Skip to content

README.md

Latest commit

 

History

History
318 lines (245 loc) · 10.2 KB

README.md

File metadata and controls

318 lines (245 loc) · 10.2 KB

Houdinis Framework - Quantum Cryptography Testing Platform

Houdinis Logo

Houdinis is a comprehensive quantum cryptography exploitation framework designed for security researchers, penetration testers, and quantum computing enthusiasts. The framework provides tools to test quantum algorithms, evaluate cryptographic vulnerabilities, and benchmark quantum computing backends.

Key Features

Multi-Backend Quantum Computing Support

  • IBM Quantum Experience - Access to real quantum hardware and cloud simulators
  • NVIDIA cuQuantum - GPU-accelerated quantum circuit simulation
  • Amazon Braket - AWS quantum computing service with multiple hardware providers
  • Microsoft Azure Quantum - Enterprise quantum cloud platform
  • Google Cirq - Research-oriented quantum computing framework
  • PennyLane - Quantum machine learning and optimization

Quantum Cryptography Exploits

  • Shor's Algorithm - RSA and ECC key factorization
  • Grover's Algorithm - Symmetric key brute force acceleration
  • Quantum Network Scanning - Identify quantum-vulnerable systems
  • Post-Quantum Migration Tools - Assess cryptographic transition needs
  • TLS/SSL Quantum Assessment - Evaluate transport layer security

Advanced Capabilities

  • Multi-platform benchmarking - Compare performance across backends
  • NISQ algorithm optimization - Noisy Intermediate-Scale Quantum device support
  • Quantum machine learning - Cryptanalysis using QML techniques
  • Harvest Now, Decrypt Later - Future quantum threat assessment

Installation

Quick Start

git clone https://github.com/firebitsbr/Houdinis.git
cd Houdinis
pip install -r requirements.txt
python main.py

Dependencies

# Core quantum computing libraries
pip install qiskit qiskit-aer qiskit-ibmq-provider
pip install cirq pennylane

# Cloud platform SDKs  
pip install amazon-braket-sdk azure-quantum
pip install cuquantum-python  # Requires NVIDIA GPU

# Framework dependencies
pip install numpy scipy matplotlib networkx
pip install cryptography paramiko requests

Quick Start Guide

1. Basic Framework Usage

from core.session import Session
from core.cli import CLI

# Initialize Houdinis session
cli = CLI()
cli.start()

# Load quantum modules
use auxiliary/quantum_config
use exploits/rsa_shor

2. Configure Quantum Backend

# IBM Quantum configuration
houdinis> use auxiliary/quantum_config
houdinis> set BACKEND ibm_quantum
houdinis> set TOKEN your_ibm_token_here
houdinis> run

# NVIDIA cuQuantum configuration  
houdinis> set BACKEND nvidia_cuquantum
houdinis> set GPU_DEVICE 0
houdinis> run

3. Run Quantum Exploit

# Shor's algorithm RSA factorization
houdinis> use exploits/rsa_shor
houdinis> set TARGET_NUMBER 15
houdinis> set BACKEND ibmq_qasm_simulator
houdinis> run

# Grover's algorithm brute force
houdinis> use exploits/grover_bruteforce
houdinis> set TARGET_KEY_SIZE 64
houdinis> set BACKEND nvidia_cuquantum
houdinis> run

4. Multi-Backend Benchmarking

# Compare algorithm performance across backends
houdinis> use exploits/multi_backend_benchmark
houdinis> set ALGORITHM shor
houdinis> set QUBITS 8
houdinis> set BACKENDS all
houdinis> set RUNS 5
houdinis> run

Module Reference

Core Modules

auxiliary/quantum_config

Multi-platform quantum backend configuration module.

Options:

  • BACKEND: Target quantum computing platform
  • TOKEN: Authentication token for cloud services
  • HUB/GROUP/PROJECT: IBM Quantum access parameters
  • DEVICE_ID: Specific quantum device selection

Supported Backends:

  • ibm_quantum - IBM Quantum Experience
  • nvidia_cuquantum - NVIDIA GPU simulation
  • amazon_braket - AWS Braket service
  • azure_quantum - Microsoft Azure Quantum
  • google_cirq - Google quantum computing
  • pennylane - Quantum ML platform

Exploitation Modules

exploits/rsa_shor

Implements Shor's algorithm for RSA key factorization.

Options:

  • TARGET_NUMBER: Number to factorize (default: 15)
  • BACKEND: Quantum backend to use
  • QUBITS: Number of qubits (auto-calculated)
  • SHOTS: Measurement repetitions (default: 1024)

exploits/grover_bruteforce

Grover's algorithm for symmetric key brute force.

Options:

  • TARGET_KEY_SIZE: Key size in bits (default: 64)
  • SEARCH_SPACE: Search space size (default: 2^16)
  • ORACLE_TYPE: Oracle implementation type
  • ITERATIONS: Grover iterations (auto-calculated)

exploits/multi_backend_benchmark

Performance comparison across quantum backends.

