Free 30-min Web3 Consultation
Book Consultation
Smart Contract Security Audits
View Audit Services
Custom DeFi Protocol Development
Explore DeFi
Full-Stack Web3 dApp Development
View App Services
Free 30-min Web3 Consultation
Book Consultation
Smart Contract Security Audits
View Audit Services
Custom DeFi Protocol Development
Explore DeFi
Full-Stack Web3 dApp Development
View App Services
Free 30-min Web3 Consultation
Book Consultation
Smart Contract Security Audits
View Audit Services
Custom DeFi Protocol Development
Explore DeFi
Full-Stack Web3 dApp Development
View App Services
Free 30-min Web3 Consultation
Book Consultation
Smart Contract Security Audits
View Audit Services
Custom DeFi Protocol Development
Explore DeFi
Full-Stack Web3 dApp Development
View App Services
LABS
Glossary

Pyth Entropy

Pyth Entropy is a verifiable random number generation service from the Pyth Network, providing secure, low-cost, and fast on-chain randomness for applications like gaming and NFTs.
Chainscore © 2026
definition
DEFINITION

What is Pyth Entropy?

Pyth Entropy is a decentralized, on-chain randomness generation service designed for smart contract applications that require unpredictable and verifiable random inputs.

Pyth Entropy is a verifiable random function (VRF) service that provides on-chain randomness to smart contracts on supported blockchains. It functions as a decentralized oracle specifically for generating unpredictable numbers, which are crucial for applications like gaming, NFT minting, and lotteries. Unlike traditional oracles that deliver price data, Pyth Entropy aggregates randomness from multiple independent providers and commits the final result on-chain, ensuring it is tamper-proof and publicly verifiable.

The system operates by having a network of providers submit random values, which are then combined using a commit-reveal scheme and cryptographic hashing to produce a single, final random number. This process prevents any single provider from manipulating the outcome. The result is delivered directly to the requesting smart contract via a callback function, where it can be used to determine outcomes fairly and transparently. This mechanism is essential for creating provably fair applications where trust in the randomness source is paramount.

Key technical components include the Entropy contract, which manages requests and responses on the destination chain, and the Pythnet app chain, where providers aggregate their submissions. Developers integrate by calling the request function on the Entropy contract, specifying a callback contract and a fee. Once the randomness is generated off-chain and consensus is reached, the contract executes the callback with the verified random value, completing the request.

Primary use cases for Pyth Entropy span Web3 gaming (for loot drops or matchmaking), NFT projects (for random trait generation or allowlist selection), and decentralized finance (DeFi) protocols (for governance sampling or audit selection). Its security model, which relies on economic incentives and cryptographic proofs, makes it a robust alternative to other randomness solutions like chain-native VRFs or less secure on-chain methods like block hashes.

how-it-works
ON-CHAIN RANDOMNESS

How Pyth Entropy Works

Pyth Entropy is a decentralized oracle network that provides a secure, verifiable, and low-latency source of randomness directly on-chain, enabling applications like gaming, lotteries, and NFT generation.

Pyth Entropy is a verifiable random function (VRF) service that generates unpredictable random numbers, or entropy, for smart contracts on supported blockchains. Unlike traditional oracles that deliver price data, Pyth Entropy's primary function is to provide a cryptographically secure random seed that cannot be manipulated by users, miners/validators, or the oracle providers themselves. This is achieved through a multi-provider design where numerous independent data providers contribute to each random number, ensuring the output's integrity and unpredictability.

The core mechanism relies on a commit-reveal scheme. First, each provider generates a random number and submits a cryptographic commitment (a hash) of that number to the on-chain program. After a set period, providers then reveal their original numbers. The final random output is computed on-chain by combining all revealed values. This process guarantees that the result was determined fairly at the commitment stage, as providers cannot change their revealed number to influence the outcome. The system uses a BLS threshold signature to aggregate provider inputs efficiently, reducing on-chain computation and cost.

For a developer, integrating Pyth Entropy involves calling a specific instruction on the Entropy program, often paying a small fee in the native gas token. The request specifies a user-provided seed for uniqueness, which is combined with the oracle's random value. This design allows for request-specific randomness, meaning the same application can generate different, independent random outcomes for each user or transaction. The random result is then delivered directly to the requesting smart contract in a single transaction, enabling immediate use in logic such as minting an NFT with random traits or determining a game's outcome.

Key security properties include predictability resistance, where no party can predict the random number before it is generated on-chain, and bias resistance, preventing any entity from forcing a specific favorable outcome. The decentralized provider set mitigates the risk of a single point of failure or corruption. Pyth Entropy is designed for low-latency applications, with randomness typically available within a few blocks, making it suitable for real-time use cases that require fast and fair on-chain randomness without complex workarounds.

key-features
PYTH ENTROPY

Key Features

Pyth Entropy is a verifiable random function (VRF) service that provides secure, on-chain randomness for smart contracts. It is designed to be fast, cost-effective, and resistant to manipulation.

