AI use in crypto crime jumps 40% in one year, TRM Labs report shows
AI tools fuel rise in crypto scams and hacks
A new report from TRM Labs shows that criminals are using artificial intelligence (AI) in crypto-related crimes 40% more than they did a year ago. The increase is most noticeable in scams, where AI tools like deepfake videos and chatbots are now common.
The report, called the 2026 AI-in-Crime Adoption Index, gives an overall score of 54 out of 100 for AI use in crypto crime. This is up from about 28 in 2024. Scams are the most advanced, labeled as "mature," while hacking and ransomware are still growing but already show heavy AI use.
Ari Redbord, Global Head of Policy and Government Affairs at TRM Labs, said AI has not created new crimes but has made old ones easier and faster. "What used to take a team of operators now takes one person with a subscription," he explained.
Key findings from the report
- AI adoption in crypto crime rose 40% year-on-year.
- Scams involving AI, like deepfakes, have increased up to 13 times since 2022.
- Losses from deepfake scams in 2026 so far are 263% higher than the full year of 2025.
- Crypto hacks reached a record 201 in the first half of 2026, more than double the 2025 total.
- North Korea-linked hackers accounted for 61% of losses in the first half of 2026, totaling $600 million.
How criminals use AI in crypto crimes
The report explains that scammers use AI to create realistic fake identities, known as deepfakes, and chatbots to trick victims. These tools help criminals scale their operations quickly and target more people than before.
Hackers are also using AI to find weaknesses in crypto systems. For example, North Korean cyber groups use AI for social engineering, deepfake job applications, and discovering vulnerabilities in software. At the Wyoming Blockchain Symposium 2026, Global Settlement Network CEO Ryan Kirkley warned that AI agents could soon break into Wi-Fi networks, passwords, and crypto wallets at a scale never seen before.
In June 2026, a security engineer used AI to find a critical flaw in Zcash’s Orchard transaction pool. This flaw could have allowed hackers to create unlimited fake tokens within the pool.
Ransomware and darknet markets
Ransomware attacks, where criminals lock a victim’s data and demand payment, are also using AI. TRM Labs noted that most ransomware operations now use AI for phishing and gaining initial access to systems. No-code ransomware kits, which require little technical skill, are sold online for $400 to $1,200.
Last month, researchers discovered JadePuffer, the first fully automated ransomware attack. An AI agent handled every step, from finding targets to encrypting data, without human involvement. Redbord called this a "civilization-level threat" because of its potential to disrupt hospitals and critical infrastructure.
AI use in narcotics trafficking and darknet markets remains limited, mostly for marketing purposes.
What is confirmed
- TRM Labs reports a 40% increase in AI adoption for crypto crimes over the past year.
- Scams involving AI, such as deepfakes, have risen significantly since 2022.
- Losses from deepfake scams in 2026 are already 263% higher than the full year of 2025.
- Crypto hacks reached a record 201 in the first half of 2026, with North Korea-linked hackers responsible for 61% of losses.
- AI is being used in ransomware attacks, including the first fully automated attack, JadePuffer.
What is still unclear
- The report does not specify how many individual scams or hacks involved AI, only the overall increase in adoption.
- It is unclear how effective law enforcement has been in stopping AI-driven crypto crimes.
- The long-term impact of AI on crypto crime trends remains uncertain.
Why this matters for crypto users
The rise of AI in crypto crime means that scams and hacks are becoming more sophisticated and harder to detect. Users need to be extra cautious, especially with unsolicited messages, job offers, or investment opportunities that seem too good to be true. The report also highlights the need for stronger security measures in crypto systems to protect against AI-driven attacks.
