Anti-Sybil

Anti-Sybil Scoring: Fair Allocations Without Farming.

Multi-wallet farming captures disproportionate allocation in public token sales at the expense of genuine participants. Tonstarter's on-chain behavioral scoring adjusts allocation weight per wallet address — reducing the advantage of coordinated farming operations without penalising single-wallet newcomers with short TON staking history.

Anti-sybil scoring reduces manipulation surface and adjusts allocation weighting — it is not identity verification and does not replace KYC due diligence.
5 behavioral signals
On-chain data only — no off-chain profiling
Score is non-identifiable
No personal data in scoring layer — wallet address and behavioral history only
Weighted allocation tiers
Higher-score wallets receive proportionally larger allocation caps
Visual representation of anti-sybil scoring algorithm showing wallet behavioral signals mapped to allocation weights on a network graph
Scoring Model

Five Behavioral Signals

Each signal contributes to a composite score between 0 and 100. The score affects allocation tier assignment — it does not determine KYC eligibility, which is a separate process.

Account age

Time since the wallet's first on-chain transaction on TON network. Longer history indicates established usage, not a newly-created farming address.

Transaction volume diversity

Variety of transaction types and counterparties over time. Genuine wallets tend to show diverse activity (transfers, contract interactions, multiple counterparties). Farming wallets often show narrow, repetitive patterns.

TON staking history

Prior staking activity on TON network indicates a longer-term participant with economic commitment to the ecosystem, not a wallet created for a single airdrop or sale event.

Cross-wallet funding source correlation

Analysis of funding chains to identify wallets funded from a single source in batch. Wallets funded together from the same address in a short timeframe are flagged as potentially coordinated.

Timing pattern similarity

Detection of wallets that make transactions at nearly identical times across multiple addresses — a hallmark of scripted farming operations rather than individual human-driven activity.

Detection

Farming Patterns Detected

  • Address clustering from a single funding source within a narrow time window
  • Coordinated transaction timing across multiple wallets (script-executed patterns)
  • Token farming history: addresses that appear repeatedly across multiple airdrop and sale registrations
  • Funding chain tracing through multiple hops to a common origin wallet
Important: Anti-sybil scoring reduces manipulation surface — it does not guarantee perfect detection. Sufficiently sophisticated multi-wallet setups with long wallet histories may score higher than naive farming wallets. This is an acknowledged limitation of on-chain behavioral analysis.
Score Profiles

What High vs. Low Score Profiles Look Like

High score wallet (65–100)
  • Account age over 12 months
  • Diverse transaction counterparties and contract interactions
  • Prior TON staking activity
  • Funded independently (exchange withdrawal or wallet-to-wallet over time)
  • No pattern overlap with other registered wallets
Low score wallet (0–39)
  • Account created within the last 3 months
  • Minimal or repetitive transaction history
  • No staking activity
  • Funded from the same address as several other applicants within 24 hours
  • Transaction timing closely correlates with other wallets in the cluster
Privacy

What Is and Is Not Tracked

What IS analyzed
  • Public on-chain transaction records
  • Wallet address and creation date
  • Transaction timing and counterparty counts
  • Staking contract interactions
  • Funding source addresses (public blockchain data)
What is NOT analyzed
  • Off-chain identity or personal data
  • Social media accounts or behavior
  • IP addresses or device fingerprints
  • Exchange account data
  • KYC documents (separate process)

Anti-sybil scoring is a blockchain analytics function. It processes publicly-visible on-chain records only. The score assigned to a wallet is non-identifiable — it does not link the score back to the KYC identity in the anti-sybil layer. The two processes (KYC and anti-sybil scoring) run in parallel but are logically separate.

Apply Your Project

Anti-sybil scoring is included in every sale listing. Submit your project to see how the full platform stack applies to your launch.

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