yesβœ… Automated
NIST Cybersecurity Frameworkβœ… Fullβœ… Yesβœ… Automated
ISO 27001βœ… Partialβœ… Yesβœ… Semi-automated
SOC 2βœ… Partialβœ… Yesβœ… Semi-automated
PCI DSSβœ… Partialβœ… Yesβœ… Manual

πŸ“ˆ 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 / hackpilot123

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

πŸ› οΈ Advanced Usage

Multi-Provider AI Models

from ai_engine import get_advanced_ai_engine, list_all_models, get_available_providers

# Initialize with a specific model
engine = get_advanced_ai_engine(model_id='claude-sonnet-5')

# Switch models at runtime
engine.set_model('gemini-3.5-flash')

# List all 26+ available models
for model in engine.list_available_models():
    status = "βœ…" if model['available'] else "❌"
    print(f"{status} {model['display_name']} ({model['provider']})")

# Check available providers
for provider in get_available_providers():
    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_hackpilot.py --deploy aws

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

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

πŸ§ͺ 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 .

πŸ“¦ Enterprise Deployment

Docker Swarm

# Initialize swarm
docker swarm init

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

Kubernetes

# Create namespace
kubectl create namespace hackpilot

# Deploy applications
kubectl apply -f k8s/

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

Cloud Platforms

AWS Deployment

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

Azure Deployment

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

GCP Deployment

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

πŸ”§ Troubleshooting

Common Enterprise Issues

Database Connection Issues

# Check PostgreSQL status
systemctl status postgresql
docker logs hackpilot-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 hackpilot-redis

# Clear cache
redis-cli FLUSHALL

AI Engine Issues

# List available AI models and providers
python3 -c "from ai_engine import list_all_models; [print(m.display_name, m.provider.value) for m in list_all_models()]"

# Test provider connectivity
python3 -c "from ai_engine.providers import ProviderFactory; print(ProviderFactory.get_available_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 hackpilot-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 hackpilot-worker=10

πŸ“„ 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

πŸ†˜ Enterprise Support

Support Channels

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

πŸ“Š Project Statistics

MetricValue
Total Lines of Code15,000+
Enterprise Dependencies90+
Configuration Options200+
Environment Variables100+
Docker Services12
Supported Compliance Frameworks5
Penetration Testing Tools50+
API Endpoints25+
Deployment Platforms6+

πŸ—ΊοΈ Roadmap

Version 2.1 (Q3 2025)

  • Multi-provider AI support (OpenAI, Anthropic, Google, DeepSeek, GLM, Local, OpenRouter)
  • 26+ model catalog with runtime switching
  • 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

πŸ™ Contributors

Core Development Team

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

πŸ’° Support HackPilot Development

Your support accelerates development, research infrastructure, and frontier AI model integrations:

Sponsor

  • πŸ’– GitHub Sponsors (Active): Sponsor @yashab-cyber on GitHub
  • πŸͺ™ Cryptocurrency Donations: For transfers (Solana, Bitcoin, Ethereum, USDT, etc.), please email [email protected]
  • πŸ“„ Full Sponsorship & Donation Guide: See DONATE.md for tier perks, transparency reports, and roadmap goals

⚠️ IMPORTANT LEGAL NOTICE

HackPilot Enterprise is designed for authorized security testing only:

  • βœ… Authorized Use: Only use against systems you own or have explicit written permission
  • βœ… Compliance: Follow all applicable laws, regulations, and industry standards
  • βœ… Responsible Disclosure: Report vulnerabilities through proper channels
  • βœ… 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.



HackPilot Enterprise

πŸš€ HackPilot Enterprise - Transforming Cybersecurity Through AI πŸš€

Made with ❀️ by Yashab Alam for enterprise security teams worldwide

⭐ Star us on GitHub | πŸ’° Support Development | πŸ“ž Get Support | 🀝 Contribute | πŸ“„ License

πŸ”— Connect with Yashab Alam

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