850223a953
- 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>
93 lines
3.1 KiB
Markdown
93 lines
3.1 KiB
Markdown
# Cross-Exchange Arbitrage Integration Plan
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## Overview
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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.
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## Core Components
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### Opportunity Detection
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- Real-time price monitoring across exchanges
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- Latency-optimized price feeds
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- Cross-exchange comparison algorithms
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- Profit calculation considering gas costs
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### Supported Arbitrage Types
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- Direct arbitrage (A→B on exchange 1, B→A on exchange 2)
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- Triangle arbitrage (A→B→C→A across multiple exchanges)
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- Multi-hop arbitrage (complex routing across multiple exchanges)
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- Cross-chain arbitrage (same token on different chains)
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### Execution Strategies
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- Atomic arbitrage (single transaction)
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- Multi-transaction arbitrage
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- Sandwich-resistant arbitrage
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- Gas-optimized execution
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## Implementation Steps
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1. Create Arbitrage struct for opportunity detection and execution
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2. Implement real-time price monitoring across exchanges
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3. Develop latency-optimized price comparison functions
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4. Add gas cost estimation for arbitrage transactions
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5. Implement atomic arbitrage execution
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6. Create multi-transaction arbitrage strategies
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7. Add protection against frontrunning
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8. Implement risk management functions
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## Pricing and Profitability
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### Cross-Exchange Price Comparison
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- Real-time price feeds from all supported exchanges
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- Price normalization across different exchange types
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- Time-adjusted pricing for fast-moving markets
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- Slippage estimation for trade execution
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### Profit Calculation
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- Calculate potential profit before gas costs
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- Factor in gas costs for the arbitrage transaction
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- Account for execution uncertainty
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- Consider minimum profitability thresholds
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### Risk Management
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- Slippage protection for large trades
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- Volume consideration based on pool liquidity
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- Market volatility adjustment
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- Maximum trade size limits
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## Testing Plan
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1. Historical backtesting of arbitrage opportunities
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2. Simulation of arbitrage execution
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3. Gas cost estimation accuracy testing
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4. Front-running resistance testing
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5. Risk management function verification
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6. Edge case testing (volatile markets, low liquidity)
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7. Performance testing under high-frequency conditions
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8. Accuracy of profit calculation
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## Performance Considerations
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- Extremely low-latency price monitoring
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- Optimized comparison algorithms
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- Efficient gas estimation
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- Fast transaction construction
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- Minimal external calls during opportunity evaluation
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- Caching of exchange state where possible
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## Security Considerations
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- Proper validation of opportunity parameters
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- Slippage protection implementation
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- Gas price monitoring and adjustment
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- Protection against invalid opportunity signals
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- Validation of exchange state before execution
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## Integration with MEV Bot
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- Coordinate with individual exchange modules
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- Integrate with transaction submission system
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- Include in overall profitability evaluation
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- Consider network congestion in execution timing
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- Track performance and frequency of successful arbitrages
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- Optimize for different market conditions |