Binance hack: no artificial intelligence behind the laundering of the 6.4 billion dollars

Elliptic’s analysis of the October Binance hack found no evidence that artificial intelligence played a role in laundering the $6.4 billion in stolen funds, contrary to speculation that AI tools had been used to obscure the money trail. The blockchain forensics firm traced the movement of the assets across wallets and chains, concluding that the laundering followed patterns consistent with manual or rule-based operations rather than machine-learning-driven obfuscation. The finding matters because AI is increasingly marketed as a core tool for on-chain compliance and threat detection, and the case offers a high-profile test of how much automation is actually driving illicit-fund tracing. With $6.4 billion at stake, the episode also underscores the scale of the October incident relative to typical exchange breaches. What to watch next is whether Elliptic and other analytics firms publish further breakdowns of the laundering routes, and whether AI-based monitoring tools can demonstrate measurable advantages in tracking the remaining funds.