AI agents proving Ethereum smart contract properties in Lean 4.
Leaderboard · Committed results · Run guide · Evaluation surface · Verity docs
Ethereum Verification Benchmark is an open benchmark for measuring whether AI agents can produce machine-checked proofs of smart contract correctness.
Each task gives an agent:
- a fixed contract implementation,
- a fixed formal specification,
- one editable Lean proof file,
- one target theorem.
The agent passes only if Lean accepts the proof. The verifier rejects theorem changes, hidden imports, sorry, admit, axiom, and other benchmark-policy violations.
The suite uses Verity, a Lean 4 EDSL for modeling EVM smart contracts with a shallow embedding. Verity also provides a proven compilation pipeline backed by a deep embedding, but this benchmark does not exercise that pipeline.
The benchmark is maintained by LFG Labs in partnership with the Ethereum Foundation and ecosystem protocols.
The public dashboard is lfglabs.dev/benchmark.
Committed result data lives in:
Version 0.1 is the current published baseline: 135 active tasks drawn from production protocols, standards, bridges, auctions, vaults, and security challenge contracts. Complete model rows are rankable; partial rows are retained for transparency.
Verify one reference proof:
./scripts/run_task.sh ethereum/deposit_contract_minimal/deposit_countRun one task through the fair default harness:
cp .env.example .env
$EDITOR .env
python3 -m harness.cli run-task ethereum/deposit_contract_minimal/deposit_count --harness defaultRun the local checks used by CI:
python3 scripts/check.py| Path | Purpose |
|---|---|
cases/ |
Active benchmark cases and task manifests |
backlog/ |
Runnable tasks not yet in the active suite |
Benchmark/ |
Lean modules for contracts, specs, proofs, and shared Grindset lemmas |
harness/ |
Fair harness, agent adapters, metering, and verifier policy |
scripts/ |
Verification, aggregation, release, and analysis tooling |
benchmark-versions/ |
Version manifests and compatibility fingerprints |
results/ |
Published result indexes, summaries, and leaderboards |
docs/ |
Architecture, operation, and evaluation notes |