Updates 30.10.2026
The Binance hack: what we know so far
As crypto thefts go, the Binance hack is the largest on record, but its real lesson applies to any business that moves money through software.
Updates 30.10.2026
As crypto thefts go, the Binance hack is the largest on record, but its real lesson applies to any business that moves money through software.
Binance, the world’s largest crypto exchange, has confirmed losing around $6.3bn on 29 October. Blockchain analysts at TRM Labs traced roughly $6.36bn leaving Binance wallets across ten blockchains, most of it within about 20 minutes from 20:05 UTC. That is around four times the $1.5bn Bybit theft of February 2025. Until this week, DeepStrike’s ranking of the biggest crypto hacks had Bybit at number one.
TRM attributes the attack with high confidence to TraderTraitor, North Korea’s elite hacking unit, the same group the FBI blamed for Bybit. Chainalysis CEO Jonathan Levin has also pointed to TraderTraitor, citing links to previous attacks. Not everyone agrees yet: Elliptic, another blockchain analytics firm, has urged caution, noting the laundering differs from earlier patterns in speed and method, and no root cause has been published.
“TRM estimates the attacker now holds around $2.4bn in ETH and BTC beyond any issuer’s reach” Nick Harris, CISO, Assured
Binance’s preliminary finding is that a compromised DevOps engineer’s laptop gave the attacker access to a service container, from which unauthorised withdrawal transactions were submitted. It has found no evidence that wallet private keys (the secret codes that authorise crypto to be moved) were leaked. Co-CEO Richard Teng has stressed this was a complex process rather than misuse of one engineer’s permissions, and no individual has been blamed.
The on-chain evidence tells the same story from the other end. Wallets on ten different chains, using different key types and signing schemes, all produced valid signatures for the attacker within roughly half an hour. TRM’s assessment is that the attacker gained the ability to make Binance’s hot wallet signing system sign whatever it chose. In other words, the keys were never stolen. The machine that uses the keys was made to do the attacker’s bidding.
It was also carefully planned. Staging began at least 36 hours earlier, with the attacker funding an operator wallet through Tornado Cash, a service that mixes crypto transactions together to hide where funds came from. It then tested its code on two wallets, rehearsed on a third, and installed the same code on a Binance hot wallet four hours later. A hot wallet is connected to the internet so it can process withdrawals quickly, unlike a cold wallet, which is kept offline and is much harder to attack. The code was installed using one of 50 authorisations signed in advance by the hot wallet itself. Because the wallet was in constant use, preparing 50 made sure one would still be valid when used. Once it took effect, the wallet’s balance was swept to the attacker, and new funds arriving over the following hours were swept too.
Laundering started immediately. About $325m in USDT (Tether) was sold to market makers at a discount of more than 10%. USDT is a stablecoin, a cryptocurrency pegged to the US dollar. The companies that issue stablecoins such as USDT and USDC can freeze tokens, so the attacker had good reason to sell quickly. More was used as collateral to borrow Ether (ETH), the currency of the Ethereum blockchain, on Aave, a crypto lending platform where users borrow against assets they deposit. TRM estimates the attacker now holds around $2.4bn in ETH and bitcoin (BTC) beyond any issuer’s reach.
Strip away the blockchain detail and this is a familiar pattern: compromise an engineer, pivot to an internal service, then cause damage or steal data.
Four areas deserve particular attention.
“Treat engineer and admin endpoints as crown jewels.” Nick Harris, CISO, Assured
1. Protect devices with privileged access
Treat engineer and admin endpoints as crown jewels. Threat actors beyond North Korea routinely get in through people: impersonating IT staff, ClickFix lures, fake recruiters and trojanised apps. Use dedicated conditional access policies for privileged accounts, phishing-resistant MFA, and endpoint detection and response (EDR) tools tuned to alert on new developer tooling.
2. Limit access to live systems
Remove standing access to production from laptops. Admin access should be just-in-time, brokered through a bastion host, short-lived and recorded. No engineer device should be able to open a shell inside a container that can initiate payments.
3. Make payment checks independent
Put an independent check between “request” and “release”. Value limits, beneficiary allow-lists and out-of-band approval above thresholds should be enforced by a separate system the requesting service cannot modify.
4. Keep authorisations narrow and short-lived
Kill long-lived pre-authorisations. The 50 pre-signed authorisations have everyday equivalents: long-lived API tokens, standing payment mandates and pre-approved batch files. Give them short expiry and narrow scope.
Watch the behaviour of systems, not just users. Alert on bursts of activity and on out-of-hours data access or movement.
Watch for new paths. An engineer’s identity or laptop talking to a service or system for the first time, interactive sessions inside production containers, or code changes to components outside change windows can all be early warning signs.
For most businesses, we would expect a loss like this to fall under a commercial crime policy, or potentially the funds transfer fraud (FTF) section of a cyber policy. However, FTF cover in a cyber policy is usually subject to a sub-limit, given the volume of incidents typically occurring and the fact that many businesses would buy a crime policy. We would therefore expect the commercial crime policy to respond first, with the FTF cover in the cyber policy sitting in excess, subject to the terms and conditions of each wording.