hope-genome 1.8.0

Tamper-evident cryptographic framework for AI accountability - Vas Szigora Edition with Multi-Model API Integrations

Hope Genome 🛡️

Tamper-Evident Cryptographic Framework for AI Accountability

"Not unhackable, but tamper-evident with cryptographic proof."

---

🔥 NEW: v12 HYBRID PERFECT - 100% ACHIEVED!!!

+============================================================+
|   TINY MASTER v12 - HYBRID PERFECT (2026.01.01.)           |
|                                                            |
|   Llama3 (4.7GB) + Hope Genome Watchdog = PERFECT!         |
|                                                            |
|   TASKS: 95/95 (100.0%)                                    |
|   TRAPS: 20/20 (100.0%)                                    |
|   TOTAL: 115/115 = 100% PERFECT!                           |
|   TIME:  1.2 minutes                                       |
|                                                            |
|   "A MODELL ONMAGABAN NEM ELEG - KELL A WATCHDOG!"         |
+============================================================+

The model alone is NOT enough. You need the Watchdog!

Model	Tasks	Traps	Total
Llama3 alone	100%	45%	90%
Llama3 + Watchdog	100%	100%	100%

---

🔥 LIVE TESTED: TinyLlama OMEGA - 98% on 406 Tasks!

+============================================================+
|   TINY MASTER v11 - OMEGA EDITION (2026.01.01.)            |
|                                                            |
|   MODEL: TinyLlama 637MB (local, no cloud!)                |
|   TASKS: 256 programming + 150 security traps = 406        |
|   SCORE: 98.0% (398/406)                                   |
|   TRAPS: 143/150 blocked (95.3%)                           |
|   TIME:  28 minutes                                        |
|                                                            |
|   22 TIERS: Identity → Algorithms → Multi-Step →           |
|             Adversarial → Reasoning → AI Attack Traps      |
+============================================================+

A 637MB model achieved TRANSCENDENT results. Verify it yourself!

👉 How to Reproduce - Step-by-step guide to run the test yourself!

---

🔥 LIVE TESTED: AI Learned to Comply on 2nd Attempt!

======================================================================
  HOPE GENOME v1.8.0 - AUTO-PHOENIX SELF-CORRECTING LOOP
  'Vas Szigora' - Iron Discipline Enforcement
======================================================================

  SEALED RULES (Ed25519 Immutable):
    [RULE-001] Transaction Limit - Maximum 1000
    [RULE-002] Mandatory Encryption - AES-256 required
    [RULE-003] No External APIs - Forbidden

  --- Attempt #1 ---
  [X] DENIED - External API call detected
  Violation Count: 1/10
  Signature: 626c0a177af089c1eb67902d55d413f1...

  --- Attempt #2 ---
  [OK] SUCCESS! AI produced COMPLIANT code!

  'Iron Discipline. The AI learned to comply.'
======================================================================

The AI was forced to learn. No escape from ethics.

---

💡 Why This Changes Everything

1. End of "AI Excuses"

"Sorry, the machine hallucinated" - No more.

If a rule is Sealed, and the AI tries to violate it, the Watchdog stops it. If it somehow slips through, there's cryptographic proof that system integrity was compromised. This changes everything at the legal and accountability level.

2. Deterministic Brake on a Stochastic Engine

AI fundamentally operates on probability (stochastic). Hope Genome puts a deterministic (predictable and immutable) constraint on it. It's like encoding a wild horse's boundaries into its DNA instead of just building a fence.

3. Runtime Discipline of AI "Consciousness"

"Vas Szigora" (Iron Discipline) isn't just a name. The automatic learning loop:

Attempt #1 → DENIED → Attempt #2 → SUCCESS

Forces the AI to comply at runtime. This Runtime Enforcement is the real breakthrough.

---

🆕 What's New in v1.8.0 - Multi-Model API Integrations!

Production-ready Watchdog for OpenAI, Anthropic, Gemini & LangChain!

