A fake job interview and a compromised artificial intelligence (AI) tool reportedly played key roles in a cyberattack that resulted in the theft of $6.3 billion in cryptocurrency from Binance, according to the exchange’s initial incident report.
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Binance, the world’s largest cryptocurrency exchange, said hackers compromised a computer used by a wallet developer before exploiting internal systems to gain control of the company’s digital wallets.
The incident, which culminated in the cryptocurrency theft on October 29, began with an advertisement promoting a modified version of a legitimate software tool. The compromised tool was reportedly used to initiate a chain of security breaches within the organisation.
How the Binance cyberattack began
According to Binance, the breach originated in June when a wallet developer inadvertently installed a compromised AI tool on a workstation.
The exchange said it detected the initial incident, replaced the affected device and updated credentials. However, the attackers had already compromised the roles and access associated with the affected employees and other members of the wallet team.
The attackers later used the compromised workstation, along with an internal AI tool, to target the systems of two wallet developers on October 20.
The incident report described how the hackers used credentials stolen from the first developer to gain access to the second developer’s system and trigger a malicious script.
This allowed the attackers to move deeper into the company’s systems and ultimately compromise its digital wallet operations.
Binance strengthens AI-based security
Following the incident, Binance said it was expanding investment in AI-driven threat detection to improve its ability to identify suspicious activity and prevent similar attacks.
The company also announced plans to establish a security research fund and develop specialised partnerships with leading AI companies.
The incident highlights the security risks associated with compromised software, stolen employee credentials and access to internal development systems.
It also demonstrates how attackers can exploit trusted tools and workplace processes to gain access to sensitive corporate infrastructure.
As companies increasingly integrate AI tools into software development and daily operations, securing employee devices, verifying software sources and monitoring internal access have become important parts of cybersecurity.
