Overview

Flipside is a platform that let users to get paid to learn about protocols and chains, and level up to become a crypto-SQL superstar. There, users can do several specific tasks (called bounties) and be paid in tokens, while learn about different projects like Sushiswap, Polygon, Thorchain, Solana, Algorand among others.

However, there are some users trying to "farm" Flipside rewards. But, are we able to find these users?

Methods

The idea is to look for participants that collect multiple times for the same bounty or hunt and then transfer all of their token incentives to the same address. For this analysis, only Ethereum and Solana chain bounties and hunts have been taken into account from 2022.

Inclusion criteria employed:

• Destination wallets with no more than 100k transactions received to avoid some pools, platforms, etc.
• More than 5 analysts sending to the same destination wallet
• Average transfers per analyst higher than 1 in the same destination wallet
• Number of same bounties received by analysts from Flipside higher than 3
• Total received by destination wallet **<**average same bounties * analysts involved * max amount received from Flipside

Ethereum chain

Looking at the Ethereum chain, we have found more than 30 possible bad actors. In the analysis, we can see the bad actors involved and the average of duplicated bounty by each destination wallet as well as the total amount (USD) received and the average transfers done per bad actior by each wallet destination.

In the table, we can find the following metrics:

• the number of other possible wallets involved
• the common destination wallet
• the average same bounties
• the number of transfers
• the total amount
• last tx date

Solana chain

Looking at the Solana chain, we have found less than 30 possible bad actors. In the analysis, we can see the bad actors involved and the average of duplicated bounty by each destination wallet as well as the total amount (SOL) received and the average transfers done per bad actor by each wallet destination.

In the table, we can find the following metrics:

• the number of other possible wallets involved
• the common destination wallet
• the average same bounties
• the number of transfers
• the total amount
• last tx date

Conclusions

• We can see how considering Ethereum chain bounties, there are a possible bad actor using more than 70 accounts! As well, the major of the potential bad actors have farmed between 500 and 2.5k USD from @flipsidecrypto bounties and hunts.
• Looking at the Solana chain, we have found a lower number than in Ethereum. In this case, the maximum amount of wallets involved in a same possible bad actor is 15. The average amount maybe farmed from Solana @flipsidecrypto bounties have been between 20 and 200.