Security and Resilience in Pyth, $PYTH does not depend on a single data source. It integrates more than 100 publishers (trading firms, exchanges, financial institutions). If a node sends manipulated data, it gets diluted among multiple sources. Statistical consolidation algorithms (medians, outlier detection) are applied to reduce the impact of anomalous or manipulated prices. Unlike Chainlink (push oracle), Pyth updates data only when a dApp needs it. This reduces exposure to congestion attacks (spamming) and avoids unnecessary gas expenses in constant updates. Multichain Redundancy, prices are published on several chains (Solana, Ethereum, BNB Chain, Base, etc.) using Wormhole as a messaging layer. Slashing (penalties with staking) for malicious publishers. Fast updates (seconds, not minutes). If a feed is not updated, dApps can detect that the data is 'stale' and use contingency measures (e.g., pause loans, limit swaps). @Pyth Network #PythRoadmap