# facebookresearch/CrypTen

A framework for Privacy Preserving Machine Learning

Repository: https://github.com/facebookresearch/CrypTen
Canonical: https://ross.abutalabs.com/products/crypten
Language: Python
License: MIT
License Family: permissive
Archived: true
Last push: 2024-11-23T22:25:52+00:00

## Health v2 (maintenance only)
Score: 10/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 2576, "days_push": 648, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: archived
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1649, forks 304 (observed 2026-08-28T04:05:16.709448+00:00)

## What it is
CrypTen is a PyTorch-based library for privacy-preserving machine learning built on secure multiparty computation. It exposes a CrypTensor object that behaves like a regular PyTorch tensor, enabling encrypted training and inference with automatic differentiation.

## Use cases
- train machine learning models on encrypted data
- run secure inference without revealing inputs
- perform secure multiparty computation with a PyTorch-like API
- research privacy-preserving machine learning techniques
- compute statistics across parties without sharing raw data
- train an SVM or neural network on encrypted tensors

## When to choose
- you need SMPC-based privacy-preserving ML with a PyTorch feel
- you are an ML researcher exploring secure computation
- you want automatic differentiation over encrypted tensors
- you work on Linux or macOS with Python and optionally GPUs

## When to avoid
- you need a production-ready secure ML system
- you need Windows support
- you need lightweight encryption rather than full multiparty computation
- you need actively maintained software with frequent releases

## Facets
- artifact type: library
- maturity: maintenance
- function: machine-learning, cryptography, security, privacy
- domain: machine-learning, security, privacy, artificial-intelligence
- platform: python
- tags: secure-multiparty-computation, pytorch, privacy-preserving-ml, research-framework, encrypted-tensors, linux, macos, gpu

## Member repositories
- facebookresearch/CrypTen (main) score 10

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:16.709448+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:45:08.700470+00:00, confidence not recorded.
  - readme: https://github.com/facebookresearch/CrypTen (fetched 2026-08-28T04:05:16.709448+00:00, sha 0ba41169ca78)
  - registry_pypi: https://pypi.org/pypi/crypten/json (fetched 2026-08-29T11:18:20.583173+00:00, sha 0a4f63fdc22d)
- Data as of 2026-08-30T08:39:29.467469+00:00.