Files
mev-beta/docs/CODE_AUDIT_FINDINGS_20251106.md
Krypto Kajun 8cba462024 feat(prod): complete production deployment with Podman containerization
- Migrate from Docker to Podman for enhanced security (rootless containers)
- Add production-ready Dockerfile with multi-stage builds
- Configure production environment with Arbitrum mainnet RPC endpoints
- Add comprehensive test coverage for core modules (exchanges, execution, profitability)
- Implement production audit and deployment documentation
- Update deployment scripts for production environment
- Add container runtime and health monitoring scripts
- Document RPC limitations and remediation strategies
- Implement token metadata caching and pool validation

This commit prepares the MEV bot for production deployment on Arbitrum
with full containerization, security hardening, and operational tooling.

🤖 Generated with Claude Code
Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-08 10:15:22 -06:00

10 KiB

Code Audit Findings & Production Readiness Analysis

Date: November 6, 2025 Status: IN PROGRESS - Preliminary Analysis Confidence: High (based on static analysis)


Executive Summary

Current Status: 🟡 PARTIALLY READY

The codebase has solid foundations but requires validation and corrections before production deployment.

Key Findings

  • Architecture is sound with proper separation of concerns
  • Gas calculation logic implemented
  • Slippage protection mechanisms in place
  • ⚠️ Test coverage unknown (tests running)
  • ⚠️ Error handling needs verification
  • ⚠️ Configuration validation required
  • Profitability thresholds may need adjustment

1. Profit Calculation Analysis

File: pkg/profitcalc/profit_calc.go (502 lines)

Strengths

  • Multi-DEX price feed integration
  • Slippage protection implemented (SlippageProtector)
  • Gas price updating (30-second interval)
  • Min profit threshold configurable
  • Confidence scoring system

Configured Values (CRITICAL)

minProfitThreshold: 0.001 ETH
maxSlippage: 3% (0.03)
gasPrice: 0.1 gwei (default)
gasLimit: 100,000 (reduced from 300k for Arbitrum L2)
gasPriceUpdateInterval: 30 seconds

Issues to Verify ⚠️

  1. Min Profit Threshold: 0.001 ETH may be too high

    • Arbitrum transaction costs typically 0.0001-0.0005 ETH
    • Current threshold only allows ~2-10x profitable trades
    • RECOMMENDATION: Lower to 0.0001 ETH for realistic opportunities
  2. Gas Estimation: Using hardcoded 100k gas limit

    • May underestimate for complex multi-hop trades
    • Should be dynamic based on path complexity
    • RECOMMENDATION: Implement adaptive gas estimation
  3. Price Feed: Multi-DEX price feed not fully visible

    • Need to verify all major DEX sources included
    • Should handle stale price data
    • RECOMMENDATION: Audit price feed completeness

2. Arbitrage Detection Engine Analysis

File: pkg/arbitrage/detection_engine.go (975 lines)

Architecture Strengths

  • Worker pool pattern for concurrent scanning
  • Backpressure handling with semaphore
  • Proper mutex protection for shared state
  • Structured logging
  • Opportunity channel for async handling

Key Features

  • Configurable scanning interval
  • Multiple worker pools (scanning + path analysis)
  • Opportunity filtering/ranking
  • Real-time opportunity distribution
  • Rate limiting

Configuration Parameters

ScanInterval: Unknown (need to check)
MaxConcurrentScans: Unknown
MinProfitThreshold: Configurable
MaxProfitThreshold: Configurable
ConfidenceThreshold: Configurable

Areas Requiring Verification ⚠️

  1. Opportunity Filtering

    • How many opportunities are filtered out?
    • Are filtering criteria too strict?
    • Need baseline metrics
  2. Concurrent Processing

    • How many workers are configured?
    • What's the opportunity throughput?
    • Are all worker pools properly sized?
  3. Path Analysis

    • How deep are path searches (multi-hop)?
    • What's the maximum path length considered?
    • Are all possible paths being explored?

3. Token & Metadata Handling

File: pkg/tokens/metadata_cache.go (498 lines)

Current Implementation

  • Token metadata caching
  • Decimal handling
  • Price tracking

Potential Issues ⚠️

  1. Stale Data: How often is cache refreshed?
  2. Missing Tokens: What happens for unlisted tokens?
  3. Decimals: Are all token decimals correctly handled?

4. Swap Analysis

File: pkg/scanner/swap/analyzer.go (1053 lines)

What We Know

  • Analyzes swaps for opportunities
  • Price impact calculations
  • Complex multi-hop analysis

Key Questions ⚠️

  1. Is it correctly identifying all swap opportunities?
  2. Are slippage calculations accurate?
  3. Is gas estimation comprehensive?

5. Main Bot Entry Point

File: cmd/mev-bot/main.go (799 lines)

Needs Verification

  • Error handling during startup
  • Graceful shutdown
  • Configuration loading
  • RPC connection management
  • Health checks
  • Logging setup

Critical Configuration Issues

1. RPC Endpoint Configuration

Concern: RPC rate limiting and failover

  • How many RPC endpoints configured?
  • What's the rate limit per endpoint?
  • Are there fallback endpoints?
  • RECOMMENDATION: Verify 2+ endpoints with failover

2. Minimum Profit Threshold

Current: 0.001 ETH Analysis:

Arbitrum Gas Costs:
- Simple swap: ~0.00005-0.0001 ETH
- Multi-hop: ~0.0002-0.0005 ETH
- Flash loan: ~0.00001 ETH (Balancer, 0% fee)

Minimum Viable Profit at 0.001 ETH threshold:
- At $2000/ETH = $2 minimum trade
- At 0.1% spread = $2000 pool liquidity needed
- Very conservative

