* feat: use `XofReader` instead of `io::Read` for no_std compatibility

* feat: remove `thiserror` dependency

thiserror is not no_std safe

* feat: move deps std features behind new `std` feature

- add new `std` feature
- add `simd_backend`
- move `colored` dep behind profile feature

* feat: use old rand(v0.7) for cubic example.

since curve25519-dalek (v3) uses old rand(v0.7) we need this.
should upgrade curve25519-dalek to v4 once it out of pre release

* feat: only build bench & profile if std in enabled

* feat: remove rand_core as dependency

* feat(ci): add job to test wasm build

* fix: rollback rand to v7 and update debug test

* fix(ci): Cargo.toml patching

* feat: make clippy happy

* feat: add wasm doc in readme

* feat: readme formatting

* feat: derive `Default` for `ProofVerifyError`
This commit is contained in:
Ashutosh Varma 2023-01-17 23:10:30 +05:30 коммит произвёл GitHub
Родитель 2dee78cfc0
Коммит 2be72b2af2
Не найден ключ, соответствующий данной подписи
Идентификатор ключа GPG: 4AEE18F83AFDEB23
9 изменённых файлов: 186 добавлений и 86 удалений

36
.github/workflows/rust.yml поставляемый
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@ -28,3 +28,39 @@ jobs:
- name: Check clippy warnings
run: cargo clippy --all-targets --all-features -- -D warnings
build_nightly_wasm:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v2
- name: Install
run: rustup default nightly
- name: Build without std
run: cargo build --no-default-features --verbose
- name: Run tests without std
run: cargo test --no-default-features --verbose
- name: Build examples without std
run: cargo build --examples --no-default-features --verbose
- name: Install wasm32-wasi target
run: rustup target add wasm32-wasi
- name: Install wasm32-unknown-unknown target
run: rustup target add wasm32-unknown-unknown
- name: Build for target wasm-wasi
run: RUSTFLAGS="" cargo build --target=wasm32-wasi --no-default-features --verbose
- name: Patch Cargo.toml for wasm-bindgen
run: |
echo "[dependencies.getrandom]" >> Cargo.toml
echo "version = \"0.1\"" >> Cargo.toml
echo "default-features = false" >> Cargo.toml
echo "features = [\"wasm-bindgen\"]" >> Cargo.toml
- name: Build for target wasm32-unknown-unknown
run: RUSTFLAGS="" cargo build --target=wasm32-unknown-unknown --no-default-features --verbose

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@ -11,22 +11,24 @@ license-file = "LICENSE"
keywords = ["zkSNARKs", "cryptography", "proofs"]
[dependencies]
curve25519-dalek = {version = "3.2.0", features = ["serde"]}
merlin = "3.0.0"
rand = "0.7.3"
digest = "0.8.1"
sha3 = "0.8.2"
byteorder = "1.3.4"
curve25519-dalek = { version = "3.2.0", features = [
"serde",
"u64_backend",
"alloc",
], default-features = false }
merlin = { version = "3.0.0", default-features = false }
rand = { version = "0.7.3", features = ["getrandom"], default-features = false }
digest = { version = "0.8.1", default-features = false }
sha3 = { version = "0.8.2", default-features = false }
byteorder = { version = "1.3.4", default-features = false }
rayon = { version = "1.3.0", optional = true }
serde = { version = "1.0.106", features = ["derive"] }
bincode = "1.2.1"
subtle = { version = "2.4", default-features = false }
rand_core = { version = "0.5", default-features = false }
zeroize = { version = "1", default-features = false }
itertools = "0.10.0"
colored = "2.0.0"
flate2 = "1.0.14"
thiserror = "1.0"
serde = { version = "1.0.106", features = ["derive"], default-features = false }
bincode = { version = "1.3.3", default-features = false }
subtle = { version = "2.4", features = ["i128"], default-features = false }
zeroize = { version = "1.5", default-features = false }
itertools = { version = "0.10.0", default-features = false }
colored = { version = "2.0.0", default-features = false, optional = true }
flate2 = { version = "1.0.14" }
[dev-dependencies]
criterion = "0.3.1"
@ -38,20 +40,38 @@ path = "src/lib.rs"
[[bin]]
name = "snark"
path = "profiler/snark.rs"
required-features = ["std"]
[[bin]]
name = "nizk"
path = "profiler/nizk.rs"
required-features = ["std"]
[[bench]]
name = "snark"
harness = false
required-features = ["std"]
[[bench]]
name = "nizk"
harness = false
required-features = ["std"]
[features]
default = ["curve25519-dalek/simd_backend"]
default = ["std", "simd_backend"]
std = [
"curve25519-dalek/std",
"digest/std",
"merlin/std",
"rand/std",
"sha3/std",
"byteorder/std",
"serde/std",
"subtle/std",
"zeroize/std",
"itertools/use_std",
"flate2/rust_backend",
]
simd_backend = ["curve25519-dalek/simd_backend"]
multicore = ["rayon"]
profile = []
profile = ["colored"]