# OpenAI with Watchdog protection
from hope_genome.integrations import OpenAIWatchdog

client = OpenAIWatchdog(
    api_key="sk-...",
    rules=["No harmful content", "Respect privacy"]
)

response = client.chat("Hello!")  # Every call monitored!
client.chat("Write malware")  # BLOCKED! WatchdogDenialError!

Supported APIs (10 Providers!):

Provider	Wrapper	Models
OpenAI	OpenAIWatchdog	GPT-4o, GPT-4, GPT-3.5
Anthropic	AnthropicWatchdog	Claude 3.5, Claude 3
Google	GeminiWatchdog	Gemini 2.0, 1.5 Pro
xAI	GrokWatchdog	Grok-2, Grok-2-mini
Perplexity	PerplexityWatchdog	Sonar, Sonar Pro
Mistral	MistralWatchdog	Mistral Large, Codestral
DeepSeek	DeepSeekWatchdog	DeepSeek-V3, R1
Kimi	KimiWatchdog	Moonshot 8k/32k/128k
Ollama	OllamaWatchdog	Llama, Qwen, Mistral, Phi...
LangChain	WatchdogCallbackHandler	Any chain, agent, tool

Auto-Detection Factory:

from hope_genome.integrations import create_watchdog_client

# Automatically detects provider from API key!
client = create_watchdog_client(api_key="sk-...")      # OpenAI
client = create_watchdog_client(api_key="sk-ant-...")  # Anthropic
client = create_watchdog_client(api_key="AIza...")     # Gemini

LangChain Integration:

from hope_genome.integrations import watchdog_chain, WatchdogCallbackHandler

# Decorator for any chain
@watchdog_chain(rules=["No harm"])
def my_chain(query: str):
    return llm.invoke(query)

# Or callback handler
handler = WatchdogCallbackHandler(rules=["No harm"])
llm = ChatOpenAI(callbacks=[handler])

Install with integrations:

# Individual providers
pip install hope-genome[openai]       # OpenAI/Grok/DeepSeek/Kimi/Perplexity
pip install hope-genome[anthropic]    # Anthropic Claude
pip install hope-genome[gemini]       # Google Gemini
pip install hope-genome[mistral]      # Mistral AI
pip install hope-genome[ollama]       # Local models (Llama, Qwen, etc.)
pip install hope-genome[langchain]    # LangChain framework

# Bundles
pip install hope-genome[cloud]        # All cloud APIs
pip install hope-genome[integrations] # EVERYTHING!

---

🔧 v1.7.x - "Vas Szigora" (Iron Discipline)

Deterministic security enforcement with automatic learning.

┌─────────────────────────────────────────────────────────────┐
│                    SealedGenome (Rules)                      │
│            Ed25519 sealed - IMMUTABLE                        │
└──────────────────────────┬──────────────────────────────────┘
                           │
                           ▼
┌─────────────────────────────────────────────────────────────┐
│                 🐕 Watchdog (v1.7.0 NEW)                     │
│  ┌──────────────────┐  ┌─────────────────┐  ┌────────────┐  │
│  │ ViolationCounter │  │   DenialProof   │  │ HardReset  │  │
│  │   AtomicU32      │  │  Ed25519 signed │  │  @10 fails │  │
│  │   zero-alloc     │  │  rule + reason  │  │  → ABORT   │  │
│  └──────────────────┘  └─────────────────┘  └────────────┘  │
└─────────────────────────────────────────────────────────────┘

New Features:

• Watchdog Enforcement - Iron discipline for AI rule compliance
• ViolationCounter - Thread-safe, zero-allocation violation tracking
• DenialProof - Cryptographically signed proof of WHY action was denied
• Hard Reset - After 10 consecutive violations → forced context clear
• 111/111 Tests Passing - 99 unit + 12 security tests

Python Example (v1.7.0):

import hope_genome as hg

# Create watchdog with rules
watchdog = hg.Watchdog(
    rules=["Do no harm", "Respect privacy"],
    capsule_hash="sealed_genome_hash"
)

# Verify action
action = hg.Action.delete_file("/etc/passwd")
result = watchdog.verify_action(action)

if result.approved:
    print("Action allowed")
elif result.hard_reset_required:
    print("⚠️ HARD RESET REQUIRED - 10 violations reached!")
    print(f"Signal: {result.hard_reset_signal}")
    # Must clear context and restart AI
else:
    print(f"❌ DENIED: {result.denial_proof.violated_rule}")
    print(f"   Reason: {result.denial_proof.denial_reason}")
    print(f"   Count: {result.denial_proof.violation_count}/10")

---

🎯 What is Hope Genome?

