Binance and Kraken, two major cryptocurrency exchanges, were targeted by social-engineering hacks similar to a recent attack on Coinbase, according to sources familiar with the situation.

Both exchanges successfully thwarted the attacks without compromising customer data.

Binance uses AI tools to detect such attempts in multiple languages and limits employee access to customer information during only customer-initiated interactions.

Kraken declined to comment on cybersecurity issues.

Social-engineering attacks have increased in the cryptocurrency sector over the past two years.

Hackers manipulate individuals to reveal confidential information and use stolen data to impersonate customers and execute fraudulent transactions.

🔗 Source: Bloomberg

🧠 Food for thought

1️⃣ Social engineering attacks represent a strategic shift in crypto cybercrime

The attacks on Coinbase, Binance, and Kraken represent a notable evolution in cryptocurrency hacking strategies from direct technical exploits to targeting human vulnerabilities.

Early cryptocurrency hacks like Mt. Gox (which lost $460 million) and Bitstamp (which lost $5 million in 2015) primarily exploited technical vulnerabilities in exchange infrastructure 1.

Current attacks show a sophisticated approach focused on manipulating employees through bribes, a tactic that proved successful at Coinbase but was thwarted at Binance and Kraken through AI-driven detection systems 2.

This shift reflects the “hardening” of exchange technical security over time, forcing attackers to target what remains the weakest link: humans with privileged access.

The Bitstamp hack from 2015 involved a phishing campaign targeting specific employees before accessing server infrastructure, which aligns with the social engineering tactics seen in recent attacks 3.

2️⃣ Cryptocurrency market cycles consistently correlate with cybercrime waves

The original article’s observation that “upticks in attacks tend to coincide with a jump in the value of digital currencies” is supported by multiple historical patterns.