Anthropic’s Claude Code AI identified a critical firmware flaw in Coldcard hardware wallets in roughly eight minutes, highlighting artificial intelligence’s growing capability in rapid cryptocurrency vulnerability detection. The automated analysis centered on how historical Coldcard firmware versions generated cryptographic random numbers, which are vital for deriving secure private keys and digital signatures.
Because the affected random number generator suffered from predictable entropy, attackers were able to derive private keys through large-scale computational analysis and drain funds from compromised wallets. The exploit triggered one of the largest security breaches in Bitcoin hardware wallet history, with initial losses exceeding 1,080 BTC in under an hour.
Subsequent community statistics indicate total stolen assets have surpassed $100 million. Onchain researcher Thorn reported 218 suspicious transactions across 462 victim addresses involving nearly 389 BTC between Bitcoin blocks 960,778 and 960,792 alone, confirming that automated draining activities remained active.
In response, security analysts are urging all affected Coldcard users to immediately transfer remaining assets to uncompromised setups, recommending higher transaction fees to ensure priority onchain confirmation before funds can be targeted again.
The speed with which Claude Code flagged the underlying cryptographic flaw has intensified discussions around automated auditing workflows. As large language models democratize both vulnerability identification and potential exploitation, market participants emphasize the urgent need for enhanced security frameworks, regulatory standards like MiCA, and updated defensive practices across crypto infrastructure.
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