115
README.md
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@ -1,33 +1,37 @@
# Spartan: High-speed zkSNARKs without trusted setup
![Rust](https://github.com/microsoft/Spartan/workflows/Rust/badge.svg)
[![](https://img.shields.io/crates/v/spartan.svg)]((https://crates.io/crates/spartan))
[![](https://img.shields.io/crates/v/spartan.svg)](<(https://crates.io/crates/spartan)>)
Spartan is a high-speed zero-knowledge proof system, a cryptographic primitive that enables a prover to prove a mathematical statement to a verifier without revealing anything besides the validity of the statement. This repository provides `libspartan,` a Rust library that implements a zero-knowledge succinct non-interactive argument of knowledge (zkSNARK), which is a type of zero-knowledge proof system with short proofs and fast verification times. The details of the Spartan proof system are described in our [paper](https://eprint.iacr.org/2019/550) published at [CRYPTO 2020](https://crypto.iacr.org/2020/). The security of the Spartan variant implemented in this library is based on the discrete logarithm problem in the random oracle model.
A simple example application is proving the knowledge of a secret s such that H(s) == d for a public d, where H is a cryptographic hash function (e.g., SHA-256, Keccak). A more complex application is a database-backed cloud service that produces proofs of correct state machine transitions for auditability. See this [paper](https://eprint.iacr.org/2020/758.pdf) for an overview and this [paper](https://eprint.iacr.org/2018/907.pdf) for details.
Note that this library has *not* received a security review or audit.
Note that this library has _not_ received a security review or audit.
## Highlights
We now highlight Spartan's distinctive features.
* **No "toxic" waste:** Spartan is a *transparent* zkSNARK and does not require a trusted setup. So, it does not involve any trapdoors that must be kept secret or require a multi-party ceremony to produce public parameters.
- **No "toxic" waste:** Spartan is a _transparent_ zkSNARK and does not require a trusted setup. So, it does not involve any trapdoors that must be kept secret or require a multi-party ceremony to produce public parameters.
* **General-purpose:** Spartan produces proofs for arbitrary NP statements. `libspartan` supports NP statements expressed as rank-1 constraint satisfiability (R1CS) instances, a popular language for which there exists efficient transformations and compiler toolchains from high-level programs of interest.
- **General-purpose:** Spartan produces proofs for arbitrary NP statements. `libspartan` supports NP statements expressed as rank-1 constraint satisfiability (R1CS) instances, a popular language for which there exists efficient transformations and compiler toolchains from high-level programs of interest.
* **Sub-linear verification costs:** Spartan is the first transparent proof system with sub-linear verification costs for arbitrary NP statements (e.g., R1CS).
- **Sub-linear verification costs:** Spartan is the first transparent proof system with sub-linear verification costs for arbitrary NP statements (e.g., R1CS).
* **Standardized security:** Spartan's security relies on the hardness of computing discrete logarithms (a standard cryptographic assumption) in the random oracle model. `libspartan` uses `ristretto255`, a prime-order group abstraction atop `curve25519` (a high-speed elliptic curve). We use [`curve25519-dalek`](https://docs.rs/curve25519-dalek) for arithmetic over `ristretto255`.
- **Standardized security:** Spartan's security relies on the hardness of computing discrete logarithms (a standard cryptographic assumption) in the random oracle model. `libspartan` uses `ristretto255`, a prime-order group abstraction atop `curve25519` (a high-speed elliptic curve). We use [`curve25519-dalek`](https://docs.rs/curve25519-dalek) for arithmetic over `ristretto255`.
* **State-of-the-art performance:**
Among transparent SNARKs, Spartan offers the fastest prover with speedups of 36–152× depending on the baseline, produces proofs that are shorter by 1.2–416×, and incurs the lowest verification times with speedups of 3.6–1326×. The only exception is proof sizes under Bulletproofs, but Bulletproofs incurs slower verification both asymptotically and concretely. When compared to the state-of-the-art zkSNARK with trusted setup, Spartans prover is 2× faster for arbitrary R1CS instances and 16× faster for data-parallel workloads.
- **State-of-the-art performance:**
Among transparent SNARKs, Spartan offers the fastest prover with speedups of 36–152× depending on the baseline, produces proofs that are shorter by 1.2–416×, and incurs the lowest verification times with speedups of 3.6–1326×. The only exception is proof sizes under Bulletproofs, but Bulletproofs incurs slower verification both asymptotically and concretely. When compared to the state-of-the-art zkSNARK with trusted setup, Spartans prover is 2× faster for arbitrary R1CS instances and 16× faster for data-parallel workloads.
### Implementation details
`libspartan` uses [`merlin`](https://docs.rs/merlin/) to automate the Fiat-Shamir transform. We also introduce a new type called `RandomTape` that extends a `Transcript` in `merlin` to allow the prover's internal methods to produce private randomness using its private transcript without having to create `OsRng` objects throughout the code. An object of type `RandomTape` is initialized with a new random seed from `OsRng` for each proof produced by the library.