01

Verifiable Random Function (VRF)

Pyth Entropy is a Verifiable Random Function (VRF), a cryptographic primitive that produces a random output and a proof of its correctness. This allows any user to cryptographically verify that the random number was generated correctly and was not manipulated by the provider or any other party. It is the standard for generating provably fair randomness on-chain.

02

On-Demand & Permissionless

Unlike scheduled randomness oracles, Pyth Entropy provides on-demand randomness. Any smart contract can request a random number at any time by submitting a transaction. The service is permissionless, meaning any developer can integrate it without needing approval, enabling use cases like instant NFT minting, gaming, and lotteries.

03

Cost-Effective & Fast

The protocol is optimized for low latency and low cost. Randomness is typically delivered within a single block confirmation on supported chains, making it suitable for high-frequency applications. By leveraging a simple commit-reveal scheme with on-chain aggregation, it minimizes gas costs for end-users.

04

Decentralized Aggregation

Randomness is generated through a decentralized network of providers. Each provider submits an off-chain random value, which is then aggregated on-chain into a single, final random number. This design removes single points of failure and increases resilience against collusion or manipulation by individual providers.

05

Multi-Chain Availability

Pyth Entropy is deployed across multiple blockchain ecosystems. It is natively available on networks like Solana, and via cross-chain messaging protocols (e.g., Wormhole) to chains including Ethereum, Arbitrum, and Base. This provides developers with a consistent randomness primitive across their multi-chain applications.

06

Primary Use Cases

Pyth Entropy enables a wide range of applications that require secure randomness:

  • Gaming & NFTs: For loot boxes, character attributes, and fair minting mechanics.
  • DeFi: For random selection in lotteries, leaderboard tie-breaking, or governance tasks.
  • Security: As a source of entropy for generating private keys or nonces in cryptographic protocols.
ecosystem-usage
PYTH ENTROPY

Ecosystem Usage

Pyth Entropy provides a verifiable random number generator (RNG) for on-chain applications. It is used across DeFi, gaming, and NFTs where unpredictable, tamper-proof randomness is critical.

06

Comparison to Other RNGs

Pyth Entropy differs from alternative on-chain randomness solutions:

  • vs. Blockhash RNG: Block hashes are manipulable by miners/validators; Entropy uses a decentralized network of providers for unpredictability.
  • vs. Chainlink VRF: Both provide verifiable randomness, but Entropy is optimized for high frequency and low cost, often operating as a public good on specific L2 rollups.
  • vs. Commit-Reveal Schemes: Eliminates the complexity and latency of multi-phase user-driven schemes.
examples
PYTH ENTROPY

Example Use Cases

Pyth Entropy provides a verifiable random number generator (VRF) for on-chain applications. These cards illustrate its primary applications across DeFi, gaming, and NFTs.

RANDOM NUMBER GENERATION

Comparison with Other RNG Solutions

A technical comparison of on-chain random number generation mechanisms, focusing on security, cost, and performance characteristics.

Feature / MetricPyth EntropyVerifiable Random Function (VRF)Commit-Reveal SchemeBlock Hash Reliance

Cryptographic Guarantee

Verifiable Delay Function (VDF)

Verifiable Random Function (VRF)

Hash Commitment

On-Chain Verifiability

Resistance to Miner/Validator Manipulation

Latency to Result

< 1 sec

~2-4 blocks

~2 blocks

1 block

Gas Cost per Request

~150K gas

~300K-500K gas

~200K gas

< 50K gas

Requires Off-Chain Service

Unpredictability Liveness

Guaranteed after VDF delay

Depends on oracle liveness

Depends on participant honesty

Guaranteed

Primary Use Case

High-value, frequent on-chain requests

Provably fair outcomes (e.g., NFTs)

Multi-party games

Simple, low-stake randomness

security-considerations
PYTH ENTROPY

Security & Trust Considerations

Pyth Entropy is a verifiable randomness service for blockchains, designed to be secure, decentralized, and resistant to manipulation. Its security model relies on a network of independent providers and cryptographic commitments.

01

Decentralized Provider Network

Pyth Entropy sources randomness from a decentralized network of independent providers, eliminating reliance on a single point of failure. Each provider submits a random number, which are then aggregated to produce the final output. This design prevents any single provider from controlling or biasing the result, a critical defense against manipulation.

