Google’s quantum breakthrough exposes over $ $600 billion in Bitcoin and Ethereum to risk

A new paper from Google Quantum AI has sharply reduced the estimated hardware required to crack elliptic-curve cryptography used by Bitcoin and much of Ethereum, moving a long-running security debate closer to market terms.

At current market prices, the quantum computing risks could affect more than $600 billion in Bitcoin, Ethereum, and stablecoins.

The paper, co-authored by Google researchers, Ethereum Foundation researcher Justin Drake, and Stanford cryptographer Dan Boneh, says Shor’s algorithm for the 256-bit elliptic curve discrete logarithm problem can run with either no more than 1,200 logical qubits and 90 million Toffoli gates or no more than 1,450 logical qubits and 70 million Toffoli gates.

Google says those circuits could be executed on a superconducting, cryptographically relevant quantum computer with fewer than 500,000 physical qubits in a few minutes, roughly a 20-fold reduction from prior estimates of the number of physical qubits.

Notably, Google does not say such a machine exists today. Still, Ethereum Foundation’s Drake said his confidence in a so-called Q-day by 2032 had risen sharply and that he now sees at least a 10% chance that a quantum computer could recover a secp256k1 private key from an exposed public key by then.


Meanwhile, Google paired the paper with an unusual disclosure model, revealing that it engaged with the US government and used a zero-knowledge proof so outsiders could verify the resource estimates without receiving the underlying attack circuits.

The paper says progress in quantum computing has reached the point where publishing improved attack details in full has become less prudent, even as publishing trustworthy resource estimates remains necessary to motivate defenses.

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Bitcoin’s problem is partly a race and partly a stockpile

For Bitcoin, the paper’s immediate market hook is timing. It models an “on-spend” attack in which a quantum machine derives a private key after a user reveals a public key by broadcasting a transaction, then tries to syndicate a competing transaction before the original payment is confirmed.

The paper says a fast-clock superconducting machine could reduce the live attack window to about 9 minutes from a primed state, close to Bitcoin’s roughly 10-minute average block time.

Bitcoin Quantum Computing RiskBitcoin Quantum Computing Risk
Bitcoin Quantum Computing Risk (Source: Google)

Under the paper’s assumptions, that implies a theft success probability of slightly less than 41%.

Meanwhile, that is only one part of the Bitcoin story, as the paper pointed out that about 6.7 million BTC are sitting in vulnerable addresses. This is equivalent to roughly $444 billion, or nearly 32% of BTC’s total cap of 21 million coins.

Of this, the paper says old Pay-to-Public-Key scripts still secure more than 1.7 million BTC, worth about $112.6 billion at current market price, and that the total amount of dormant quantum-vulnerable Bitcoin may reach 2.3 million BTC across script types, or about $152.3 billion.

Those coins cannot all be migrated simply by asking current users to move funds, because many are thought to be abandoned, lost, or otherwise inactive.

Apart from that, the authors also argue that Taproot, despite its benefits for privacy and flexibility, reintroduced a quantum weakness because Pay-to-Taproot places the tweaked public key directly in the locking script.

They added that Grover-based attacks on Bitcoin mining remain impractical for decades, keeping the near-term focus on signatures rather than proof of work.

That leaves Bitcoin with two distinct problems. One is the risk of live transactions if a future fast-clock machine can reliably break keys within the settlement window. The other is a large stock of older or exposed coins that could become fixed targets in a post-CRQC world.

The paper explicitly states that every existing Bitcoin transaction type is vulnerable to on-spend attacks from a future fast-clock machine, while older P2PK outputs and modern P2TR outputs introduce at-rest exposure of their own.

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Ethereum’s quantum risk runs through wallets, validators, and tokenized assets

Meanwhile, the quantum risks for Ethereum are presented differently.

The paper says early fast-clock quantum computers are unlikely to launch the same kind of on-spend attack there because Ethereum produces blocks in deterministic 12-second slots, processes most transactions in less than a minute, and already relies heavily on private mempools.

Instead, the main quantum threat lies in at-rest attacks against long-lived accounts and the systems attached to them.

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