Illicit Crypto Flows Hit Record $158 Billion In 2025, TRM Says

bitcoinistPublished on 2026-01-30Last updated on 2026-01-30

Abstract

According to TRM Labs, illicit crypto flows reached a record $158 billion in 2025, driven by increasingly sophisticated scams using AI tools. Large language models, deepfakes, and voice cloning were employed to create believable messages and fake personas, helping fraudsters build trust before soliciting money through fake investments or false emergencies. These operations often function like small companies, using phishing kits and AI services to scale their efforts. While scam proceeds slightly decreased to $35 billion, the overall volume of criminal activity rose significantly. Despite improvements in scam-detection technology, the use of AI makes scams harder to identify and more convincing.

Scammers used new tools to widen their reach and to seem more real. According to TRM Labs, the use of large language models in scams jumped fivefold in 2025, helping fraudsters write believable messages, run many conversations at once, and trick people in different languages.

AI Tools Helping Con Artists Build Trust

Reports say AI images, voice cloning, and deepfakes are cutting the cost of making fake people who look and sound legit. These tricks have fed a pattern where criminals first make a target feel safe and then ask for money.

In some cases, a romance angle is used to win trust, and that trust is later turned into fake investment offers or bogus tax demands. This staged approach has let scams run longer and capture bigger sums from fewer victims.

A Rise In Industrial-Scale Fraud

Behind many of these schemes are groups that act like small companies. They hire people, sell tools, and reuse scripts to run campaigns in many places.

Some providers now sell phishing kits or offer AI-as-a-service to automate messages and replies, lowering the bar for new fraudsters and making scams easier to copy and spread.

Deepfake Calls And Targeted Hacks

Reports note that attackers have even used fake video calls to trick crypto workers into installing malware. In several incidents, victims were invited to what looked like normal Zoom meetings, only to find AI-generated faces on the screen.

When the meeting “needed a patch,” victims were urged to install what was actually malicious software. These methods have been linked to North Korea–connected groups and were flagged by security researchers last year.

BTCUSD now trading at $87,971. Chart: TradingView

Crypto Price Action Enters The Story

While the scams became more sophisticated, the market evolved too. Bitcoin was trading in the range of $88,000 to $90,000 in late January 2026 as investors considered macro news and policy developments.

This market context is important: as prices increase, the urgency and authenticity of crypto scams may seem more plausible, and the risks for both victims and law enforcement may be higher.

Scam Proceeds Compared To Illicit Flows Overall

Illicit inflows to crypto assets reached a record high of $158 billion, a substantial increase due to improved monitoring that brought more illicit activity to light.

Meanwhile, scam-related wallets saw a slight decrease in proceeds to around $35 billion in 2025, from $38 billion in the previous year.

However, the total volume of criminal activity increased substantially, even as the portion attributed to scams increased marginally.

It appears that scam-detecting technology is improving, but scams are evolving rapidly. The increasing use of AI-based tools makes generic advice less helpful, as the scams now sound more authentic.

Featured image from Unsplash, chart from TradingView

Related Questions

QWhat was the total value of illicit crypto flows in 2025 according to TRM Labs?

AIllicit crypto flows reached a record high of $158 billion in 2025.

QHow did the use of large language models in scams change in 2025?

AThe use of large language models in scams jumped fivefold in 2025.

QWhat was the approximate trading range of Bitcoin in late January 2026?

ABitcoin was trading in the range of $88,000 to $90,000 in late January 2026.

QHow much did scam-related wallet proceeds amount to in 2025?

AScam-related wallets saw proceeds of around $35 billion in 2025, down from $38 billion the previous year.

QWhat are some specific AI tools mentioned that are being used by scammers to build trust?

AScammers are using AI images, voice cloning, and deepfakes to create fake people who look and sound legitimate to build trust.

Related Reads

Why Pricing Social Interactions is Doomed to Fail?

