AI Crypto Crime: Deepfakes, Fake Support, Phishing

AI crypto crime has moved out of its niche and onto the agenda of analysts and regulators. On August 21, 2026, The Block reported on the new “AI-in-Crime Adoption Index” from TRM Labs, which assesses the role of artificial intelligence in crypto-related crime in a systematic way. One caveat matters here: The Block summarises the TRM Labs analysis, but it supplies no independent global statistics on crypto fraud. According to TRM Labs, AI is increasingly used to run existing attacks faster, in more convincing language and with sharper targeting. More AI in cybercrime does not automatically mean that every crypto loss has grown to the same degree. This article sets out which forms of attack gain plausibility, where the data gaps sit and which protective measures still count.

What Is Behind the AI Crypto Crime Trend

AI crypto crime describes the use of artificial intelligence to prepare, personalise or automate criminal activity in the crypto space. In practice, AI generates or improves text, translations, images, voices, chat replies and variations of a lure. It does not necessarily replace known fraud models; more often it amplifies classic social engineering, in which attackers exploit trust, helpfulness, fear, time pressure or apparent authority so that victims hand over data, connect a wallet or sign a transaction themselves. According to TRM Labs, fraud is the most advanced category for the use of AI in criminal contexts within its own index.