Options:

  • ALGORITHM: Algorithm to benchmark (shor, grover, qft, vqe)
  • QUBITS: Circuit size (default: 4)
  • BACKENDS: Backends to test (default: all)
  • RUNS: Benchmark runs per backend (default: 3)
  • SAVE_RESULTS: Save results to JSON file

Network Scanning Modules

scanners/quantum_vuln_scanner

Identifies systems vulnerable to quantum attacks.

Options:

  • TARGET: Target network or host
  • CHECK_TLS: Scan TLS/SSL configurations
  • CHECK_SSH: Analyze SSH key algorithms
  • QUANTUM_TIMELINE: Years until quantum threat (default: 15)

scanners/network_scanner

General network reconnaissance with quantum awareness.

Options:

  • TARGET: Target network range
  • PORTS: Ports to scan (default: common)
  • CRYPTO_ANALYSIS: Perform cryptographic analysis
  • OUTPUT_FORMAT: Report format (json, xml, txt)

Utility Modules

payloads/decrypt_tls

TLS/SSL quantum decryption simulation.

utils/banner

Framework banner and version information.

Backend Comparison

Backend Type Performance Cost Use Case
IBM Quantum Real Hardware Medium Free Tier Research, Education
NVIDIA cuQuantum GPU Simulation Very High Local GPU Large Simulations
Amazon Braket Cloud High Pay-per-use Production, Hybrid
Azure Quantum Cloud High Enterprise Business Applications
Google Cirq Simulation Medium Free Algorithm Development

Performance Benchmarks (Sample)

Algorithm IBM Quantum NVIDIA cuQuantum Amazon Braket Azure Quantum
Shor (8 qubits) 45.2s 2.1s 12.7s 18.3s
Grover (6 qubits) 32.1s 1.3s 8.9s 14.2s
QFT (5 qubits) 28.5s 0.8s 6.2s 9.7s

Documentation

Notebooks Directory

Comprehensive Jupyter notebooks with detailed examples:

  • Shors_Algorithm_RSA_Exploitation.ipynb - RSA factorization tutorial
  • Grovers_Algorithm_Symmetric_Key_Attacks.ipynb - Symmetric key attacks
  • Post_Quantum_Cryptography_Analysis.ipynb - PQC migration guide
  • Quantum_Machine_Learning_Cryptanalysis.ipynb - QML techniques
  • Multi_Backend_Performance_Comparison.ipynb - Backend benchmarking

Configuration Files

config.ini

Main framework configuration:

[DEFAULT]
framework_name = Houdinis
version = 1.0.0
author = Mauro Risonho de Paula Assumpção aka firebitsbr

[quantum]
default_backend = ibm_quantum
max_qubits = 20
default_shots = 1024

[security]
enable_logging = true
log_level = INFO

[SECURITY] Security Considerations

Responsible Use

This framework is designed for:

  • Security research and vulnerability assessment
  • Educational purposes and quantum computing learning
  • Cryptographic analysis and post-quantum migration planning
  • Algorithm benchmarking and performance evaluation

Ethical Guidelines

  • Only test systems you own or have explicit permission to test
  • Respect cloud platform terms of service and usage limits
  • Use findings to improve security, not to cause harm
  • Report vulnerabilities responsibly through proper channels

Legal Disclaimer

Users are responsible for complying with applicable laws and regulations. The authors assume no liability for misuse of this framework.

Contributing

Development Setup

git clone https://github.com/firebitsbr/Houdinis.git
cd Houdinis
pip install -r requirements.txt
pip install -r requirements-dev.txt  # Development dependencies

# Run tests
python -m pytest tests/

# Code formatting
black . && flake8 .

Contribution Guidelines

  1. Fork the repository
  2. Create a feature branch
  3. Implement your changes with tests
  4. Ensure code quality (black, flake8, mypy)
  5. Submit a pull request with detailed description

Adding New Backends

  1. Implement backend class in quantum/backend.py
  2. Add configuration support in auxiliary/quantum_config.py
  3. Update requirements.txt with new dependencies
  4. Add documentation to BACKENDS.md
  5. Include example in demo scripts

[FILE] License

MIT License

Copyright (c) 2025 Mauro Risonho de Paula Assumpção aka firebitsbr

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

[THANKS] Acknowledgments

  • IBM Quantum Team - Qiskit and quantum computing access
  • NVIDIA - cuQuantum GPU acceleration
  • Amazon Web Services - Braket quantum computing service
  • Microsoft - Azure Quantum platform
  • Google - Cirq quantum computing framework
  • Xanadu - PennyLane quantum machine learning
  • Quantum Computing Community - Research and collaboration

[SUPPORT] Support

[ELECTRIC] Houdinis Framework - Making quantum cryptography testing accessible to everyone.

"Any sufficiently advanced cryptography is indistinguishable from magic... until quantum computers arrive."