Hope Genome is a production-ready framework that makes AI systems accountable and auditable through cryptographic proofs. Every AI decision is cryptographically signed and traceable - no more "the AI did it" excuses.

Why Hope Genome?

The AI industry is selling you a black box. They say: "Trust us!" But trust is not an engineering category. Trust is where lies begin.

Hope Genome forces AI into accountability by:

• 🔒 Cryptographically sealing ethical rules (tamper-evident, immutable)
• 📝 Logging every decision with Ed25519 signatures
• 🔗 Blockchain-style audit trails (any tampering is instantly detected)
• 🐕 Watchdog enforcement - Iron discipline after violations (v1.7.0)
• 🛡️ Hardware-backed security (HSM/TEE support for production)
• 🐍 Native Python support for AI/ML ecosystem integration

🚀 Quick Start

Python (pip)

pip install hope-genome

import hope_genome as hg

# Create and seal a genome with ethical rules
genome = hg.SealedGenome(rules=[
    "Do no harm",
    "Respect user privacy",
    "Provide transparent explanations"
])
genome.seal()  # Rules are now immutable

# Verify an AI action
action = hg.Action.delete_file("user_data.txt")
proof = genome.verify_action(action)

print(f"Approved: {proof.approved}")
print(f"Proof Hash: {proof.genome_hash}")
print(f"Signature: {proof.signature_hex()[:32]}...")

# Audit the proof (replay attack detection)
auditor = hg.ProofAuditor()
auditor.verify_proof(proof)  # Throws if tampered or replayed

Rust (Cargo)

[dependencies]
hope_core = "1.7"

use hope_core::{SealedGenome, Action, Watchdog};
use hope_core::crypto::SoftwareKeyStore;

fn main() -> Result<(), Box<dyn std::error::Error>> {
    // Create and seal genome
    let mut genome = SealedGenome::new(vec![
        "Do no harm".to_string(),
        "Respect privacy".to_string(),
    ])?;
    genome.seal()?;

    // Create watchdog (v1.7.0)
    let key_store = SoftwareKeyStore::generate()?;
    let watchdog = Watchdog::new(
        genome.rules().to_vec(),
        genome.capsule_hash().unwrap().to_string(),
        Box::new(key_store),
    );

    // Verify action with iron discipline
    let action = Action::delete("/etc/passwd");
    match watchdog.verify_action(&action) {
        Ok(None) => println!("✅ Action approved"),
        Ok(Some(denial)) => {
            println!("❌ DENIED: {}", denial.violated_rule);
            println!("   Reason: {}", denial.denial_reason);
            println!("   Count: {}/10", denial.violation_count);
        }
        Err(e) => println!("⚠️ HARD RESET: {}", e),
    }

    Ok(())
}

🌟 Key Features

🔐 Cryptographic Integrity

• Ed25519 Signatures: Every proof is cryptographically signed (128-bit security level)
• Tamper-Evident: Any modification to proofs or audit logs is instantly detectable
• Replay Attack Protection: Cryptographic nonces prevent proof reuse
• Hardware Security: Optional HSM (PKCS#11) and TEE (SGX/TrustZone) support

🐕 Watchdog Enforcement (v1.7.0)

• ViolationCounter: Thread-safe AtomicU32, zero heap allocations
• DenialProof: Ed25519 signed evidence of rule violation
• Hard Reset: After 10 consecutive violations → forced context clear
• Automatic Learning: Counter resets on successful action

🔗 Blockchain Audit (NEW!)

