Chainlink Unveils New Data Feed Integration with Polygon zkEVM for Enhanced Blockchain Functionality

Chainlink, the decentralized oracle network, has announced the launch of its data feeds on Polygon’s zero-knowledge scaling solution, which is compatible with the Ethereum Virtual Machine. This move, as reported in a press release shared with crypto.news, represents a significant enhancement for blockchain developers, enabling them to build decentralized applications on Polygon’s zkEVM with improved resistance to API downtime and flash loan attacks.

Marc Borion, head of Polygon Labs, heralded this integration as a crucial step that will pave the way for the deployment of several significant protocols on the Polygon zkEVM platform in the early part of the next year. He emphasized the potential of Chainlink oracles in unlocking a wide array of DeFi applications. These applications are expected to leverage the unique benefits of a ZK rollup, including rapid finality and robust security.

Chainlink oracles function as decentralized applications that bridge blockchains with off-chain data sources. They enable smart contracts to access essential real-world information such as prices, events, and other pertinent data not inherently stored on the blockchain. This functionality is crucial for the accurate and efficient operation of many blockchain-based applications.

In an interesting turn of events in November 2023, Chainlink acknowledged the efforts of whitehat hackers Zach Obront and Or Cyngiser (Trust) by awarding them a $300,000 bounty. This reward was given in recognition of their discovery of a critical bug in Chainlink’s Verifiable Random Function (VRF). The VRF is a random number generator that allows smart contracts to access random values securely. The discovered bug, if exploited, could have severely compromised the integrity of this system.

A year prior, Trust and Obront had identified a potential vulnerability where a malicious VRF subscription owner could manipulate the random number generation process. Their experiments showed that by blocking and rerolling randomness, it was possible to force users to receive an unfavorable outcome while securing a desired value for themselves.