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Ethereum Researcher Urges Crypto Industry to Prepare 'Bunker Mode' Over AI Threat to Wallet Security
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Ethereum Researcher Urges Crypto Industry to Prepare 'Bunker Mode' Over AI Threat to Wallet Security

Ethereum researcher Justin Drake has urged the crypto industry to prepare for "bunker mode," warning AI could potentially break the cryptography securing

8 октября 2026 г.Источник: coindesk.com ↗

Ethereum researcher Justin Drake has called on the crypto industry to begin preparing for "bunker mode," warning that artificial intelligence could find a way to break the mathematics protecting bitcoin and ether wallets in the worst case "in months, not years."

"Today I call upon the blockchain industry to calmly start planning for 'bunker mode,'" Drake wrote on X on Wednesday, urging large holders to begin a gradual move of their funds to fresh addresses whose public keys have never appeared onchain.

A wallet uses a secret number, called a private key, to authorize payments. A related public key lets the network check those approvals. Generating the public key is easy, but working backward from it to the secret is supposed to take an impractical amount of computing work. Drake's concern is that AI may help someone find a shortcut, letting an attacker recover the secret and spend the coins on ordinary computers, with no need for the quantum machines the industry has been preparing for.

Millions of bitcoin sit in addresses whose public keys are already visible onchain, as CoinDesk has previously reported. On Ethereum, any account that has ever sent a transaction has revealed its key, and the stablecoins and tokenized funds issued on the network are controlled through that signature system as well. No practical attack on bitcoin or Ethereum's wallet keys has been demonstrated, and none appeared in the research reviewed by CoinDesk.

Ethereum co-founder Vitalik Buterin said AI could also weaken some quantum-resistant cryptography, though he cautioned that rushed wallet migrations can cause losses.

The warning followed OpenAI's release on Tuesday of 722 mathematical manuscripts produced by an unreleased model tested on approximately 4,000 research problems. Some findings have computer-checkable proofs, while others remain unverified and could contain errors, the company said. The manuscripts came from the model OpenAI said last month had solved the Navier–Stokes problem, one of seven Millennium Prize challenges in mathematics. Each result used, on average, computing power equal to roughly three hours of ChatGPT Pro reasoning, the company said.

Drake said the math behind bitcoin and ether wallet signatures, known as elliptic curves, follows tidy patterns that a powerful enough AI could learn to exploit. Hash functions, which turn any piece of data into a fixed-length digital fingerprint that can't be worked backward, are built to scramble information with as little pattern as possible.

AI-Assisted Attacks Already Causing Losses

  • Last December, Anthropic researchers showed frontier models could write working exploits against simulated copies of real DeFi contracts.
  • In late July, a volunteer group called the Bitcoin Red Team used AI models to sweep 390 Bitcoin software projects in about 27 hours, logging nearly 5,000 possible flaws, 85 of them rated critical.
  • On July 30, an attacker began draining Coldcard hardware wallets through a five-year-old firmware bug, taking at least 1,367 BTC, and maker Coinkite said it suspected AI helped find the flaw.
  • Days later, BTCPay Server confirmed attackers had stolen funds from merchants' Lightning nodes through a similar exploit.

Source: CoinDesk

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