Files
mukul975 efca3ec611 feat: add NIST CSF 2.0 nist_csf field to all 754 cybersecurity skills
Mapped every skill to NIST CSF 2.0 subcategory IDs (GV/ID/PR/DE/RS/RC functions)
based on subdomain and content analysis. Restores 11 skills corrupted during
prior rebase, re-enriching with ATLAS, D3FEND, NIST AI RMF, and CSF 2.0 fields.

All 754 skills now carry structured mappings for all 5 security frameworks:
- MITRE ATT&CK (in tags)
- MITRE ATLAS v5.5 (atlas_techniques)
- MITRE D3FEND v1.3 (d3fend_techniques)
- NIST AI RMF 1.0 (nist_ai_rmf)
- NIST CSF 2.0 (nist_csf)
2026-04-06 11:17:40 +02:00

3.1 KiB

name, description, domain, subdomain, tags, version, author, license, nist_csf
name description domain subdomain tags version author license nist_csf
implementing-zero-knowledge-proof-for-authentication 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 cybersecurity cryptography
cryptography
zero-knowledge-proof
authentication
privacy
zkp
1.0 mahipal Apache-2.0
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

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