🔮 | Pyth Entropy

Random at its finest. Fully powered by the best infra provider.

MonoChest and MonoPot results are 100% random. To ensure that all given chest rewards and tickets are unpredictable, we looked for some of the best infra providers in DeFi and chose Pyth Network's Entropy.

Pyth Entropy introduces a groundbreaking method for supplying secure random numbers on the blockchain, now available on the Blast Mainnet. This solution addresses our need for a quick and affordable on-chain randomness source.

Random numbers are produced as Verifiable Random Functions (VRFs) by Pyth for use in games. When a game contract requests a random number, it is generated and then sent back to the contract by Entropy once the provider has fulfilled the request.

Utilizing Pyth Entropy has several benefits that we believe will ensure the best gaming experience, including:

  • Security: Pyth Entropy utilizes a commit-reveal protocol, ensuring strong security measures and consistent responsiveness. This protocol reduces the need for trust among participants, and by adhering to it, Entropy users can be assured that the results are genuinely random.

  • Speed: Pyth Entropy employs a pull design akin to Pythnet Price Feeds. Within the Entropy protocol, communication between the two parties occurs over HTTP rather than directly on the blockchain. This design choice boosts both the speed and simplicity of Entropy compared to other random number generation alternatives.

  • Unpredictability: Prior to requesting the random number, no participant should be able to foresee the random value with better-than-chance accuracy. This characteristic formally defines what it means to be "random."

  • Determinism: Once the random number is requested, only a single possible value can result. This ensures that participants cannot alter the outcome after the request has been made.

  • Liveness: Once the random number is requested, the protocol proceeds to completion, including the reveal phase.

For more information about Pyth Entropy, please refer to Pyth's docs: https://docs.pyth.network/entropy

Last updated