RECOMMENDATION: Lower threshold to 0.0001 ETH

3. Gas Price Settings

Current: Hardcoded 0.1 gwei + dynamic updates Issue: Arbitrum L2 pricing model different from L1

  • Should use current gas price from RPC
  • 30-second updates might be too frequent
  • RECOMMENDATION: Verify gas price source

Test Coverage Gaps (PREDICTED)

Based on code analysis, likely gaps:

1. Edge Cases Not Covered

  • Zero amount handling
  • Extreme price discrepancies
  • Network errors during calculation
  • Stale price data handling

2. Multi-Hop Paths

  • 3-hop arbitrage paths
  • Complex routing scenarios
  • Circular opportunities

3. Error Scenarios

  • RPC connection failures
  • Rate limit handling
  • Timeout scenarios
  • Corrupted data handling

4. Concurrent Operations

  • Race conditions in opportunity detection
  • Worker pool saturation
  • Memory leaks in long-running processes

Production Readiness Checklist

Configuration ⚠️

  • RPC endpoints configured with failover
  • Min profit threshold validated against market data
  • Gas estimation verified for all transaction types
  • Rate limiting properly configured
  • Error recovery mechanisms active

Functionality (Needs Testing)

  • Opportunity detection working end-to-end
  • Profit calculation accurate
  • Slippage protection active
  • Gas costs properly estimated
  • Transaction building correct

Reliability ⚠️

  • Health checks operational
  • Logging complete
  • Error handling comprehensive
  • Graceful shutdown implemented
  • Recovery from failures

Performance ⚠️

  • Opportunity detection < 1 second
  • Transaction building < 1 second
  • Memory usage stable
  • CPU usage reasonable
  • No goroutine leaks

Security

  • No hardcoded secrets
  • Input validation comprehensive
  • Error messages don't leak sensitive data
  • Rate limiting enforced
  • Access control proper

IMMEDIATE (Before Production)

  1. Lower Min Profit Threshold

    • Change from 0.001 ETH to 0.0001 ETH
    • File: pkg/profitcalc/profit_calc.go:61
    • Reason: Current threshold too high for realistic opportunities
  2. Verify RPC Configuration

    • Ensure failover endpoints configured
    • Verify rate limiting settings
    • Test connection resilience
  3. Run Full Test Suite

    • Fix any failing tests
    • Ensure 100% coverage
    • Add missing test cases

SHORT TERM (First Week)

  1. Implement Adaptive Gas Estimation

    • Current: hardcoded 100k gas
    • Target: dynamic based on path complexity
    • Impact: More accurate profitability
  2. Add More Logging

    • Log all opportunity detections
    • Log profit calculations with details
    • Log transaction attempts and results
  3. Implement Health Checks

    • RPC endpoint health
    • Market data freshness
    • System resource monitoring

MEDIUM TERM (Ongoing)

  1. Performance Optimization

    • Benchmark opportunity detection
    • Optimize database queries
    • Reduce latency to execution
  2. Advanced Features

    • Cross-chain opportunities
    • More DEX integrations
    • Advanced risk management

Metrics to Monitor

Once in production, track these metrics:

Detection Metrics

Opportunities detected per minute
Average detection latency (ms)
Distribution by profit range
Distribution by path length
Filter-out rate (how many filtered vs executed)

Execution Metrics

Execution success rate (%)
Average profit per trade (ETH/USD)
Total profit per day/week/month
Average gas cost (ETH/USD)
Net profit after gas costs

System Metrics

Memory usage (MB)
CPU usage (%)
Goroutine count
RPC request rate
Error rate (%)

Risk Assessment

HIGH RISK 🔴

  1. Unknown test coverage

    • Tests currently running
    • Coverage percentage unknown
    • May have critical gaps
  2. Configuration not validated

    • Min profit threshold unverified
    • RPC endpoints unknown
    • Gas settings not confirmed
  3. Error handling untested

    • Network failure scenarios
    • Configuration errors
    • Edge cases

MEDIUM RISK 🟡

  1. Performance unknown

    • Opportunity detection speed
    • Memory usage under load
    • Concurrent operation limits
  2. Market data freshness

    • Price feed update frequency
    • How stale prices are handled
    • Multi-DEX price reconciliation

LOW RISK 🟢

  1. Core architecture

    • Design is sound
    • Proper separation of concerns
    • Good use of Go patterns
  2. Security basics

    • No obvious hardcoded secrets (visible)
    • Input validation present
    • Proper logging without leakage

Next Steps

Immediate (Current)

  1. Wait for test results
  2. Analyze any test failures
  3. Fix identified issues
  4. Run coverage analysis

Short Term (Today)

  1. Review and adjust configuration
  2. Lower min profit threshold
  3. Verify RPC setup
  4. Run integration tests

Medium Term (This Week)

  1. Deploy to testnet
  2. Monitor for 24+ hours
  3. Collect metrics
  4. Optimize based on data

Production Deployment

  1. Only after all above complete
  2. With continuous monitoring
  3. With automated alerts
  4. With kill switches ready

Conclusion

Current Assessment: Codebase is structurally sound but requires testing, configuration validation, and threshold adjustments before production use.

Estimated Time to Production Ready:

  • With successful tests: 2-3 hours
  • With test failures: 4-8 hours
  • With major issues: 1-2 days

Confidence in Profitability: Medium

  • Architecture supports finding opportunities
  • Configuration may need adjustment
  • Real-world testing needed

Recommendation: Proceed with testing and fixes as outlined.


Generated: 2025-11-06 Status: PRELIMINARY (Based on static analysis) Next: Update based on actual test results