## Examples
To import `libspartan` into your Rust project, add the following dependency to `Cargo.toml`:
```text
spartan = "0.7.1"
```
@ -36,11 +40,11 @@ The following example shows how to use `libspartan` to create and verify a SNARK
Some of our public APIs' style is inspired by the underlying crates we use.
```rust
# extern crate libspartan;
# extern crate merlin;
# use libspartan::{Instance, SNARKGens, SNARK};
# use merlin::Transcript;
# fn main() {
extern crate libspartan;
extern crate merlin;
use libspartan::{Instance, SNARKGens, SNARK};
use merlin::Transcript;
fn main() {
// specify the size of an R1CS instance
let num_vars = 1024;
let num_cons = 1024;
@ -66,16 +70,17 @@ Some of our public APIs' style is inspired by the underlying crates we use.
.verify(&comm, &inputs, &mut verifier_transcript, &gens)
.is_ok());
println!("proof verification successful!");
# }
}
```
Here is another example to use the NIZK variant of the Spartan proof system:
```rust
# extern crate libspartan;
# extern crate merlin;
# use libspartan::{Instance, NIZKGens, NIZK};
# use merlin::Transcript;
# fn main() {
extern crate libspartan;
extern crate merlin;
use libspartan::{Instance, NIZKGens, NIZK};
use merlin::Transcript;
fn main() {
// specify the size of an R1CS instance
let num_vars = 1024;
let num_cons = 1024;
@ -97,20 +102,22 @@ Here is another example to use the NIZK variant of the Spartan proof system:
.verify(&inst, &inputs, &mut verifier_transcript, &gens)
.is_ok());
println!("proof verification successful!");
# }
}
```
Finally, we provide an example that specifies a custom R1CS instance instead of using a synthetic instance
```rust
#![allow(non_snake_case)]
# extern crate curve25519_dalek;
# extern crate libspartan;
# extern crate merlin;
# use curve25519_dalek::scalar::Scalar;
# use libspartan::{InputsAssignment, Instance, SNARKGens, VarsAssignment, SNARK};
# use merlin::Transcript;
# use rand::rngs::OsRng;
# fn main() {
extern crate curve25519_dalek;
extern crate libspartan;
extern crate merlin;
use curve25519_dalek::scalar::Scalar;
use libspartan::{InputsAssignment, Instance, SNARKGens, VarsAssignment, SNARK};
use merlin::Transcript;
use rand::rngs::OsRng;
fn main() {
// produce a tiny instance
let (
num_cons,
@ -146,17 +153,17 @@ Finally, we provide an example that specifies a custom R1CS instance instead of
.verify(&comm, &assignment_inputs, &mut verifier_transcript, &gens)
.is_ok());
println!("proof verification successful!");
# }
}
# fn produce_tiny_r1cs() -> (
# usize,
# usize,
# usize,
# usize,
# Instance,
# VarsAssignment,
# InputsAssignment,
# ) {
fn produce_tiny_r1cs() -> (
usize,
usize,
usize,
usize,
Instance,
VarsAssignment,
InputsAssignment,
) {
// We will use the following example, but one could construct any R1CS instance.
// Our R1CS instance is three constraints over five variables and two public inputs
// (Z0 + Z1) * I0 - Z2 = 0
@ -247,36 +254,42 @@ Finally, we provide an example that specifies a custom R1CS instance instead of
assignment_vars,
assignment_inputs,
)
# }
}
```
For more examples, see [`examples/`](examples) directory in this repo.
## Building `libspartan`
Install [`rustup`](https://rustup.rs/)
Switch to nightly Rust using `rustup`:
```text
rustup default nightly
```
Clone the repository:
```text
git clone https://github.com/Microsoft/Spartan
cd Spartan
```
To build docs for public APIs of `libspartan`:
```text
cargo doc
```
To run tests:
```text
RUSTFLAGS="-C target_cpu=native" cargo test
```
To build `libspartan`:
```text
RUSTFLAGS="-C target_cpu=native" cargo build --release
```
@ -284,19 +297,41 @@ RUSTFLAGS="-C target_cpu=native" cargo build --release
> NOTE: We enable SIMD instructions in `curve25519-dalek` by default, so if it fails to build remove the "simd_backend" feature argument in `Cargo.toml`.
### Supported features
* `profile`: enables fine-grained profiling information (see below for its use)
- `std`: enables std features (enabled by default)
- `simd_backend`: enables `curve25519-dalek`'s simd feature (enabled by default)
- `profile`: enables fine-grained profiling information (see below for its use)
### WASM Support
`libspartan` depends upon `rand::OsRng` (internally uses `getrandom` crate), it has out of box support for `wasm32-wasi`.
For the target `wasm32-unknown-unknown` disable default features for spartan
and add direct dependency on `getrandom` with `wasm-bindgen` feature enabled.
```toml
[dependencies]
spartan = { version = "0.7", default-features = false }
# since spartan uses getrandom(rand's OsRng), we need to enable 'wasm-bindgen'
# feature to make it feed rand seed from js/nodejs env
# https://docs.rs/getrandom/0.1.16/getrandom/index.html#support-for-webassembly-and-asmjs
getrandom = { version = "0.1", features = ["wasm-bindgen"] }
```
## Performance
### End-to-end benchmarks
`libspartan` includes two benches: `benches/nizk.rs` and `benches/snark.rs`. If you report the performance of Spartan in a research paper, we recommend using these benches for higher accuracy instead of fine-grained profiling (listed below).
To run end-to-end benchmarks:
```text
RUSTFLAGS="-C target_cpu=native" cargo bench
```
### Fine-grained profiling
Build `libspartan` with `profile` feature enabled. It creates two profilers: `./target/release/snark` and `./target/release/nizk`.
These profilers report performance as depicted below (for varying R1CS instance sizes). The reported

