- Updated all ponder event handlers to use proper TypeScript types
- Removed all 'any' type annotations from event handlers
- Handlers now properly leverage TypeScript's type inference
- Improved type safety across the ponder indexer
Fixes#22
- Updated kraiken-lib tsconfig and yarn.lock
- Added package.json with playwright-mcp dependency
- Updated uni-v3-lib submodule
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- Fixed service dependencies (removed bootstrap dependency for runtime services)
- Added landing service for documentation site at root path
- Moved web-app to /app path, landing to / path
- Fixed permission issues with lowercase 'z' SELinux context
- Added kraiken-lib compilation in txn-bot container
- Fixed TypeScript build for kraiken-lib with proper volumes
- Updated entrypoint scripts to handle npm installs properly
- Added locale fixes to Containerfiles
- Changed Caddy port from 80 to 8081 for external access
- Updated Docs link to point to local landing page
All services now working:
- Landing page at /
- Web app at /app/
- GraphQL at /graphql
- Transaction bot at /txn
- Anvil RPC at /rpc/anvil
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- Integrate staking and exitPosition actions into fuzzing scenarios
- Add staking metrics (percentageStaked, avgTaxRate) to CSV output
- Implement snatching mechanism when stake pool reaches capacity
- Add configurable staking parameters (enable/disable, buy bias, staking bias)
- Support configurable number of trades per run
- Simplify to single trader account with proportional ETH funding
- Configure tax rates: 0-15 for initial stakes, 28 for snatching
- Clean up debug logging and verbose output
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Co-Authored-By: Claude <noreply@anthropic.com>
- Add staking/unstaking actions to fuzzing scenarios (stake every 3rd trade)
- Implement snatching logic when stake pool reaches capacity (uses max tax rate)
- Add configurable parameters:
- buyBias: Control buy vs sell ratio (0-100%)
- stakingBias: Control stake vs unstake ratio (0-100%)
- tradesPerRun: Configure number of trades per scenario
- staking: Enable/disable staking entirely
- Simplify to single trading strategy (_executeRandomLargeTrades)
- Fix memory issues by recording only every 5th trade to CSV
- Track staking metrics (stakes attempted/succeeded, snatches attempted/succeeded)
- Update CLAUDE.md with new fuzzing parameters and usage examples
- Clean up old TODO files and unused code
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- Added BUY_BIAS environment variable (0-100%) to control trading direction
- Implemented biased trading logic in all strategies (Random, Whale, Volatile, etc.)
- Created run-improved-fuzzing.sh script with buy bias support
- Fixed memory issues in CSV generation by simplifying string concatenation
- Fixed console.log parameter issues in staking functions
- Updated run-recorded-fuzzing.sh to accept buybias parameter
- Testing shows up to 99% of authorized stake reached with 100% buy bias
Co-Authored-By: Claude <noreply@anthropic.com>
- Deploy Uniswap factory once before all runs (saves ~1.16M gas per run)
- Fix CSV buffer accumulation bug by clearing buffer between runs
- Add clearCSV() function to CSVManager for proper buffer management
- Each fuzzing run now gets its own clean CSV with correct token0isWeth values
- Comment out failing console.log in Optimizer.t.sol to fix compilation
The token ordering now correctly alternates:
- Even seeds: token0isWeth = true (WETH < KRAIKEN)
- Odd seeds: token0isWeth = false (KRAIKEN < WETH)
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Co-Authored-By: Claude <noreply@anthropic.com>
Replace hardcoded anchorWidth=100 with dynamic calculation that uses staking data as a decentralized oracle.
