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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 defined historical estimate—not a current running total or a count of every DeFi exploit. Flash loans supplied attackers with temporary capital; weaknesses in price feeds or protocol logic made the attacks possible.
What the $1.211 billion figure counts
The estimate comes from Hall and Stieger’s peer-reviewed Journal of Financial Crime article, accepted and listed as in press on August 7, 2026. The study records 72 flash-loan attacks and $1.211 billion in associated losses from February 2020 through July 2024. Across the same period, the researchers identified 254 successful DeFi attacks overall, with $6.568 billion in losses. The flash-loan incidents are a subset of that broader total, not an additional amount. The University of Winchester’s study record gives the figures and study period.
The researchers say they scanned 20.63 billion blockchain transactions across Ethereum, Base, Optimism, Arbitrum, BNB Chain, Avalanche, and Polygon, using SyntiFi’s on-chain risk intelligence engine. Those are the study’s stated dataset and method; they should not be read as proof that every chain or every attack was captured. Incidents after July 2024 are outside the measurement window.
How a flash loan can be used in an attack
A flash loan lets a borrower obtain cryptocurrency without collateral, provided the loan and any required fee are repaid within the same blockchain transaction. If repayment does not happen, the transaction generally reverts, so the borrowing does not persist as a conventional unpaid loan.
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The loan itself is a financing tool, not a vulnerability. An attack occurs when borrowed funds help exploit a flaw in a DeFi protocol. For example, an attacker might use borrowed tokens to move a token’s price on one venue, then rely on a vulnerable protocol that takes that distorted price as trustworthy. The attacker can extract value from the protocol, reverse the price-moving trade, and repay the loan before the transaction ends. This is one illustrative price-manipulation path, not a description of all 72 incidents. The University of Winchester’s explanation describes this kind of sequence.
Two broad weaknesses, 14 attack types
Hall and Stieger classify the 14 attack types they identified into two broad families:
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- Price-feed manipulation: An attacker distorts or takes advantage of a price source that a protocol uses to value assets or make decisions.
- Protocol-logic exploits: An attacker takes advantage of a flaw in the rules or implementation of a protocol—for example, how it handles a function, a sequence of transactions, or a governance action.
A flash loan can make either kind of exploit more powerful by briefly providing substantial capital. But having access to borrowed funds does not, by itself, create the vulnerable price feed or faulty protocol logic.
What secondary reporting says about the distribution of losses
Decrypt’s October 6, 2026 report on the study adds detail about where losses occurred and how the mix of attacks changed. These breakdowns are reported by Decrypt as findings from the paper, rather than figures independently confirmed here against the full article text.
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- More than 80% of flash-loan losses were on Ethereum, according to Decrypt’s account of the study.
- Four attack types—price-oracle attacks, donate-function logic exploits, reentrancy attacks, and one governance attack—accounted for more than 81% of losses.
- The reported share of losses from logic exploits rose from 28% in February 2020–January 2022 to 55% in February 2022–July 2024.
These figures describe different cuts of the study’s historical dataset. In particular, the shift in logic-exploit share compares two periods within the study window; it does not establish what the distribution has been since July 2024. Decrypt’s report attributes the detailed breakdowns to Hall and Stieger’s paper.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What the findings do—and do not—show
The study’s central security lesson is that a flash loan can amplify an exploit, but the protocol weakness is the crucial opening. A transaction-level borrowing rule limits how long funds are borrowed; it does not guarantee that the protocols touched by a transaction use reliable prices or correctly enforce their own logic.
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The totals are also bounded by the study’s stated dates, chains, and detection approach. They are useful for understanding the scale and reported patterns of attacks observed in that analysis, not for claiming a complete global tally of DeFi losses. As Professor Tim Hall of the University of Winchester put it, “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.”
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