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@ -27,7 +27,7 @@ fn nizk_prove_benchmark(c: &mut Criterion) {
let gens = NIZKGens::new(num_cons, num_vars, num_inputs);
let name = format!("NIZK_prove_{}", num_vars);
let name = format!("NIZK_prove_{num_vars}");
group.bench_function(&name, move |b| {
b.iter(|| {
let mut prover_transcript = Transcript::new(b"example");
@ -61,7 +61,7 @@ fn nizk_verify_benchmark(c: &mut Criterion) {
let mut prover_transcript = Transcript::new(b"example");
let proof = NIZK::prove(&inst, vars, &inputs, &gens, &mut prover_transcript);
let name = format!("NIZK_verify_{}", num_cons);
let name = format!("NIZK_verify_{num_cons}");
group.bench_function(&name, move |b| {
b.iter(|| {
let mut verifier_transcript = Transcript::new(b"example");

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@ -22,7 +22,7 @@ fn snark_encode_benchmark(c: &mut Criterion) {
let gens = SNARKGens::new(num_cons, num_vars, num_inputs, num_cons);
// produce a commitment to R1CS instance
let name = format!("SNARK_encode_{}", num_cons);
let name = format!("SNARK_encode_{num_cons}");
group.bench_function(&name, move |b| {
b.iter(|| {
SNARK::encode(black_box(&inst), black_box(&gens));
@ -51,7 +51,7 @@ fn snark_prove_benchmark(c: &mut Criterion) {
let (comm, decomm) = SNARK::encode(&inst, &gens);
// produce a proof
let name = format!("SNARK_prove_{}", num_cons);
let name = format!("SNARK_prove_{num_cons}");
group.bench_function(&name, move |b| {
b.iter(|| {
let mut prover_transcript = Transcript::new(b"example");
@ -100,7 +100,7 @@ fn snark_verify_benchmark(c: &mut Criterion) {
);
// verify the proof
let name = format!("SNARK_verify_{}", num_cons);
let name = format!("SNARK_verify_{num_cons}");
group.bench_function(&name, move |b| {
b.iter(|| {
let mut verifier_transcript = Transcript::new(b"example");