Changes:
- Add _calculateAnchorWidth() function to Optimizer.sol
- Base width 40% with adjustments based on staking percentage and average tax rate
- Staking adjustment: -20% to +20% (inverse relationship)
- Tax rate adjustment: -10% to +30% (direct relationship)
- Final range clamped to 10-80% for safety
Rationale:
- High staking % = bullish sentiment → narrower anchor (20-35%) for fee optimization
- Low staking % = bearish/uncertain → wider anchor (60-80%) for defensive positioning
- High tax rates = volatility expected → wider anchor to reduce rebalancing
- Low tax rates = stability expected → narrower anchor for fee collection
The Harberger tax mechanism acts as a prediction market where stakers' self-assessed valuations reveal market expectations.
Tests:
- Add comprehensive unit tests in test/Optimizer.t.sol
- Add mock contracts for testing (MockStake.sol, MockKraiken.sol)
- Manual verification confirms all scenarios calculate correctly
Documentation:
- Add detailed analysis of anchorWidth price ranges
- Add staking-based strategy recommendations
- Add verification of calculation logic
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- Updated all production code references from 'harb' to 'kraiken'
- Changed 'Harberger tax' references to 'self-assessed tax'
- Updated function names (_getHarbToken -> _getKraikenToken)
- Modified documentation and comments to reflect new branding
- Updated token symbol from HARB to KRAIKEN in tests
- Maintained backward compatibility with test variable names
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The fuzzing script was failing with out-of-gas errors when large KRAIKEN sells
tried to traverse many tick ranges in Uniswap V3. Fixed by adding the
--disable-block-gas-limit flag to forge script execution.
Also fixed the CSV symlink path for the visualizer to work correctly.
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Co-Authored-By: Claude <noreply@anthropic.com>
- Increased gas limit to 100M to prevent out-of-gas errors during large swaps
- Fixed symlink path for profitable_scenario.csv to work with visualizer
- Position CSVs are now always generated when recording profitable scenarios
The out-of-gas error was occurring when large KRAIKEN sells tried to traverse
many tick ranges in Uniswap V3. The visualizer couldn't display data because
the CSV symlink was created in the wrong directory.
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Co-Authored-By: Claude <noreply@anthropic.com>
- Replaced old FuzzingAnalysis.s.sol with improved RecordedFuzzingAnalysis
- Old fuzzing used trades too small (0.1-100% of remaining balance) to reach discovery
- New system uses larger trades (50-200 ETH) that successfully find invariants
- run-fuzzing.sh now redirects to run-recorded-fuzzing.sh for backward compatibility
- Added position CSV generation for profitable scenarios to support visualizer
- Visualizer automatically launches when invariants are found
- Removed unnecessary debugCSV complexity
The old fuzzing couldn't find invariants because trades got progressively smaller
(often <1 ETH after a few iterations) and couldn't move price the 3,690 ticks
needed to reach the discovery position. The new system maintains large trade sizes
throughout the scenario, successfully finding profitable exploits.
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Co-Authored-By: Claude <noreply@anthropic.com>
Implements comprehensive fuzzing improvements to find and reproduce invariant violations:
Recording System:
- ScenarioRecorder captures exact trading sequences that violate invariants
- Exports to JSON, replay scripts, and human-readable summaries
- Unique Run IDs (format: YYMMDD-XXXX) for easy communication
Enhanced Fuzzing:
- ImprovedFuzzingAnalysis with larger trades (50-500 ETH) to reach discovery position
- Multiple strategies: Discovery Push, Whale Manipulation, Volatile Swings
- Successfully finds profitable scenarios with 66% success rate
Shell Scripts:
- run-recorded-fuzzing.sh: Automated fuzzing with recording and unique IDs
- replay-scenario.sh: One-command replay of specific scenarios
New Optimizers:
- ExtremeOptimizer: Tests extreme market conditions
- MaliciousOptimizer: Attempts to exploit the protocol
Documentation:
- Updated CLAUDE.md with complete recording workflow
- Enhanced 4-step debugging process
- Quick reference for team collaboration
This system successfully identifies and reproduces the discovery position exploit,
where traders can profit by pushing trades into the unused liquidity at extreme ticks.
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Co-Authored-By: Claude <noreply@anthropic.com>
