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- Added comprehensive bounds checking to prevent buffer overruns in multicall parsing - Implemented graduated validation system (Strict/Moderate/Permissive) to reduce false positives - Added LRU caching system for address validation with 10-minute TTL - Enhanced ABI decoder with missing Universal Router and Arbitrum-specific DEX signatures - Fixed duplicate function declarations and import conflicts across multiple files - Added error recovery mechanisms with multiple fallback strategies - Updated tests to handle new validation behavior for suspicious addresses - Fixed parser test expectations for improved validation system - Applied gofmt formatting fixes to ensure code style compliance - Fixed mutex copying issues in monitoring package by introducing MetricsSnapshot - Resolved critical security vulnerabilities in heuristic address extraction - Progress: Updated TODO audit from 10% to 35% complete 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
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Cross-Exchange Arbitrage Integration Plan
Overview
This document outlines the implementation plan for identifying and executing cross-exchange arbitrage opportunities in the MEV bot. This involves finding price differences between exchanges for the same asset pair and executing profitable trades.
Core Components
Opportunity Detection
- Real-time price monitoring across exchanges
- Latency-optimized price feeds
- Cross-exchange comparison algorithms
- Profit calculation considering gas costs
Supported Arbitrage Types
- Direct arbitrage (A→B on exchange 1, B→A on exchange 2)
- Triangle arbitrage (A→B→C→A across multiple exchanges)
- Multi-hop arbitrage (complex routing across multiple exchanges)
- Cross-chain arbitrage (same token on different chains)
Execution Strategies
- Atomic arbitrage (single transaction)
- Multi-transaction arbitrage
- Sandwich-resistant arbitrage
- Gas-optimized execution
Implementation Steps
- Create Arbitrage struct for opportunity detection and execution
- Implement real-time price monitoring across exchanges
- Develop latency-optimized price comparison functions
- Add gas cost estimation for arbitrage transactions
- Implement atomic arbitrage execution
- Create multi-transaction arbitrage strategies
- Add protection against frontrunning
- Implement risk management functions
Pricing and Profitability
Cross-Exchange Price Comparison
- Real-time price feeds from all supported exchanges
- Price normalization across different exchange types
- Time-adjusted pricing for fast-moving markets
- Slippage estimation for trade execution
Profit Calculation
- Calculate potential profit before gas costs
- Factor in gas costs for the arbitrage transaction
- Account for execution uncertainty
- Consider minimum profitability thresholds
Risk Management
- Slippage protection for large trades
- Volume consideration based on pool liquidity
- Market volatility adjustment
- Maximum trade size limits
Testing Plan
- Historical backtesting of arbitrage opportunities
- Simulation of arbitrage execution
- Gas cost estimation accuracy testing
- Front-running resistance testing
- Risk management function verification
- Edge case testing (volatile markets, low liquidity)
- Performance testing under high-frequency conditions
- Accuracy of profit calculation
Performance Considerations
- Extremely low-latency price monitoring
- Optimized comparison algorithms
- Efficient gas estimation
- Fast transaction construction
- Minimal external calls during opportunity evaluation
- Caching of exchange state where possible
Security Considerations
- Proper validation of opportunity parameters
- Slippage protection implementation
- Gas price monitoring and adjustment
- Protection against invalid opportunity signals
- Validation of exchange state before execution
Integration with MEV Bot
- Coordinate with individual exchange modules
- Integrate with transaction submission system
- Include in overall profitability evaluation
- Consider network congestion in execution timing
- Track performance and frequency of successful arbitrages
- Optimize for different market conditions