# zksk’s docs¶

Zero-Knowledge Swiss Knife: Python library for prototyping composable zero-knowledge proofs in the discrete-log setting.

Let’s say Peggy commits to a secret bit and wants to prove to Victor in zero knowledge that she knows this bit—that is, without revealing it. In Camenisch-Stadler notation, we can write:

To implement this zero-knowledge proof, Peggy will run:

from zksk import Secret, DLRep
from zksk import utils

# Setup: Peggy and Victor agree on two group generators.
G, H = utils.make_generators(num=2, seed=42)
# Setup: generate a secret randomizer.
r = Secret(utils.get_random_num(bits=128))

# This is Peggy's secret bit.
top_secret_bit = 1

# A Pedersen commitment to the secret bit.
C = top_secret_bit * G + r.value * H

# Peggy's definition of the proof statement, and proof generation.
# (The first or-clause corresponds to the secret value 0, and the second to the value 1. Because
# the real value of the bit is 1, the clause that corresponds to zero is marked as simulated.)
stmt = DLRep(C, r * H, simulated=True) | DLRep(C - G, r * H)
zk_proof = stmt.prove()


Victor will receive the commitment C and zk_proof from Peggy, and run this to verify the proof:

from zksk import Secret, DLRep

# Setup: get the agreed group generators.
G, H = utils.make_generators(num=2, seed=42)
# Setup: define a randomizer with an unknown value.
r = Secret()

stmt = DLRep(C, r * H) | DLRep(C - G, r * H)
assert stmt.verify(zk_proof)


Victor is now convinced that Peggy knows the committed bit.