vfhe 0.0.2

A library for Zero-Knowledge Proofs, (verifiable) Fully Homomorphic Encryption, and related techniques.

vfhe

The VFHE library: a library for Zero-Knowledge Proofs, (verifiable) Fully Homomorphic Encryption, and related techniques.

❗ Warning: This is a pre-release version of the library and is subject to breaking changes. ❗

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Modules

Each module is a self-contained folder under modules/. A module is Python-facing (ships a python/ package + a cdef exposing its C to Python) or internal C-only (contributes compiled kernels used by other modules, no Python symbols).

Module	Kind	What it provides
arith	Python-facing	RNS polynomial arithmetic over Z_q[X]/(X^N+1): incomplete NTTs, complex FFTs, general multiprecision, and basic number theory procedures
misc	Python-facing	The native handle (ffi/lib/libvfhe) plus the internal C utilities: BLAKE3-seeded PRNG, AES-CTR RNG, aligned allocation, mod-switching helpers
mlwe	Python-facing	LWE / Module-LWE and MGSW: key generation, encryption, key-switching, arithmetic, and ring morphisms
fhe	Python-facing	Schemes on top of mlwe: CKKS (encode/encrypt/rescale/rotate/multiply), CGGI16 functional bootstrap, GP25 sparse-amortized bootstrap
piop	Python-facing	Sketch of IOP prover/verifier framework (currently under development)
circuit	Python-facing	Layered GKR arithmetic circuits (protobuf wire format) and their polynomial export to arith
compiler, polycom, snark, vfhe	placeholder	reserved for the compiler frontend, polynomial commitments, the SNARK layer, and the top-level assembly

Installing

pip install vfhe

VFHE ships as an sdist only, with no pre-built wheels, so every install compiles from source and tunes to your CPU. On an x86 machine with AVX-512 IFMA this enables -march=native, the SIMD kernels, AES-NI, and BLAKE3 SIMD; on any other CPU it builds the portable engine (and prints a notice). The result targets this machine. You need a C compiler (clang/gcc); the sdist bundles the BLAKE3 sources, so no submodules are required.

Choosing the compiler. The build uses your interpreter's compiler by default (no configuration needed). To pick a specific one (e.g. with several installed), set the standard CC environment variable; it steers both the CPU detection and the compile, in lockstep:

CC=gcc-14 pip install vfhe

Forcing a portable build. If you build in one place and run in another (Docker image built on a big CI box, run on a smaller node), set VFHE_PORTABLE=1 to skip CPU detection and build the portable engine that runs on any CPU; -march=native would otherwise bake in the build host's features and crash elsewhere. When the portable engine ends up on a CPU that does support AVX-512 IFMA, VFHE prints a one-time hint to rebuild tuned (silence it with the usual warnings filters).

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Development

The development guide, covering the repository layout, the build system, testing, coverage, and CI, is in docs/DEVELOPMENT.md. Contribution expectations are in CONTRIBUTING.md.

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Authors

See AUTHORS.md. Authors are sorted alphabetically by surname, following mathematical tradition.

Maintainers can be reached at [e-mail].

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Citation

If you use VFHE in academic work, please cite the software using CITATION.cff (GitHub renders a "Cite this repository" button from it) and the archived release DOI where relevant. (When a paper is published, we'll add it as the preferred citation.)

Once a release is archived on Zenodo (enable the GitHub-Zenodo integration, then cut a GitHub release), add the DOI badge here:

[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.XXXXXXX.svg)](https://doi.org/10.5281/zenodo.XXXXXXX)