How We Simulate Real On-Chain Behavior

Fraktom's simulations are built using a hybrid model of real-world data and synthetic testing logic to maximize realism without risking real funds.

Fraktom's scenarios are modeled using:

• Historical Solana token launch data

• Rug pull case studies

• Synthetic token generators

What the Simulation Engine Analyzes The simulation engine parses mock contract metadata and wallet flows to replicate patterns commonly seen across Solana memecoin launches:

• Bridge activity patterns (funds arriving from known deployer hubs)

• Wallet clustering (supply concentrated across few holders)

• Influencer social activity and timing anomalies

• Suspicious early exits or liquidity drains

• Stealth launches and mismatched narratives

Sample Scenario Blueprint

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interface TokenScenario {
  name: string;
  devWallets: number;
  honeypotFlagged: boolean;
  txnCountFirst5Min: number;
  sniperActivity: boolean;
  bridgeSourceMatch: boolean;
}

This flexible model lets us generate realistic trade-offs, red flags, and conditions that simulate true on-chain pressure. By interacting with these scenarios in real time, users develop pattern recognition before they put real capital at risk.