This New Tool Prevents Bots From Taking Over NFT Drops

As the use of non-fungible tokens (NFT) has skyrocketed within the art world, and as other industries such as media, sports and entertainment, have implemented them as revenue generators over the past year, so have automated bots that make this new revenue model less valuable for artists and companies.

These bots aren’t new though – many were originally generated from the high-end sneaker market and in recent months have permeated the blockchain. Not only do these bots deepen inequity within the marketplace but they also ultimately manipulate the prices of the resale market. In January 2021, the Yeezy ‘Sun’ drop retailed at approximately $250, but the shoes could be found on resale sites for around $600 that same day.

In September 2021, Time Magazine launched thousands of NFTs, but their launch was taken over by scalper bots, despite precautions put in place to limit the number of NFT purchases per person. This drop also resulted in inflated transaction fees on the blockchain network.

A new tool developed by researchers at Cornell Tech, led by PhD student Yan Ji and research engineer Tyler Kell, aims to enforce a one-NFT-per-person drop policy. A successful demo took place at ETH Denver this week, where attendees established unique identities to participate in a free NFT drop with prominent digital artist Zach Lieberman.

The smart contract technology tool the team developed establishes unique identities for participants to confirm they are not bots. The tool verifies legal names from trustworthy websites such as the Social Security Administration (the data is confidentially collected and processed through a trusted execution environment so that the information cannot be accessible by anyone including the developers) or alternatively by decentralized identities based on Proof of Attendance Protocol.

“NFTs were designed to democratize the future of art-buying, but for the most part, only people whose skills are technologically advanced enough have been consistently successful at acquiring these works,” said Cornell Tech research engineer Tyler Kell. “This new technique that our team developed will allow for NFT drops to be equitable and fair and ultimately improve the market overall.”

While previous attempts at preventing bots from taking over NFT drops have included a variety of solutions that allow sellers to target a specific individual including white lists, limiting unique crypto wallets and limiting the number of purchases per person. Each of these have been circumvented in different ways, as social media accounts are not strong credentials and users can purchase accounts to get on white lists.

The researchers intend to further this work by potentially developing other desirable tools and techniques such as sophisticated collector analysis and bot identification that can be used to establish a more equitable NFT market.