mirror of
https://github.com/SHOGGOTH-SECTOR/sica-fondt.git
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24f816b6a3
Place useful parts of the surrounding repos into sica-fondt by layer, per the
body model (Ada = membrane; brain/endocrine/capabilities/knowledge non-Ada):
- brain/ LLM reasoning + providers (dapr, hermes, MoMoA)
- capabilities/ REPRAG sidecars: hermes tools/skills, dapr tools, parallel
dispatch, A51 channels, and the OSINT cluster
- knowledge/ LORAG corpus: 754 cyber-skills, agency personas, secure-coding,
MITRE ATT&CK data
- reference/ defensive threat-reference (C3, shhbruh doc) + AdaYaml parser
License handling: AGPL sources (worldosint, advanced_evolution, mercury,
Reticulum) and GPL DeTTECT are SPEC-only clean-room/port descriptions — no
copyleft code copied. MIT/Apache/data parts copied as working trees.
Safety: shhbruh escape/persistence material and C3 covert-C2 kept as reference
only, not wired into the running organism. See CONSOLIDATION.md.
https://claude.ai/code/session_01UehUqEXXJJCsHoA4voCU5c
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3.1 KiB
| 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 |
|
1.0 | mahipal | Apache-2.0 |
|
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
- Setup: Public generator g, prime p, q (order of g)
- Registration: Prover computes y = g^x mod p (public key from secret x)
- Commitment: Prover sends t = g^r mod p (random r)
- Challenge: Verifier sends random c
- Response: Prover sends s = r + c*x mod q
- 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