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Clear out junk files and repair common Windows errorsFree Scan →Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →A study by Tim Hall and Remo Stieger estimates that 72 flash-loan attacks caused $1.211 billion in losses between February 2020 and July 2024. That is a historical estimate for the incidents and chains the researchers analyzed—not a live total of DeFi losses or a count that includes attacks after July 2024.
What the $1.211 billion figure includes
Hall and Stieger’s peer-reviewed Journal of Financial Crime article, accepted and in press on 7 August 2026, identifies 72 flash-loan attacks with $1.211 billion in losses during the study period. Across the broader set of 254 successful DeFi attacks they identified, losses totaled $6.568 billion. The flash-loan incidents are a subset of that broader attack count, not an additional category to add to it. University of Winchester research record
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The study covers February 2020 through July 2024. Its figures therefore do not describe later incidents, and should not be read as an up-to-date cumulative loss tracker.
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How the researchers assembled the dataset
The University of Winchester says the analysis examined seven chains on which flash loans are available: Ethereum, Base, Optimism, Arbitrum, BNB Chain, Avalanche, and Polygon. The researchers used SyntiFi’s on-chain risk intelligence engine to scan 20.63 billion blockchain transactions. These details describe the study’s dataset; they do not establish that every attack on every chain was detected. University of Winchester institutional release
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How a flash loan can be used in an attack
A flash loan lets a borrower access cryptocurrency without collateral, provided the borrowed amount is repaid within the same blockchain transaction. That constraint makes the loan a source of temporary capital, not by itself a vulnerability or an attack.
For example, an attacker could borrow funds, use them to move a token’s price on one venue, then exploit a separate protocol that relies on that temporarily distorted price. The attacker may reverse the market move, repay the loan before the transaction ends, and keep assets taken from the vulnerable protocol. This is one possible price-manipulation path, not a description of every incident in the study.
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The crucial weakness lies in the protocol’s handling of prices, rules, or state changes. The loan can make a large or rapid exploit possible, but a sound protocol should not become vulnerable simply because a user can briefly borrow a large amount.
Two broad kinds of weakness, 14 attack types
Hall and Stieger identify 14 flash-loan attack types grouped into two broad families: manipulation of price feeds and exploitation of flaws in protocol logic. The first family targets how a protocol determines an asset’s value. The second takes advantage of unintended behavior in how the protocol’s code processes transactions or enforces its rules. University of Winchester research record
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What secondary coverage reports about where losses came from
Decrypt’s 6 October 2026 report, attributing the figures to the study, says more than 80% of flash-loan losses occurred on Ethereum. It also reports that four attack types—price oracle attacks, donate-function logic exploits, reentrancy attacks, and one governance attack—accounted for more than 81% of losses. These are shares reported in secondary coverage of the paper, rather than figures independently confirmed here against its full text. Decrypt report, 6 October 2026
The same report says logic exploits made up 28% of losses from February 2020 through January 2022, rising to 55% from February 2022 through July 2024. The comparison concerns the share of flash-loan losses attributed to logic exploits in those two periods; it is not a comparison of total loss amounts.
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What the study does—and does not—show
The findings show that flash loans featured in a substantial set of costly DeFi attacks during the period studied. They do not mean flash loans are inherently malicious: the mechanism enables within-transaction borrowing, while the attack depends on a weakness in a protocol or its price inputs.
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Professor Tim Hall of the University of Winchester described the broader stakes this way: “We now are seeing crimes that we have never seen before and ones that are capable of stealing mind-boggling sums of money, often in the tens of millions of dollars.” University of Winchester institutional release
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