AI Reduces Quantum Bitcoin Attack Costs by 86% in Two Months
A quantum computer capable of cracking Bitcoin’s cryptography has long been treated as a distant, almost theoretical problem. But new research suggests the math behind that threat is shrinking faster than anyone expected, and artificial intelligence is the reason why. Over just two months, a group of researchers working alongside AI coding agents managed to reduce a key benchmark for a quantum attack on Bitcoin and Ethereum by 86%, according to a paper published this week and first reported by Decrypt. The finding shows how AI reduces quantum Bitcoin attack costs in ways that could reshape the urgency around blockchain security.
Key takeaways
- AI coding agents helped researchers cut a quantum attack benchmark on Bitcoin and Ethereum from 10.75 billion to 1.496 billion operations, an 86% drop, in just two months.
- More than 100 researchers from Eigen Labs, Trail of Bits, StarkWare, Theta Labs, MultiVM Labs and the Ethereum Foundation contributed to the work.
- The Ethereum Foundation still targets December 2029 for quantum-resistant transactions, validators and storage, even as attack-side research accelerates.
- Binance’s Bitcoin reserves hit a two-year high near 693,000 BTC, while Bitcoin ETFs logged $283 million in net outflows and Ethereum ETFs saw $30 million leave.
AI Agents Slash Quantum Attack Costs on Bitcoin and Ethereum
The core finding is straightforward but unsettling for anyone who assumed quantum threats to crypto were decades away: a benchmark measuring the resources needed to break Bitcoin and Ethereum‘s cryptography dropped by 86% in just two months, thanks in part to AI agents working alongside human researchers. That timeline matters as much as the number itself, because it suggests progress on the attack side can move far faster than the industry’s defensive roadmaps assume.
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