Sandwich attacks involve a malicious actor placing two transactions around a victim’s pending trade on a decentralized exchange. This maneuver aims to profit from the price change induced by the victim’s original transaction. The attacker executes a purchase before the victim’s order and a sale immediately after, effectively ‘sandwiching’ the victim’s trade. This strategy exploits transaction ordering vulnerabilities on blockchain networks to extract value.
Context
The prevalence of sandwich attacks remains a significant concern within decentralized finance ecosystems. Developers are actively seeking mitigation strategies, including private transaction relays and improved consensus mechanisms, to diminish their effectiveness. These attacks highlight the ongoing challenges in ensuring fair and transparent transaction execution on public blockchains. News reports frequently cover new approaches to combatting this form of extractable value.
Foundational research establishes a surprising link: any Differential Privacy mechanism can be repurposed to eliminate algorithmic bias in transaction ordering, providing a provable defense against MEV.
This research quantifies the significant economic costs and market distortions caused by Maximal Extractable Value (MEV) transaction re-ordering on Ethereum, revealing hidden burdens on users and the critical need for systemic reforms.
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