Orbital EMP

Screenshots

Problem Statement

This project would allow airdrop creators to setup their airdrop campaigns with built-in anti-sybil provisions. They would provide the list of airdrop eligible wallets, which will be screened via clustering or any other automated anti-sybil tooling. These tools can be aggressive (high false positive), because users will be able to seek recourse for being wrongly flagged as a bot.Users can visit the site to check their drops and attempt to claim them, and those who find themselves flagged as a bot may use their world id to verify their humanity.This means the process should be frictionless for most users, while power users with multiple wallets that seem suspicious have a means of verifying themselves and separating themselves from the bot farmers.

Solution

The project consists of two parts: the T3-based client and an additional flask backend. The T3 stack forms the main scaffold and glue for the project:discord oauth2 logins via nextauthdrizzle to setup and manage the postgres databasetrpc to query the database conveniently as an APIchakraUI for building styles componentsFor the users that fail the sybil detection, an option to verify their humanity is done through integrating worldid: this is done by simply using worldidkit and allowing logins via QR code (+worldapp) which then grants the user a verified status.For sybil detection, we use the Louvain Algorithm via a convenient python library, networkx, all accessible via flask. For the transaction data, I would have liked to use a subgraph but within the time constraints, I couldn't find one with the suitable transaction data.