00mjk / liboqs-python

Python 3 bindings for liboqs

liboqs-python: Python 3 bindings for liboqs

---

liboqs-python offers a Python module providing quantum-resistant cryptographic algorithms via liboqs.

Overview

The Open Quantum Safe (OQS) project has the goal of developing and prototyping quantum-resistant cryptography.

liboqs is an open source C library for quantum-resistant cryptographic algorithms. See more about liboqs at https://github.com/open-quantum-safe/liboqs/, including a list of supported algorithms.

liboqs-python is an open source Python 3 wrapper for the liboqs C library. liboqs-python provides:

• a common API for post-quantum key encapsulation mechanisms and digital signature schemes
• a collection of open source implementations of post-quantum cryptography algorithms

The OQS project also provides prototype integrations into application-level protocols to enable testing of quantum-resistant cryptography.

More information on OQS can be found on our website: https://openquantumsafe.org/.

Pre-requisites

Python 3.x liboqs-python depends on the liboqs C library; liboqs must first be compiled as a Linux/macOS/Windows library (i.e. using ninja install with -DBUILD_SHARED_LIBS=ON during configuration), see the specific platform building instructions below.

Contents

The project contains the following files:

• oqs/oqs.py: a Python 3 module wrapper for the liboqs C library.
• oqs/rand.py: a Python 3 module supporting RNGs from <oqs/rand.h>
• examples/kem.py: key encapsulation example
• examples/rand.py: RNG example
• examples/sig.py: signature example
• tests: unit tests

Usage

liboqs-python defines two main classes: KeyEncapsulation and Signature, providing post-quantum key encapsulation and signture mechanisms, respectively. Each must be instantiated with a string identifying one of mechanisms supported by liboqs; these can be enumerated using the get_enabled_KEM_mechanisms and get_enabled_sig_mechanisms functions. The files in examples/ demonstrate the wrapper's API. Support for alternative RNGs is provided via the randombytes[*] functions.

Installation

First, you must build liboqs according to the liboqs building instructions with shared library support enabled (add -DBUILD_SHARED_LIBS=ON to the cmake command), followed (optionally) by a sudo ninja install to ensure that the shared library is visible system-wide (by default it installs under /usr/local/include and /usr/local/lib on Linux/macOS).

On Linux/macOS you may need to set the LD_LIBRARY_PATH (DYLD_LIBRARY_PATH on macOS) environment variable to point to the path to liboqs' library directory, e.g.

export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/lib

assuming liboqs.so.* were installed in /usr/local/lib (true if you ran sudo ninja install after building liboqs).

On Windows ensure that the liboqs shared library oqs.dll is visible system-wide. Use the "Edit the system environment variables" Control Panel tool or type in a Command Prompt

set PATH="%PATH%;C:\some\dir\liboqs\build\bin"

of course replacing the paths with the ones corresponding to your system.

liboqs-python does not depend on any other Python packages. The package isn't hosted on PyPI yet. We recommend to install it into a virtualenv using:

# create & activate virtual environment, e.g.:
python3 -m venv <virtualenv_name>
source <virtualenv_name>/bin/activate

cd /some/dir/liboqs-python
python3 setup.py install

On Windows replace the command source <virtualenv_name>/bin/activate with <virtualenv_name>\Scripts\activate.bat.

Running

The liboqs-python project should be in the PYTHONPATH:

export PYTHONPATH=/some/dir/liboqs-python

or, on Windows platforms, use the "Edit the system environment variables" Control Panel tool or type in a Command Prompt

set PYTHONPATH="C:\some\dir\liboqs-python"

As any python module, liboqs wrapper components can be imported into python programs with import oqs.

To run an example program:

python3 examples/kem.py

To run the unit tests with a test runner (e.g. nose or rednose (apt install python3-nose python3-rednose or pip3 install nose rednose)):

python3 -m nose --rednose --verbose

To run the unit tests without a test runner:

python3 tests/test_kem.py
python3 tests/test_sig.py

liboqs-python has been extensively tested on Linux, macOS and Windows platforms. Continuous integration is provided via CircleCI and AppVeyor.

Limitations and security

liboqs is designed for prototyping and evaluating quantum-resistant cryptography. Security of proposed quantum-resistant algorithms may rapidly change as research advances, and may ultimately be completely insecure against either classical or quantum computers.

We believe that the NIST Post-Quantum Cryptography standardization project is currently the best avenue to identifying potentially quantum-resistant algorithms. liboqs does not intend to "pick winners", and we strongly recommend that applications and protocols rely on the outcomes of the NIST standardization project when deploying post-quantum cryptography.

We acknowledge that some parties may want to begin deploying post-quantum cryptography prior to the conclusion of the NIST standardization project. We strongly recommend that any attempts to do make use of so-called hybrid cryptography, in which post-quantum public-key algorithms are used alongside traditional public key algorithms (like RSA or elliptic curves) so that the solution is at least no less secure than existing traditional cryptography.

Just like liboqs, liboqs-python is provided "as is", without warranty of any kind. See LICENSE.txt for the full disclaimer.

License

liboqs-python is licensed under the MIT License; see LICENSE.txt for details.

Team

The Open Quantum Safe project is led by Douglas Stebila and Michele Mosca at the University of Waterloo.

Contributors

Contributors to the liboqs-python wrapper include:

• Ben Davies (University of Waterloo)
• Vlad Gheorghiu (evolutionQ, University of Waterloo)
• Christian Paquin (Microsoft Research)
• Douglas Stebila (University of Waterloo)

Support

Financial support for the development of Open Quantum Safe has been provided by Amazon Web Services and the Tutte Institute for Mathematics and Computing.

We'd like to make a special acknowledgement to the companies who have dedicated programmer time to contribute source code to OQS, including Amazon Web Services, Cisco Systems, evolutionQ, IBM Research, and Microsoft Research.

Research projects which developed specific components of OQS have been supported by various research grants, including funding from the Natural Sciences and Engineering Research Council of Canada (NSERC); see the source papers for funding acknowledgments.