zama-ai

    zama-ai/tfhe-rs

    TFHE-rs: A Pure Rust implementation of the TFHE Scheme for Boolean and Integer Arithmetics Over Encrypted Data.

    cryptography
    homomorphic-encryption
    rust
    tfhe
    Rust
    NOASSERTION
    1.7K stars
    338 forks
    1.7K GitHub watchers
    Updated Nov 2, 2026
    View on GitHub

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    Where it stands

    Rank, growth pace and release cadence relative to everything GStars tracks.

    5 releases in the last 90 days, the latest 14 days ago, with 66 contributors on GitHub.

    Gained 26% more stars in the last 90 days than in the 90 days before.

    Use Cases & Benefits

    • Implements the TFHE scheme in pure Rust for performing boolean and integer arithmetic on encrypted data.
    • Provides a stable, high-performance, and production-ready library with Rust, C, and WASM APIs for flexible homomorphic encryption usage.
    • Use for developing privacy-preserving applications requiring encrypted computations on boolean and integer data.
    • Use for integrating homomorphic encryption into Rust-based backend services with efficient ciphertext compression and key management.
    • Use for client-side encrypted data processing in web applications via the WASM API to maintain data confidentiality.

    Should you depend on it?

    License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.

    License

    Other

    GitHub could not identify this license; read the LICENSE file before depending on it.

    Community files

    • README: present
    • Contributing guide: present
    • Code of conduct: present

    Watch-outs

    • License not identified by GitHub; read the LICENSE file before depending on it.

    General guidance from repository metadata, not legal advice. How we score

    From the README

    TFHE-rs is a pure Rust implementation of TFHE for boolean and integer arithmetics over encrypted data.

    TFHE-rs is designed for developers and researchers who want full control over what they can do with TFHE, while not having to worry about the low-level implementation. The goal is to have a stable, simple, high-performance, and production-ready library for all the advanced features of TFHE.

    Learn more about TFHE-rs features in the documentation.

    Excerpt from the zama-ai/tfhe-rs README on GitHub (NOASSERTION license). © its authors.Read the full README on GitHub

    Daily snapshots

    Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots

    Forks

    338+5

    Open issues

    57+10

    Compared with peers in Cryptography

    Fastest-growing repositories GStars tracks in this cohort for the week of Nov 1, by 7-day star growth

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    zama-ai/tfhe-rs1.7K—6414 days ago
    Category median49.4K+24060—

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