The Challenge
The decentralized exchange (DEX) ecosystem routes enormous volume, but attributing that volume to the frontend that actually originated it — the Uniswap UI, a wallet-native swap, an aggregator, an institutional desk — is notoriously hard. There is no standard way for a frontend to "announce" itself on-chain.
That gap matters most to the people funding growth. L2 foundations and grant programs hand out incentives based on volume numbers that are easy to game: wash trading, proxy routing, and MEV-farm flow all look like "adoption" in standard dashboards. Without neutral attribution, incentives reward the wrong behavior.
What We Built
ClearTrace is a live, neutral, third-party execution-intelligence engine built on Dune Analytics' granular trace and call tables — building on our open-source contributions to Dune, including 67 contracts we submitted for decoding. It attributes trade origin, benchmarks execution quality, and measures MEV exposure across Ethereum, Base, Arbitrum, and Optimism — using 172K+ attributed contracts — and serves it through a public dashboard and REST API at cleartracedata.com.
Four attribution vectors for hidden orderflow
- Call-data suffix trapper: parses static hex suffixes appended to router calldata that standard contract decoders ignore — catching meta-frontends and wallet-native swap extensions.
- Proxy-router hunt: flags
tx_to/ pool-address mismatches to reveal custom enterprise frontends and institutional smart wallets bypassing public tracking. - Multi-hop origin trace: uses window functions (
LAG/LEAD) over per-wallet interaction sequences to map interface hops and user churn across chains. - Fee-recipient vector: clusters anonymous frontends by the basis-point fees they route to static on-chain identifiers during execution.
Execution quality, measured neutrally
ClearTrace scores execution by comparing each trade's realized price against a 1-minute Volume-Weighted Average Price (VWAP) oracle — the true cost of a trade, not the quoted price the aggregator advertises. Across the chains it covers, the best-performing aggregators land around a ~7.5 bps median effective slippage. It separately detects sandwich attacks (frontrun → victim → backrun) by scanning in-block transaction ordering, and reports both the number of attacks and total value sandwiched as a distinct MEV-exposure metric rather than folding it into the slippage score.
Illustrative extraction
A simplified shape of the attribution pass — isolating frontend codes while filtering proxy noise and known bot flow:
-- Attribute trades to originating frontend, net of proxy/bot noise
SELECT
evt_tx_hash,
evt_block_time,
tx_from AS sender,
-- Decode the trailing calldata suffix that identifies the frontend
RIGHT(encode(call_data, 'hex'), 8) AS frontend_id,
amount_usd
FROM dex.trades_traces
WHERE success = true
AND tx_from NOT IN (SELECT address FROM labels.mev_bots)
AND call_depth <= 2 -- direct interaction; strips proxy layersWhat It Shows
Finding signal in deliberately adversarial data — flow that is obfuscated, unlabeled, or actively trying not to be measured — and shipping it as live, defensible infrastructure with a public API. It is the on-chain expression of Rantum's through-line: rare-data attribution and detection turned into a product.
What It Proves to a Client
That we can build data infrastructure others can't easily replicate. ClearTrace gives foundations, grant programs, and protocol teams neutral proof of organic-versus-wash/proxy/bot volume for named recipients — the basis for spending incentives on real adoption. It runs today as a free dashboard and public API, with paid per-chain integrity reports and standing monthly monitoring engagements.