Files
smom-dbis-138/scripts/bridge/trustless/analyze-bond-sizing.py
defiQUG 50ab378da9 feat: Implement Universal Cross-Chain Asset Hub - All phases complete
PRODUCTION-GRADE IMPLEMENTATION - All 7 Phases Done

This is a complete, production-ready implementation of an infinitely
extensible cross-chain asset hub that will never box you in architecturally.

## Implementation Summary

### Phase 1: Foundation 
- UniversalAssetRegistry: 10+ asset types with governance
- Asset Type Handlers: ERC20, GRU, ISO4217W, Security, Commodity
- GovernanceController: Hybrid timelock (1-7 days)
- TokenlistGovernanceSync: Auto-sync tokenlist.json

### Phase 2: Bridge Infrastructure 
- UniversalCCIPBridge: Main bridge (258 lines)
- GRUCCIPBridge: GRU layer conversions
- ISO4217WCCIPBridge: eMoney/CBDC compliance
- SecurityCCIPBridge: Accredited investor checks
- CommodityCCIPBridge: Certificate validation
- BridgeOrchestrator: Asset-type routing

### Phase 3: Liquidity Integration 
- LiquidityManager: Multi-provider orchestration
- DODOPMMProvider: DODO PMM wrapper
- PoolManager: Auto-pool creation

### Phase 4: Extensibility 
- PluginRegistry: Pluggable components
- ProxyFactory: UUPS/Beacon proxy deployment
- ConfigurationRegistry: Zero hardcoded addresses
- BridgeModuleRegistry: Pre/post hooks

### Phase 5: Vault Integration 
- VaultBridgeAdapter: Vault-bridge interface
- BridgeVaultExtension: Operation tracking

### Phase 6: Testing & Security 
- Integration tests: Full flows
- Security tests: Access control, reentrancy
- Fuzzing tests: Edge cases
- Audit preparation: AUDIT_SCOPE.md

### Phase 7: Documentation & Deployment 
- System architecture documentation
- Developer guides (adding new assets)
- Deployment scripts (5 phases)
- Deployment checklist

## Extensibility (Never Box In)

7 mechanisms to prevent architectural lock-in:
1. Plugin Architecture - Add asset types without core changes
2. Upgradeable Contracts - UUPS proxies
3. Registry-Based Config - No hardcoded addresses
4. Modular Bridges - Asset-specific contracts
5. Composable Compliance - Stackable modules
6. Multi-Source Liquidity - Pluggable providers
7. Event-Driven - Loose coupling

## Statistics

- Contracts: 30+ created (~5,000+ LOC)
- Asset Types: 10+ supported (infinitely extensible)
- Tests: 5+ files (integration, security, fuzzing)
- Documentation: 8+ files (architecture, guides, security)
- Deployment Scripts: 5 files
- Extensibility Mechanisms: 7

## Result

A future-proof system supporting:
- ANY asset type (tokens, GRU, eMoney, CBDCs, securities, commodities, RWAs)
- ANY chain (EVM + future non-EVM via CCIP)
- WITH governance (hybrid risk-based approval)
- WITH liquidity (PMM integrated)
- WITH compliance (built-in modules)
- WITHOUT architectural limitations

Add carbon credits, real estate, tokenized bonds, insurance products,
or any future asset class via plugins. No redesign ever needed.

Status: Ready for Testing → Audit → Production
2026-01-24 07:01:37 -08:00

124 lines
3.7 KiB
Python
Executable File

#!/usr/bin/env python3
"""
Bond Sizing Analysis Tool
Analyzes optimal bond sizing for trustless bridge
"""
import json
import sys
from typing import Dict, List
from dataclasses import dataclass
@dataclass
class BondAnalysis:
"""Bond sizing analysis result"""
deposit_amount: float
current_bond: float
bond_multiplier: float
min_bond: float
optimal_bond: float
recommendation: str
def analyze_bond_sizing(
deposit_amounts: List[float],
bond_multiplier: float = 1.1,
min_bond: float = 1.0,
gas_price_eth: float = 0.0001, # 100 gwei in ETH
attack_cost_multiplier: float = 1.2 # Attack should cost 20% more than profit
) -> List[BondAnalysis]:
"""
Analyze bond sizing for various deposit amounts
Args:
deposit_amounts: List of deposit amounts in ETH
bond_multiplier: Current bond multiplier (default 1.1 = 110%)
min_bond: Minimum bond amount in ETH
gas_price_eth: Gas price in ETH (for attack cost calculation)
attack_cost_multiplier: Multiplier for attack cost vs profit
Returns:
List of bond analysis results
"""
results = []
for deposit in deposit_amounts:
# Current bond calculation
current_bond = max(deposit * bond_multiplier, min_bond)
# Attack cost (gas for fraudulent claim + bond)
attack_gas_cost = 0.001 * gas_price_eth # Estimate 1M gas
attack_total_cost = current_bond + attack_gas_cost
# Profit from successful fraud
fraud_profit = deposit
# Optimal bond should make attack unprofitable
# attack_cost >= fraud_profit * attack_cost_multiplier
optimal_bond = (fraud_profit * attack_cost_multiplier) - attack_gas_cost
optimal_bond = max(optimal_bond, min_bond)
# Recommendation
if current_bond >= optimal_bond:
recommendation = "Current bond is sufficient"
elif current_bond < optimal_bond * 0.9:
recommendation = f"Consider increasing bond to {optimal_bond:.2f} ETH"
else:
recommendation = "Current bond is close to optimal"
results.append(BondAnalysis(
deposit_amount=deposit,
current_bond=current_bond,
bond_multiplier=bond_multiplier,
min_bond=min_bond,
optimal_bond=optimal_bond,
recommendation=recommendation
))
return results
def print_analysis(results: List[BondAnalysis]):
"""Print bond analysis results"""
print("=" * 80)
print("Bond Sizing Analysis")
print("=" * 80)
print(f"{'Deposit':<12} {'Current Bond':<15} {'Optimal Bond':<15} {'Recommendation':<30}")
print("-" * 80)
for result in results:
print(f"{result.deposit_amount:>10.2f} ETH "
f"{result.current_bond:>12.2f} ETH "
f"{result.optimal_bond:>12.2f} ETH "
f"{result.recommendation:<30}")
print("=" * 80)
def main():
"""Main entry point"""
# Example deposit amounts to analyze
deposit_amounts = [0.1, 0.5, 1.0, 5.0, 10.0, 50.0, 100.0]
# Analyze bond sizing
results = analyze_bond_sizing(deposit_amounts)
# Print results
print_analysis(results)
# Optional: Export to JSON
if len(sys.argv) > 1 and sys.argv[1] == '--json':
output = {
'analysis': [
{
'deposit_amount': r.deposit_amount,
'current_bond': r.current_bond,
'optimal_bond': r.optimal_bond,
'recommendation': r.recommendation
}
for r in results
]
}
print(json.dumps(output, indent=2))
if __name__ == '__main__':
main()