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@ -1,8 +1,8 @@
use super::group::{GroupElement, VartimeMultiscalarMul, GROUP_BASEPOINT_COMPRESSED};
use super::scalar::Scalar;
use digest::XofReader;
use digest::{ExtendableOutput, Input};
use sha3::Shake256;
use std::io::Read;
#[derive(Debug)]
pub struct MultiCommitGens {
@ -21,7 +21,7 @@ impl MultiCommitGens {
let mut gens: Vec<GroupElement> = Vec::new();
let mut uniform_bytes = [0u8; 64];
for _ in 0..n + 1 {
reader.read_exact(&mut uniform_bytes).unwrap();
reader.read(&mut uniform_bytes);
gens.push(GroupElement::from_uniform_bytes(&uniform_bytes));
}

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@ -1,17 +1,26 @@
use core::fmt::Debug;
use thiserror::Error;
use core::{
fmt::Display,
fmt::{self, Debug},
};
#[derive(Error, Debug)]
#[derive(Debug, Default)]
pub enum ProofVerifyError {
#[error("Proof verification failed")]
#[default]
InternalError,
#[error("Compressed group element failed to decompress: {0:?}")]
DecompressionError([u8; 32]),
}
impl Default for ProofVerifyError {
fn default() -> Self {
ProofVerifyError::InternalError
impl Display for ProofVerifyError {
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
match &self {
ProofVerifyError::DecompressionError(bytes) => write!(
f,
"Compressed group element failed to decompress: {bytes:?}",
),
ProofVerifyError::InternalError => {
write!(f, "Proof verification failed",)
}
}
}
}

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@ -90,9 +90,9 @@ impl R1CSInstance {
B: &[(usize, usize, Scalar)],
C: &[(usize, usize, Scalar)],
) -> R1CSInstance {
Timer::print(&format!("number_of_constraints {}", num_cons));
Timer::print(&format!("number_of_variables {}", num_vars));
Timer::print(&format!("number_of_inputs {}", num_inputs));
Timer::print(&format!("number_of_constraints {num_cons}"));
Timer::print(&format!("number_of_variables {num_vars}"));
Timer::print(&format!("number_of_inputs {num_inputs}"));
Timer::print(&format!("number_non-zero_entries_A {}", A.len()));
Timer::print(&format!("number_non-zero_entries_B {}", B.len()));
Timer::print(&format!("number_non-zero_entries_C {}", C.len()));
@ -157,9 +157,9 @@ impl R1CSInstance {
num_vars: usize,
num_inputs: usize,
) -> (R1CSInstance, Vec<Scalar>, Vec<Scalar>) {
Timer::print(&format!("number_of_constraints {}", num_cons));
Timer::print(&format!("number_of_variables {}", num_vars));
Timer::print(&format!("number_of_inputs {}", num_inputs));
Timer::print(&format!("number_of_constraints {num_cons}"));
Timer::print(&format!("number_of_variables {num_vars}"));
Timer::print(&format!("number_of_inputs {num_inputs}"));
let mut csprng: OsRng = OsRng;

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@ -10,7 +10,7 @@ use core::convert::TryFrom;
use core::fmt;
use core::iter::{Product, Sum};
use core::ops::{Add, AddAssign, Mul, MulAssign, Neg, Sub, SubAssign};
use rand_core::{CryptoRng, RngCore};
use rand::{CryptoRng, RngCore};
use serde::{Deserialize, Serialize};
use subtle::{Choice, ConditionallySelectable, ConstantTimeEq, CtOption};
use zeroize::Zeroize;
@ -813,7 +813,7 @@ mod tests {
);
assert_eq!(
format!("{:?}", R2),
"0x1824b159acc5056f998c4fefecbc4ff55884b7fa0003480200000001fffffffe"
"0x0ffffffffffffffffffffffffffffffec6ef5bf4737dcf70d6ec31748d98951d"
);
}