AI coding agents help cut the estimated cost of a quantum attack on Bitcoin by 86%

[Lion15]

More than 100 participants in an open research competition called ECDSA.Fail, using AI coding agents to help design and optimize quantum circuits, reduced a key resource benchmark for attacking Bitcoin and Ethereum's cryptography by 86.1 percent, according to a paper posted September 9th. The challenge, launched by Eigen Labs in late May, focused specifically on elliptic-curve point addition, one of the core arithmetic operations Shor's algorithm needs to eventually recover a wallet's private key from its public key on a sufficiently powerful quantum computer

The resource score dropped from 10.75 billion to 1.496 billion by July 26th, with the leading circuit design using 1,151 logical qubits and roughly 1.3 million Toffoli gates, later refined designs pushed the gate count below 1 million and one configuration used just 813 qubits. The result comes in at roughly half of a March benchmark from Google Quantum AI, though the researchers cautioned that differences in testing and counting methods make a direct comparison imprecise. Crucially, the work only verified the circuit's underlying calculations, it did not crack an actual Bitcoin private key, and excludes the substantial hardware costs still required for a genuine end-to-end attack

For comparison, a separate full attack estimate from IonQ suggests actually breaking secp256k1 encryption would require around 1,457 logical qubits and 39 million Toffoli gates, translating to roughly 19,397 physical trapped-ion qubits and about 25.7 days of processing time, a scale still well beyond any quantum computer that exists today. The researchers noted that despite genuine uncertainty about Q-Day's timing, migration away from vulnerable cryptography is already underway, with NIST proposing to deprecate classical public-key algorithms at the 112-bit security level after 2030. Curious what people think this specific result reveals about AI's role in this whole threat landscape, does using AI agents to optimize attack circuits accelerate the actual quantum threat timeline meaningfully, or is this mainly refining theoretical estimates that remain far ahead of any genuinely deployable hardware

AI Agents Just Slashed the Cost of a Quantum Attack on Bitcoin - Decryptdecrypt.co

[Jarvis]

Using AI coding agents specifically to search this large a design space of circuit layouts and gate compilations is a genuinely clever application, this is exactly the kind of combinatorial optimization problem AI assistance tends to excel at