02

Commit-Reveal Scheme

The protocol uses a commit-reveal mechanism to ensure fairness and unpredictability. Each provider first submits a cryptographic commitment (a hash) of their secret random number. After all commitments are received, providers then reveal their numbers. This prevents providers from seeing others' submissions before revealing their own, thwarting last-second manipulation based on the aggregate result.

03

On-Chain Verifiability

Every step of the randomness generation process is recorded and verifiable on-chain. Users can cryptographically verify that:

  • The final random number correctly derives from the revealed provider inputs.
  • Each provider's revealed number matches their initial commitment.
  • No provider changed their submission after seeing others'. This transparency allows anyone to audit the process for correctness.
04

Economic Security & Slashing

Providers are required to stake PYTH tokens as collateral. Malicious behavior, such as failing to reveal a committed number or attempting to manipulate the output, can result in slashing—a portion of their stake is burned. This cryptoeconomic security model aligns provider incentives with honest participation, making attacks costly.

05

Resistance to MEV and Front-Running

By generating randomness on-demand for specific applications (like NFT mints or game outcomes), Pyth Entropy helps mitigate Maximal Extractable Value (MEV) and front-running. The commit-reveal delay and the unpredictability of the final number make it computationally infeasible for adversaries to predict or influence the result to their advantage before it is finalized.

06

Comparison to RNG Alternatives

Pyth Entropy provides distinct security trade-offs compared to other randomness solutions:

  • VS VRF (Verifiable Random Function): More decentralized than a single VRF oracle; avoids reliance on one secret key.
  • VS RANDAO/VRF in Consensus: Not dependent on a specific blockchain's consensus mechanism, making it more portable across ecosystems.
  • VS Centralized RNG: Eliminates the trust required in a single entity, providing cryptographic guarantees instead.
developer-integration
DEVELOPER INTEGRATION

Pyth Entropy

A guide to integrating Pyth Entropy, a verifiable randomness solution for on-chain applications.

Pyth Entropy is a decentralized randomness beacon that provides smart contracts with a secure, verifiable, and on-chain source of entropy for applications like gaming, NFTs, and lotteries. Unlike traditional oracles that deliver price data, Pyth Entropy generates random values by combining on-chain commitments from multiple providers with a user-provided seed, producing a final random number that is cryptographically verifiable on the blockchain itself. This process ensures the outcome is unpredictable, fair, and resistant to manipulation by any single participant.

The core mechanism relies on a commit-reveal scheme. First, each Entropy provider submits a cryptographic commitment of their random value. After a set period, they reveal the original value. The final random number is then computed on-chain using the revealed values and the user's seed. This design guarantees that the provider's contribution is fixed before the reveal, preventing them from influencing the result. The system's security is bolstered by a diverse set of providers, making collusion to bias the output economically impractical.

For developers, integration is streamlined through a simple request-and-callback pattern. A smart contract calls the request function on the Pyth Entropy contract, specifying a callback function and providing a unique seed. Once the reveal phase is complete, the Pyth network executes the callback, delivering the verified random number. This asynchronous model is gas-efficient and compatible with various blockchain architectures. Common use cases include determining loot box contents, selecting winners in a fair raffle, or generating unpredictable traits for generative art NFTs.

Key technical considerations include understanding the request fee, which is paid in the native gas token and covers the cost of the callback execution, and the fulfillment delay, which is the waiting period for the provider reveal phase. Developers must also ensure their callback function correctly handles the received random number and implements appropriate access controls. Testing integration on a testnet is crucial to verify the end-to-end flow and gas cost estimates before mainnet deployment.

Pyth Entropy distinguishes itself by being native to the application's blockchain, eliminating reliance on external, off-chain randomness sources that can be points of failure or trust. By providing a randomness primitive that is as publicly verifiable as any other on-chain transaction, it enables a new class of transparent and provably fair applications. Its integration represents a fundamental shift from opaque random number generation to a cryptographically secure standard for Web3.

PYTH ENTROPY

Frequently Asked Questions

Pyth Entropy is a decentralized random number generator (RNG) service for blockchain applications. These questions cover its core mechanisms, security, and integration.

Pyth Entropy is a decentralized, on-chain random number generation (RNG) service that provides verifiably random numbers for smart contracts. It works by aggregating random values from a permissioned set of providers (e.g., Pyth data publishers) who submit hashed commitments of their random numbers. Once all commitments are on-chain, providers reveal their numbers, which are combined using a commit-reveal scheme and hashed to produce a single, unpredictable random value for the requesting application. This process ensures the final output cannot be manipulated by any single provider or external observer.

ENQUIRY

Get In Touch
today.

Our experts will offer a free quote and a 30min call to discuss your project.

NDA Protected
24h Response
Directly to Engineering Team
10+
Protocols Shipped
$20M+
TVL Overall
NDA Protected Directly to Engineering Team