Titled "Why Putting a Price on Social Interaction Is Doomed to Fail," this article critiques attempts to monetize social networks directly through SocialFi models, arguing their inevitable failure stems from a fundamental misunderstanding of media dynamics. Using Marshall McLuhan's theory of "hot" and "cold" media, the author posits that social networks are inherently "cold" media. Their value isn't contained in individual posts but is co-created through user participation, interpretation, and fragmented, ongoing interaction (e.g., replies, shares). This ambiguity and need for user involvement are core to their function. The article asserts that SocialFi projects like Friend.tech failed because introducing real-time, tradable financial pricing (a definitive "hot" signal) into this "cold" environment doesn't add a layer—it replaces the medium's essence. The unambiguous price signal overshadows and nullifies the nuanced, participatory social signal. Users become traders, not participants, and when speculative profits vanish, the underlying social ecosystem—never genuinely cultivated—collapses entirely. This principle extends beyond crypto. The author argues platforms like Twitter have gradually "heated up" through metrics (likes, retweets counts, algorithmically defined value), shifting users from participants to performers and eroding organic engagement. The solution isn't to abandon capital but to manage its entry point. Successful models like Substack, Patreon, or Bandcamp allow capital to "condense" at specific, isolated nodes (e.g., subscriptions, one-time payments) without permeating and "heating" every social interaction. They preserve the core "cold," participatory medium while enabling monetization at designated boundaries. The NFT boom and bust serves as a stark parallel: the ancient "cold" medium of collecting (valued for story, community, gradual accumulation) was rapidly destroyed by platforms that introduced real-time floor prices, rarity scores, and trading dashboards, transforming collectors into speculators and vaporizing cultural value when prices fell. The core lesson: "Liquidity equals heat." Injecting high liquidity and definitive pricing into a "cold" participatory medium doesn't optimize it; it fundamentally alters and destroys its value-creating mechanism. The future lies not in pricing every social gesture but in finding precise, non-invasive points for capital to condense without overheating the entire ecosystem.

marsbit6m ago

Why Pricing Social Interactions is Doomed to Fail?

marsbit6m ago

Jensen Huang's CMU Speech: In the AI Era, Don't Just Watch, Build

Jensen Huang, CEO of NVIDIA and a first-generation immigrant, delivered the commencement address to Carnegie Mellon University's class of 2026. He shared his personal journey from a humble background to founding NVIDIA, emphasizing resilience, learning from failure, and the responsibility that comes with leadership. Huang framed the present moment as the dawn of the AI revolution, a shift he believes is more profound than previous computing waves. He described AI as fundamentally resetting computing—moving from human-written software to machines that understand, reason, and use tools. This will create a new industry for generating intelligence and transform every sector. While acknowledging AI's potential to automate tasks and displace some jobs, Huang distinguished between the *tasks* of a job and its core *purpose*. He argued AI will augment human capability, not replace humans. The real risk, he stated, is not AI itself, but people being left behind by those who effectively use AI. He presented AI as a generational opportunity for massive infrastructure investment—in chip factories, data centers, energy grids, and advanced manufacturing—that could re-industrialize nations like the U.S. and bridge the digital divide by making computing and intelligent tools accessible to all. Huang called for a balanced approach: advancing AI safely and responsibly, establishing prudent policies, ensuring broad access, and encouraging universal participation. He urged the graduates not to fear the future but to engage with optimism and ambition, reminding them of CMU's motto, "My heart is in the work." His core message was clear: this is their moment to actively build and shape the AI-powered future, not merely observe it.

marsbit1h ago

Jensen Huang's CMU Speech: In the AI Era, Don't Just Watch, Build

marsbit1h ago

The Era Has Arrived Where Human Writers Must Prove They Are Not Machines

The article describes an era where AI-generated content is flooding the market, forcing human authors to prove they are not machines. It begins with the example of dozens of AI-written, error-ridden biographies of Henry Kissinger appearing on Amazon within hours of his death, a pattern repeated for other deceased celebrities and even living experts who find fraudulent books under their names. This spam content has exploded, with monthly new book releases on platforms like Amazon reaching 300,000 by late 2025. The issue spans genres, from suspiciously high proportions of AI-written teen romance and self-help books to dangerous, AI-generated foraging guides containing lethal advice. The platforms' automated review systems, designed to catch plagiarism and banned words, are ill-equipped to detect AI-generated text that avoids these pitfalls while being nonsensical or fraudulent. The problem has infiltrated traditional publishing. A major publisher, Hachette, had to recall a bestselling horror novel after AI detection tools suggested 78% of its content was machine-generated. An acclaimed European philosophy book was later revealed to be entirely written by AI under a fake author persona. In response, authors are fighting back. At the 2026 London Book Fair, 10,000 writers published a blank book titled "Don't Steal This Book" containing only their signatures—using emptiness as a protest weapon in an age of AI overproduction. Initiatives like the "Human Author Certification" program have emerged, ironically placing the burden on humans to prove their work is not machine-made. The article warns of a vicious cycle: AI-generated low-quality books pollute the data used to train future AI models, leading to "model collapse" and an ever-worsening flood of digital waste, eroding trust in publishing and devaluing human creativity.

marsbit1h ago

The Era Has Arrived Where Human Writers Must Prove They Are Not Machines

marsbit1h ago

Trading

Spot
Futures
活动图片