Daniel Kang

license

Apache-2.0(OSI)

source

public

core features withheld

no

Daniel Kang publishes the prover and its converters under Apache-2.0, with no paid edition or withheld component, so anyone may run, modify and redistribute it. The placeholder crate on crates.io declares AGPL-3.0-or-later instead; it carries none of the prover, so the repository's license governs.

• https://crates.io/api/v1/crates/zkml/0.0.1 recorded 2026-09-27

  zkml 0.0.1, created 2023-02-27: license AGPL-3.0-or-later, has_lib false, bin_names [main], one Rust file, crate_size 15,542 bytes

• https://raw.githubusercontent.com/ddkang/zkml/main/Cargo.toml recorded 2026-09-27

  Package zkml 0.0.1, "Zero-knowledge machine learning", license = "LICENSE" (the file name put in the SPDX field), homepage github.com/ddkang/zkml, repository github.com/ddkang/zkml-public.git; depends on the PSE halo2, halo2_gadgets and halo2_proofs crates

• https://raw.githubusercontent.com/ddkang/zkml/main/LICENSE recorded 2026-09-27

  Apache License, Version 2.0, full text; the appendix copyright line is left as the unfilled template

• https://ungh.cc/repos/ddkang/zkml/files/main recorded 2026-09-27

  Full file listing of ddkang/zkml main at 4378958, 125 paths: src/, python/ converters, examples/, testing/; no ee/, enterprise/, commercial/ or proprietary/ directory

• https://ungh.cc/repos/ddkang/zkml/releases recorded 2026-09-27

  No releases published for ddkang/zkml

GitHub stars are the only signal: the prover is installed by building the repository, and the zkml crate is a placeholder that does not contain it. A star is not a use.

• https://crates.io/api/v1/crates/zkml/0.0.1 recorded 2026-09-27

  zkml 0.0.1, created 2023-02-27: license AGPL-3.0-or-later, has_lib false, bin_names [main], one Rust file, crate_size 15,542 bytes

• https://ungh.cc/repos/ddkang/zkml recorded 2026-09-27

  ddkang/zkml: 379 stars, 42 forks, default branch main, pushed 2024-05-17

A proof lets anyone confirm that a specific model computed a specific output without trusting the party that ran it, which puts ZKML beside NVIDIA's hardware attestation at the top of the category. It accepts only TensorFlow Lite models.

• https://arxiv.org/abs/2210.08674 recorded 2026-09-27

  "Scaling up Trustless DNN Inference with Zero-Knowledge Proofs", the paper the README cites for implementation details

• https://raw.githubusercontent.com/ddkang/zkml/main/Cargo.toml recorded 2026-09-27

  Package zkml 0.0.1, "Zero-knowledge machine learning", license = "LICENSE" (the file name put in the SPDX field), homepage github.com/ddkang/zkml, repository github.com/ddkang/zkml-public.git; depends on the PSE halo2, halo2_gadgets and halo2_proofs crates

• https://raw.githubusercontent.com/ddkang/zkml/main/README.md recorded 2026-09-27

  "zkml is a framework for constructing proofs of ML model execution in ZK-SNARKs"; "Currently, we accept TFLite models"; the quickstart creates params_kzg and params_ipa and proves an MNIST circuit with kzg