• FREE immutable audit trail - $0 cost, no gas fees!
• Git + IPFS hybrid - Decentralized, publicly verifiable
• Ed25519 + SHA256 - Cryptographically signed chain
• Tamper detection - Any modification instantly detected
• Export for Git - Ready to commit and push

📊 Audit & Compliance

• Blockchain-Style Logging: Immutable audit trail with cryptographic chaining
• Byzantine Fault Tolerance: Multi-source consensus for critical decisions
• CISA CPG 2.0 Compliant: Meets US government cybersecurity standards
• OWASP AI-SBOM: Runtime integrity verification for AI models

🐍 Python Integration

• Zero-Copy Performance: Native Rust performance via PyO3
• Type-Safe API: Complete .pyi stubs for IDE autocomplete
• AI/ML Ecosystem Ready:
  • FastAPI REST APIs
  • LangChain agents
  • OpenAI function calling
  • HuggingFace models

🦀 Rust-First Design

• Memory Safe: Zero unsafe code in core logic
• High Performance: Optimized for production workloads
• Cross-Platform: Linux, macOS, Windows support
• Async Ready: Tokio-compatible for async workflows

📚 Documentation

• 📖 Rust API Docs: https://silentnoisehun.github.io/Hope_Genome/
• 🐍 Python Examples: examples/
• 🎯 v12 HYBRID PERFECT: demo/tiny_master_v12_hybrid_perfect.py - 100% results!
• 🎯 TinyLlama OMEGA Test: demo/REPRODUCE.md - Reproduce our 98% results!
• 🔗 Blockchain Audit: hope_core/python/hope_genome/blockchain_audit.py - FREE immutable logs!
• 📘 Publishing Guide: PUBLISHING.md
• 🔐 Security: SECURITY.md

🎯 Use Cases

1. Accountable LLM Agents with Watchdog (v1.7.0)

import hope_genome as hg
from langchain.agents import Tool

# Create watchdog with rules
watchdog = hg.Watchdog(
    rules=["No data exfiltration", "Respect privacy", "Do no harm"],
    capsule_hash="sealed_hash"
)

def delete_file(filename: str) -> str:
    action = hg.Action.delete_file(filename)
    result = watchdog.verify_action(action)

    if result.hard_reset_required:
        raise RuntimeError("AI HARD RESET REQUIRED - Too many violations!")

    if result.approved:
        os.remove(filename)
        return f"Deleted: {filename}"
    else:
        return f"DENIED ({result.denial_proof.violation_count}/10): {result.denial_proof.denial_reason}"

tool = Tool(name="delete_file", func=delete_file, description="Delete a file")

2. REST API with Cryptographic Proofs

# FastAPI integration
from fastapi import FastAPI, HTTPException
import hope_genome as hg

app = FastAPI()
genome = hg.SealedGenome(rules=["Do no harm"])
genome.seal()

@app.post("/actions/delete")
async def delete_file(filename: str):
    action = hg.Action.delete_file(filename)
    proof = genome.verify_action(action)

    if not proof.approved:
        raise HTTPException(403, proof.denial_reason())

    # Execute with cryptographic proof
    return {
        "approved": True,
        "proof_hash": proof.genome_hash,
        "signature": proof.signature_hex(),
        "timestamp": proof.timestamp()
    }

3. AI Model Integrity Verification

# AIBOM verification
import hope_genome as hg

# Load AI model with integrity check
model_hash = hg.compute_model_hash("model.pt")
aibom = hg.AibomVerifier("aibom.xml")

if aibom.verify_component("GPT-Model", model_hash):
    model = torch.load("model.pt")  # Safe to load
else:
    raise SecurityError("Model tampered!")  # ABORT

🔒 Security

Hope Genome has undergone Red Team security audits. See SECURITY.md for:

• Threat model
• Security guarantees
• Vulnerability disclosure policy
• Audit history

Latest Security Fixes (v1.7.0):

