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Overview

Analyzes an Ethereum address for sybil behavior by computing behavioral and relational signals from on-chain transaction data. Returns a composite sybil score (0-100, where higher = more likely sybil) along with individual indicator values.
This endpoint examines Ethereum mainnet transaction history to detect patterns consistent with sybil wallets -low diversity of counterparties, scripted timing, minimal gas expenditure, and lack of identity attestations.

Authentication

This endpoint supports two authentication methods:
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Path Parameters

string
required
Ethereum address or ENS name (e.g., vitalik.eth or 0xd8dA6BF26964aF9D7eEd9e03E53415D37aA96045)

Response

string
The resolved Ethereum address (checksummed)
string
ISO 8601 timestamp of when the analysis was computed
integer
Composite sybil score from 0-100. Higher scores indicate a greater likelihood that the address is a sybil.
string
Human-readable risk classification derived from sybil_score. One of: low, medium, high, critical.
object
Individual signals used to compute the composite score.
integer
Number of unique addresses this wallet has transacted with (normal transactions + ERC-20 token transfers), excluding itself.
integer
Number of unique smart contracts called (transactions with non-empty input data) or created.
number
Total gas spent on outbound transactions, in ETH. Calculated as the sum of gasUsed times gasPrice for all transactions sent from this address.
string
The address that first funded this wallet (sender of the first inbound ETH transfer). Null if no inbound value transfers exist.
number
Shannon entropy of inter-transaction time deltas, normalized to 0-1. Higher values indicate more varied (human-like) timing patterns; lower values suggest scripted/automated behavior.
integer
Number of verified identity attestations associated with this address (ENS name, Gitcoin Passport, POAPs, credentials, etc.).
integer
Number of days since the wallet’s first transaction on Ethereum mainnet.
integer
Total number of normal transactions on Ethereum mainnet.

Risk Levels

Scoring Methodology

The sybil score is computed by normalizing each indicator through a sigmoid function and combining them with the following weights:

Use Cases

Screen recipient addresses before distributing tokens. Flag addresses with high or critical risk levels to prevent sybil farming.
Verify that voters in DAO governance represent unique humans by checking sybil scores before counting votes or distributing voting power.
Combine sybil detection with credit scoring to identify borrowers who may be operating multiple wallets to circumvent lending limits.
Gate access to communities, allowlists, or early access programs by requiring a sybil score below a threshold (e.g., score under 25).

Performance

  • Response Time: Typically 2-5 seconds (uncached), under 100ms (cached)
  • Caching: Results cached for 30 minutes per address
  • Data Source: Ethereum mainnet only (via Etherscan API)