109 lines
2.9 KiB
Python

from keum import grumpkin, PrimeFiniteField
import poseidon
# !Important! The crypto primitives here must be in agreement with the proving system
# E.g. if you are using noir with the Barretenberg, we must use the Grumpkin curve.
Point = grumpkin.AffineWeierstrass
Field = grumpkin.Fq
class Field(PrimeFiniteField):
ORDER = poseidon.prime_64
def poseidon_grumpkin_field():
# TODO: These parameters are made up.
# return poseidon.Poseidon(
# p=Field.ORDER,
# security_level=128,
# alpha=5,
# input_rate=3,
# t=9,
# )
h, _ = poseidon.case_simple()
# h, _ = poseidon.case_neptune()
# h = poseidon.Poseidon(
# p=Field.ORDER,
# security_level=128,
# alpha=5,
# input_rate=3,
# t=9,
# )
# TODO: this is hacks on hacks to make poseidon take in arbitrary input length.
# Fix is to implement a sponge as described in section 2.1 of
# https://eprint.iacr.org/2019/458.pdf
def inner(data):
assert all(
isinstance(d, Field) for d in data
), f"{data}\n{[type(d) for d in data]}"
data = [d.v for d in data]
digest = 0
for i in range(0, len(data), h.input_rate - 1):
digest = h.run_hash([digest, *data[i : i + h.input_rate - 1]])
return digest
return inner
POSEIDON = poseidon_grumpkin_field()
def prf(domain, *elements) -> Field:
return Field(int(POSEIDON([*_str_to_vec(domain), *elements])))
def hash_to_curve(domain, *elements) -> Point:
# HACK: we don't currently have a proper hash_to_curve implementation
# so we hack the Point.random() function.
#
# Point.random() calls into the global `random` module to generate a
# point. We will seed the random module with the result of hashing the
# elements and then call Point.random() to retreive the point
# corresponding to the mentioned elements.
r = prf(f"HASH_TO_CURVE_{domain}", *elements)
import random
random.seed(r.v)
return Point.random()
def comm(*elements):
"""
Returns a commitment to the sequence of elements.
The commitmtent can be opened at index 0..len(elements)
"""
raise NotImplementedError()
def pederson_commit(value: Field, blinding: Field, domain: Point) -> Point:
return Point.generator().mul(value) + domain.mul(blinding)
def merkle_root(data) -> Field:
data = _pad_to_power_of_2(data)
nodes = [CRH(d) for d in data]
while len(nodes) > 1:
nodes = [CRH(nodes[i], nodes[i + 1]) for i in range(0, len(nodes), 2)]
return nodes[0]
def _pad_to_power_of_2(data):
import math
max_lower_bound = int(math.log2(len(data)))
if 2**max_lower_bound == len(data):
return data
to_pad = 2 ** (max_lower_bound + 1) - len(data)
return data + [Field.zero()] * to_pad
def _str_to_vec(s):
return [Field(ord(c)) for c in s]