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NEEDS PROOFv2.0

Threat Model

Adversaries, failure modes, and the security boundary around economic settlement.

Updated 2026-09-23 · Canonical at www.spawnfarm.com · Status labels describe evidence, not marketing readiness

Assume every actor may be malicious or fail.

Designer threats

  • malicious/buggy model;
  • misleading scientific claims;
  • dependency drift;
  • hidden network/time/randomness;
  • disappearing data.

Controls: pinned version, provenance, deterministic environment, data availability requirements, tests, explicit limitations.

Launcher threats

  • unfair configuration;
  • excessive fees;
  • liquidity withdrawal;
  • rule changes after players enter;
  • underfunded runtime.

Controls: bounded configuration, fee templates/caps, protected liquidity, immutable Season rules, minimum runway requirements.

Player threats

  • duplicate withdrawal;
  • malformed inputs;
  • front-running strategy reveals;
  • Sybil participation;
  • manipulation of predictable randomness.

Controls: nonces/position IDs, input validation, commit/reveal where required, World-level eligibility policies, explicit randomness class.

Runner threats

  • fabricated state;
  • stale state;
  • wrong code/runtime;
  • selective censorship;
  • withholding data/output;
  • submitting cheap hash spam for rewards.

Controls: bonds, exact job spec, independent replay, payment only after finality, replaceability/failover.

Verifier threats

  • collusion;
  • bribery;
  • downtime;
  • homogeneous infrastructure failure.

Controls: diversity, bonds, exposure caps, public replay, later stronger proofs.

Contract threats

  • reentrancy;
  • integer/rounding bugs;
  • settlement overflow/underbacking;
  • admin/key abuse;
  • upgrade risk;
  • token edge cases.

Controls: SafeERC20 patterns, checks-effects-interactions, formal invariants, staged caps, audit, narrow admin authority, testnet deployments.

Market threats

  • token price collapse;
  • wash trading;
  • thin liquidity;
  • MEV;
  • manipulation of fee-driven runtime metrics.

Controls: do not equate liquidity lock with safety, measure real fees, separate runtime solvency from token price, cap dependencies on unverified market behavior.