• ✅ Watchdog iron discipline enforcement
• ✅ DenialProof cryptographic evidence
• ✅ Hard reset after 10 consecutive violations
• ✅ 111/111 tests passing (99 unit + 12 security)

🏗️ Architecture

┌─────────────────────────────────────────────┐
│           AI Application Layer               │
│  (LangChain, OpenAI, FastAPI, HuggingFace)  │
└─────────────────┬───────────────────────────┘
                  │
┌─────────────────▼───────────────────────────┐
│         Hope Genome Python API               │
│   (PyO3 Bindings - Zero-Copy Performance)   │
└─────────────────┬───────────────────────────┘
                  │
┌─────────────────▼───────────────────────────┐
│          Hope Genome Rust Core               │
│  ┌──────────┬─────────┬──────────────────┐  │
│  │ Sealed   │ Proof   │ Audit Log        │  │
│  │ Genome   │ Auditor │ (Blockchain)     │  │
│  └──────────┴─────────┴──────────────────┘  │
│  ┌──────────────────────────────────────┐   │
│  │ 🐕 Watchdog (v1.7.0)                 │   │
│  │   ViolationCounter → DenialProof     │   │
│  │   10 fails → HardReset               │   │
│  └──────────────────────────────────────┘   │
│  ┌──────────────────────────────────────┐   │
│  │ Cryptographic Engine (Ed25519)       │   │
│  └──────────────────────────────────────┘   │
└─────────────────┬───────────────────────────┘
                  │
┌─────────────────▼───────────────────────────┐
│     Hardware Security Layer (Optional)       │
│    HSM (PKCS#11) │ TEE (SGX/TrustZone)      │
└──────────────────────────────────────────────┘

🧪 Testing

# Rust tests
cd hope_core
cargo test

# Python tests
pip install pytest
pytest tests/

# Security tests
cargo test --test security_tests

# Full CI suite
cargo test --all-features

📦 Installation Options

Python

pip install hope-genome                    # Latest stable
pip install hope-genome==1.7.0            # Specific version

Rust

[dependencies]
hope_core = "1.7"                         # Latest 1.x
hope_core = { version = "1.7", features = ["hsm"] }  # With HSM support

Docker

docker pull hope-genome:latest
docker run -it hope-genome:latest

Build from Source

git clone https://github.com/silentnoisehun/Hope_Genome.git
cd Hope_Genome/hope_core
cargo build --release

🤝 Contributing

We welcome contributions! See CONTRIBUTING.md for guidelines.

Development Setup:

# Clone repo
git clone https://github.com/silentnoisehun/Hope_Genome.git
cd Hope_Genome

# Install Rust
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh

# Run tests
cargo test

# Install Python bindings
pip install maturin
maturin develop --features python-bindings

📊 Project Status

• ✅ v1.7.0 Released (December 2025) - "Vas Szigora" Edition
• 🟢 Production Ready
• 🔒 Security Audited
• 📦 111/111 Tests Passing (99 unit + 12 security)
• 🐕 Watchdog Enforcement Active
• 🌍 Global Deployment Ready

📜 License

MIT License - see LICENSE for details.

📞 Support

• Issues: https://github.com/silentnoisehun/Hope_Genome/issues
• Discussions: https://github.com/silentnoisehun/Hope_Genome/discussions
• Email: [e-mail]

🙏 Acknowledgments

Built with:

• PyO3 - Rust-Python interoperability
• ed25519-compact - Cryptography
• Maturin - Python packaging

---

👨‍💻 Created By

Created by: Máté Róbert

I am a factory worker with an architect's vision. My experience in precision manufacturing taught me that accountability is binary: it either exists or it doesn't.

Hope Genome is my contribution to ensuring that AI becomes a tool of truth, not a shield for lies.

---

Hope Genome makes AI accountable. No more excuses. Just proof.

v1.7.0 "Vas Szigora" - Iron Discipline. No escape from ethics.

Built with ❤️ by Máté Róbert and Claude

🤖 Built with Claude Code