implementing-zero-knowledge-proof-for-authentication

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Zero-Knowledge Proofs (ZKPs) allow a prover to demonstrate knowledge of a secret (such as a password or private key) without revealing the secret itself. This skill implements the Schnorr identificati

xalgord By xalgord schedule Updated 6/6/2026

name: implementing-zero-knowledge-proof-for-authentication description: Zero-Knowledge Proofs (ZKPs) allow a prover to demonstrate knowledge of a secret (such as a password or private key) without revealing the secret itself. This skill implements the Schnorr identificati domain: cybersecurity subdomain: cryptography tags:

  • cryptography
  • zero-knowledge-proof
  • authentication
  • privacy
  • zkp version: '1.0' author: mahipal license: Apache-2.0 nist_csf:
  • PR.DS-01
  • PR.DS-02
  • PR.DS-10

Implementing Zero-Knowledge Proof for Authentication

Overview

Zero-Knowledge Proofs (ZKPs) allow a prover to demonstrate knowledge of a secret (such as a password or private key) without revealing the secret itself. This skill implements the Schnorr identification protocol and a simplified ZKPP (Zero-Knowledge Password Proof) using the discrete logarithm problem, enabling authentication where the server never learns the user's password.

When to Use

  • When deploying or configuring implementing zero knowledge proof for authentication capabilities in your environment
  • When establishing security controls aligned to compliance requirements
  • When building or improving security architecture for this domain
  • When conducting security assessments that require this implementation

Common Misconfigurations & Verification

  • Predictable challenge / nonce reuse: in Schnorr, reusing the commitment randomness r across two challenges leaks the secret x via x = (s1 - s2)/(c1 - c2). Generate r from a CSPRNG per proof and never reuse it. Verify two runs produce different t values.
  • Weak Fiat-Shamir transcript: the non-interactive challenge must hash the full transcript including the public key and commitment (c = H(g, y, t, msg)), not just t — otherwise proofs are forgeable or transferable. Use a collision-resistant hash.
  • Verifier-chosen challenge skipped / replay: without binding to a fresh server nonce or message, a captured transcript can be replayed. Include a server-supplied challenge or message and reject duplicates.
  • Insecure group parameters: use a safe prime p and prime-order subgroup q; validate that y lies in the correct subgroup to avoid small-subgroup attacks.
  • Secret transmitted or logged: confirm the server never receives or stores x.
  • Mandatory tests: (1) honest prover always verifies (completeness); (2) a random/forged response without x fails verification (soundness); (3) the server transcript never contains the secret (zero-knowledge); (4) repeated authentications yield distinct transcripts; (5) a replayed transcript is rejected.

Prerequisites

  • Familiarity with cryptography concepts and tools
  • Access to a test or lab environment for safe execution
  • Python 3.8+ with required dependencies installed
  • Appropriate authorization for any testing activities

Objectives

  • Implement Schnorr's identification protocol for ZKP authentication
  • Build a non-interactive ZKP using Fiat-Shamir heuristic
  • Implement zero-knowledge password proof (ZKPP)
  • Demonstrate completeness, soundness, and zero-knowledge properties
  • Compare ZKP authentication with traditional password verification

Key Concepts

ZKP Properties

Property Description
Completeness Honest prover always convinces honest verifier
Soundness Dishonest prover cannot convince verifier (except negligible probability)
Zero-Knowledge Verifier learns nothing beyond the statement's truth

Schnorr Protocol

  1. Setup: Public generator g, prime p, q (order of g)
  2. Registration: Prover computes y = g^x mod p (public key from secret x)
  3. Commitment: Prover sends t = g^r mod p (random r)
  4. Challenge: Verifier sends random c
  5. Response: Prover sends s = r + c*x mod q
  6. Verify: Check g^s == t * y^c mod p

Security Considerations

  • Use cryptographically secure random number generators
  • Challenge must be unpredictable (from verifier's perspective)
  • For non-interactive proofs, use Fiat-Shamir with collision-resistant hash
  • ZKP alone does not provide forward secrecy; combine with TLS

Validation Criteria

  • Honest prover always verifies successfully (completeness)
  • Random response without secret does not verify (soundness)
  • Server never receives the secret value
  • Non-interactive proof is verifiable offline
  • Multiple authentications produce different transcripts
  • Protocol resists replay attacks
Install via CLI
npx skills add https://github.com/xalgord/xalgorix --skill implementing-zero-knowledge-proof-for-authentication
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