Tornado Cash uses smart contracts that accept ETH & other token deposits from one address and enables their withdrawal from a different address. To preserve privacy a relayer can be used to withdraw to an address with no ETH balance.

Tornado Cash is a fully decentralized non-custodial protocol allowing private transactions on Ethereum and other adjacent blockchains. Tornado Cash was co-founded by Roman Semenov in 2019.

TORN token holders own and govern the protocol. They currently take a cut of the total withdrawal fees paid (revenue).

github

etherscan

Infrastructure

Tornado Cash

# Tornado Cash Active users (monthly) Methodology

## 1. Overview

Monthly Active Users (MAU) measures the number of unique users who performed withdrawals from Tornado Cash mixing contracts over a rolling 30-day period. This metric tracks user engagement with Tornado Cash's privacy protocol by counting distinct withdrawal recipients across all supported token pools and blockchains. The calculation uses HyperLogLog probabilistic data structures to efficiently aggregate unique users across multiple time periods and dimensions.

## 2. Data sources

The calculation relies on the following raw data sources:

- **Tornado Cash withdrawal events**: Parsed `Withdrawal` events from Tornado Cash contracts deployed across Ethereum, Arbitrum, Avalanche, BSC, Gnosis, Optimism, and Polygon blockchains
- **Multi-token pool coverage**: Events from various token-specific pools including ETH (0.1, 1, 10, 100), DAI (100, 1K, 10K, 100K), USDC (100, 1K), USDT (100, 1K), WBTC (0.1, 1), BNB (0.1, 1, 10, 100), AVAX (10, 100, 500), MATIC (100, 1K, 10K, 100K), and XDAI (100, 1K, 10K, 100K) denominations
- **Blockchain transaction data**: Transaction timestamps and hash identifiers from supported blockchain networks  
- **Chain availability metadata**: Data indicating which blockchain networks are operational and should be included in calculations

## 3. Step-by-step calculation

### Component A: User activity extraction
- **Purpose**: Identifies active users from Tornado Cash withdrawal transactions
- **Logic**: Extracts withdrawal events from all Tornado Cash token pools across supported blockchains. Each withdrawal event contains a recipient address (`to` field) representing a user withdrawing mixed tokens. The system processes events from multiple token pools per chain, including various ETH denominations on Ethereum/Arbitrum/Optimism, stablecoin pools on Ethereum, native token pools (BNB, AVAX, MATIC, XDAI) on respective chains. Users are classified as "Transactor" type, representing individuals who initiate withdrawal transactions. All interactions are categorized under the infrastructure market sector.
- **Key fields**: `block_timestamp` for timing, `transaction_hash` for uniqueness, `to` address for user identification, `chain` for network classification, `user_type` as "Transactor"

### Component B: Daily active users calculation  
- **Purpose**: Aggregates withdrawal activity into daily distinct user counts
- **Logic**: Groups withdrawal events by day using timestamp truncation to daily boundaries. Counts distinct user addresses per day, segmented by blockchain network, user type, and product identifier. Creates the foundation dataset of daily unique users that will be aggregated into monthly windows. Applies chain availability filters to exclude data from networks that may be temporarily unavailable or deprecated.
- **Key fields**: `timestamp` truncated to day, `chain` identifier, `user_type`, `product_id`, `user_address` for distinct counting

### Component C: HyperLogLog sketch creation
- **Purpose**: Converts daily user counts into probabilistic data structures for efficient aggregation
- **Logic**: Transforms daily distinct user counts into HyperLogLog sketches with precision parameter 15. HyperLogLog enables efficient merging of user counts across time periods while maintaining reasonable accuracy for cardinality estimation. This approach prevents memory overflow when calculating rolling windows over large user datasets and allows for approximate distinct counting across multiple dimensions.
- **Key fields**: `hll` sketch containing compressed user count data, preserving timestamp and dimensional attributes

### Component D: Rolling window construction
- **Purpose**: Creates 30-day rolling windows for each calendar day
- **Logic**: Generates a datespine covering all days from the earliest available data to the current date. For each day in the datespine, creates associations with the 29 preceding days to form 30-day windows. Joins the windowed days with the daily HLL sketches to collect all user activity within each 30-day period. Applies incremental processing logic to optimize performance by only recalculating recent time periods when new data arrives.
- **Key fields**: `timestamp` as the end date of each 30-day window, `joinday` representing each day within the window, joined HLL sketches for the period

### Final aggregation
- **Combining components**: Merges HyperLogLog sketches across all days within each 30-day window to calculate unique users who were active during the period. The HLL merge operation deduplicates users who were active on multiple days within the same 30-day window.
- **Dimensional breakdowns**: Calculates MAU across four different aggregation levels: overall project level (all chains and products combined), by individual blockchain network, by user type classification, and by product identifier. Each breakdown maintains separate HLL calculations to provide granular analytics.
- **Time aggregation**: Uses rolling 30-day windows where each day represents the end of a unique 30-day period. Windows overlap significantly, providing smooth trending of user activity over time.
- **Final calculation**: Extracts final MAU counts from merged HyperLogLog sketches using the extract function. Applies the standardized metric finalization process to ensure consistent schema formatting and fills missing time periods with zero values where no user activity occurred.

*This methodology was automatically generated by Token Terminal's methodology analyzer.*

Unique revenue-generating users over a rolling 30-day window.

Tornado CashTORN

Active users (monthly)

Active users (monthly)

Competitive landscape

Chain breakdown