Sandwich Attacks

The Marginal Effects of Ethereum Network MEV Transaction Re-Ordering ArXiv ID: 2508.04003 “View on arXiv” Authors: Bruce Mizrach, Nathaniel Yoshida Abstract Two MEV builders now produce nearly 80% of Ethereum blocks. Block builders have the ability to reorder transactions on the blockchain in a way that can be harmful to participants. We estimate they would pay in the aggregate nearly $14 million per month to ensure that they remained in the first quartile of the block. Sandwich attacks, in which a transaction is front-run, are frequent, averaging more than one per block. Gas fees on these transactions pay for nearly 15% of the MEV payments to the validator. These attacks have especially large marginal effects and skew the distribution. Reforms such as gas fee priority or private transaction pools might be helpful. ...

Price manipulation schemes of new crypto-tokens in decentralized exchanges ArXiv ID: 2502.10512 “View on arXiv” Authors: Unknown Abstract Blockchain technology has revolutionized financial markets by enabling decentralized exchanges (DEXs) that operate without intermediaries. Uniswap V2, a leading DEX, facilitates the rapid creation and trading of new tokens, which offer high return potential but exposing investors to significant risks. In this work, we analyze the financial impact of newly created tokens, assessing their market dynamics, profitability and liquidity manipulations. Our findings reveal that a significant portion of market liquidity is trapped in honeypots, reducing market efficiency and misleading investors. Applying a simple buy-and-hold strategy, we are able to uncover some major risks associated with investing in newly created tokens, including the widespread presence of rug pulls and sandwich attacks. We extract the optimal sandwich amount, revealing that their proliferation in new tokens stems from higher profitability in low-liquidity pools. Furthermore, we analyze the fundamental differences between token price evolution in swap time and physical time. Using clustering techniques, we highlight these differences and identify typical patterns of honeypot and sellable tokens. Our study provides insights into the risks and financial dynamics of decentralized markets and their challenges for investors. ...