An Airdrop Cookbook by Hemera and TokenTable : Hemera & TokenTable’s Guide for AI-Powered Fair Token Distribution
Introduction
The first few months of 2024 have already been filled with a flurry of airdrops, and the remainder of the year will most likely follow suit in a similar fashion of airdrop frenzy. For projects looking to launch their token, sybil resistance and token distribution management are key points of discussion, as they directly flow into each other and help determine overall token allocations for the community. This article is a joint effort by Hemera and TokenTable to educate the community on best practices of managing airdrops when it comes to building sybil resistance mechanisms, and distributing tokens with the least amount of friction.
Hemera’s Airdrop Auditing
Traditional rule-based systems used for airdrop auditing have limitations in detecting sophisticated bot and sybil patterns. These systems rely on predefined rules and struggle to adapt to evolving fraudulent tactics, making them less effective in identifying new and emerging fraudulent behaviors.
To overcome the limitations of rule-based systems, Hemera offers an Unsupervised Machine Learning (UML) — powered solution for airdrop auditing:
Behavioural Detection: UML excels in discerning atypical behavioral patterns within vast datasets, proving highly adept at detecting bots that subtly mimic legitimate user behaviour. While bots may appear similar to genuine users on an individual basis, their suspicious activities become conspicuous when scrutinizing hundreds or thousands of instances, such as wallets or user profiles.
Adaptability to Emerging Threats: UML can adapt to new and evolving bot behaviours without the need for constant retraining. This is crucial in the context of rapidly changing bot tactics, as supervised methods may struggle to keep up with the diversity of new patterns.
Reduced Labelling Overhead: UML doesn’t require labeled datasets for training, saving the effort and cost associated with manually annotating data. This makes it more practical for scenarios where obtaining labeled data is challenging or expensive.
Discovery of Unknown Patterns: Unsupervised methods can uncover previously unknown patterns or trends in data. This is beneficial for detecting novel bot behaviours that might not be covered by predefined rules or labeled datasets used in supervised learning.
Community Friendly: Hemera’s UML algorithm provides clear output on the reasons behind its detections, allowing project teams to openly engage with the community and explain why particular wallets are classified as bots. By accurately identifying fraudulent behavior, project teams can optimize the distribution of airdrops, ensuring that genuine users receive the rewards they deserve.
Case Study
Hemera’s AI-powered solution outlined above has successfully identified various bot patterns in ZetaChain’s airdrop data snapshot from its product ZetaLabs. Given this data from their snapshot taken August 20th, 2023, Hemera’s solution was utilized to map out bot detection based on data across all connected chains. Through this methodology, over 300,000 addresses were identified as potential bots.
Here are three examples of key patterns found:
Pattern #1: Deceptive Funding Wallets
In this case, a group of 1000+ wallets in the same airdrop campaign exhibited suspicious behaviour. They made identical fund transfers of the same amount at the same time, using different funding wallets to mask their actions. Among them, more than 500 wallets followed the exact same transaction sequences during a specific timeframe. This indicates a highly advanced form of fraudulent activity.
The coordinated bot group demonstrated a suspicious behaviour by utilizing the same funding wallets to conduct identical transaction behaviours across the group. Notably, once these wallets received airdrops, they immediately executed transfers to the main wallet, a behaviour that is unusual for legitimate wallets.
Pattern #2: Complicated Transaction Sequence Patterns
Similar transaction behaviours were detected across various wallets, involving interactions with identical contract addresses in synchronized time sequences.
Pattern #3: Cross-Chain Bot Fraud
Hemera uncovered a sophisticated form of bot fraud called Cross-Chain Bot Fraud. Multiple bots collaborated across different blockchain networks, executing synchronized operations to deceive and manipulate the system for illicit gains.
Simplified token distribution with TokenTable
Building products in web3 in itself is a challenge, and the added pressure of building in-house solutions to manage token airdrops while ensuring the security of the infrastructure can be quite taxing to any team. It is with these constraints in mind that TokenTable is able to offer a secure, transparent and automated airdrop solution, so organizations can focus on building, and less on managing.
Some notable TokenTable case studies include conducting Zetachain’s >$20M airdrop to 14K+ wallet address, and helping manage Starknet Foundation’s investor token unlock. Here are some ways TokenTable can help you simplify the airdrop process.
Gated Access Token Claims
TokenTable has the capability to add gated access in the airdrop claiming process. This means that organizations could provide custom requests for gating airdrop access to particular NFT holders, issue a specific attestation for product usage, or require KYC details for users to access the airdrop.
ZetaChain for example implemented a KYC gated claim for their token airdrop. Airdrop participants were required to provide their KYC information, after which they were issued an on-chain attestation through Sign Protocol that allowed them to claim their respective tokens. Here is a demo of how TokenTable’s KYC gated access implementation.
Automated Token Distribution Using Smart Contracts
TokenTable is live across the Ethereum and EVM networks and utilizes smart contracts to manage token distribution. Through TokenTable you can create an unlocking schedule using the Token Unlocker contract and existing token recipients by uploading a CSV — the entire user journey is automated and seamless. Here is a quick demo of how uploading token recipients would look like. Naturally, security is of the utmost importance, therefore, TokenTable has been audited by both OtterSec and Nethermind Security.
Custom token claiming portals
In collaboration with the organization conducting the token airdrop, a custom claiming portal can be created and embedded in the organization’s website to avoid any confusion as to the authenticity of the claiming portal, or the location. Here is ZetaChain’s custom claiming portal for example linked to Zetahub.
Conclusion
The joint effort between Hemera and TokenTable is to encourage an equitable, transparent and efficient method for startups to conduct token airdrops. For founders, if you are planning your token airdrop and are confused about how to approach sybil resistance, or manage your token distribution, feel free to reach out to us — TokenTable, Hemera — and we will help you conduct your airdrop the best way possible.
