Impersonation scams surged in 2025, exploding by roughly 1,400% and driving some of the largest losses in crypto fraud history. Chainalysis’ analysis shows scammers leaned on AI, voice cloning and fake customer‑support setups to scale attacks, pushing on‑chain scam losses into the low double‑digit billions. The problem wasn’t just more scams — each incident grew dramatically more costly. The average take from impersonation schemes jumped more than 600% year‑over‑year, turning what once were small cons into six‑ and seven‑figure heists. Chainalysis points to automated tooling and off‑the‑shelf phishing services that let bad actors run scams like factories, churning out polished social‑engineering campaigns at scale. AI was central to the shift. Reporters and industry analysts recorded widespread use of AI‑generated voice and face clones plus highly convincing messages to impersonate exchange staff, celebrities or close contacts. Those deepfakes expanded both reach and conversion rates: industry writeups show AI‑enabled scams were several times more profitable than older approaches. A high‑profile example involved scammers posing as a major exchange and siphoning nearly $16 million in a single coordinated operation — a headline case that highlighted how quickly impersonation attacks can become mass theft when combined with refined fake identities and organized social engineering. Chainalysis’ findings also describe scam groups operating more like small businesses. Criminal networks outsource pieces of the fraud chain — buying deepfake clips, commissioning scripts, and hiring money movers — which makes operations more efficient and harder for law enforcement to disrupt. One analysis estimated AI‑assisted schemes were about 4.5 times more profitable than traditional scams, a gap attackers exploited to scale up rapidly. Total loss estimates for 2025 vary by tracker. Some monitors put on‑chain thefts at around $14 billion, while Chainalysis suggests the figure could reach $17 billion once more incidents and off‑rail thefts are included. The spread reflects how fast new cases were uncovered and how many thefts shifted away from public on‑chain visibility. Featured image: Unsplash. Chart: TradingView. Read more AI-generated news on: undefined/news

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