In the world of cryptocurrencies, public listing of a new token often generates significant hype, in many cases causing its price to skyrocket in a few seconds. In this scenario, timing is crucial to determine the success or failure of an investment opportunity. In this work, we present an in-depth analysis of sniper bots, automated tools designed to buy tokens as soon as they are listed on the market. We leverage GitHub open-source repositories of sniper bots to analyze their features and how they are implemented. Then, we build a dataset of Ethereum and BNB Smart Chain (BSC) liquidity pools to identify addresses that serially take advantage of sniper bots. Our findings reveal 14,029 sniping operations on Ethereum and 1,395,042 in BSC that bought tokens for a total of $10,144,808 dollars and $18,720,447, respectively. We find that Ethereum operations have a higher success rate but require a larger investment. Finally, we analyze token smart contracts to identify mechanisms that can hinder sniper bots.
Ready, Aim, Snipe! Analysis of Sniper Bots and their Impact on the DeFi Ecosystem / Cernera, Federico; LA MORGIA, Massimo; Mei, Alessandro; Mongardini, ALBERTO MARIA; Sassi, Francesco. - (2023), pp. 1093-1102. (Intervento presentato al convegno ACM Web Conference 2023 tenutosi a Austin, Texas, USA) [10.1145/3543873.3587612].
Ready, Aim, Snipe! Analysis of Sniper Bots and their Impact on the DeFi Ecosystem
Federico Cernera;Massimo La Morgia
;Alessandro Mei;Alberto Maria Mongardini;Francesco Sassi
2023
Abstract
In the world of cryptocurrencies, public listing of a new token often generates significant hype, in many cases causing its price to skyrocket in a few seconds. In this scenario, timing is crucial to determine the success or failure of an investment opportunity. In this work, we present an in-depth analysis of sniper bots, automated tools designed to buy tokens as soon as they are listed on the market. We leverage GitHub open-source repositories of sniper bots to analyze their features and how they are implemented. Then, we build a dataset of Ethereum and BNB Smart Chain (BSC) liquidity pools to identify addresses that serially take advantage of sniper bots. Our findings reveal 14,029 sniping operations on Ethereum and 1,395,042 in BSC that bought tokens for a total of $10,144,808 dollars and $18,720,447, respectively. We find that Ethereum operations have a higher success rate but require a larger investment. Finally, we analyze token smart contracts to identify mechanisms that can hinder sniper bots.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
