AI-enabled crime

Table of contents

What is AI-enabled crime?

As artificial intelligence (AI) continues to reshape industries, criminals are also leveraging its power to enhance their illicit activities. AI-enabled crime refers to the use of machine learning, automation, and artificial intelligence techniques to facilitate, scale, or conceal illegal operations.

Within the cryptocurrency ecosystem specifically, criminals are increasingly using AI to eliminate human bottlenecks. This not only enables malign actors to carry out hacks, fraud, ransomware, and other known illicit activities at an unprecedented scale — but also has created a market for new crime typologies with the potential for alarming impact, including deepfakes that are being leveraged for extortion, AI agents that rapidly spread misinformation, and smart contract exploitation.

This new frontier of AI-enabled crime presents new challenges for law enforcement, regulators, and crypto businesses.

‍

How is AI transforming illicit crypto activity? What are some emerging crypto crime typologies?

AI crime, particularly in the cryptocurrency space, has evolved beyond simple automation. Criminals now utilize AI to exploit vulnerabilities in blockchain technology and digital financial systems. Here are some of the most prominent ways AI is being deployed:

Automated money laundering and mixing services

AI-powered algorithms are enhancing the effectiveness of crypto laundering techniques. Criminals use AI-driven mixers (also known as tumblers) to obscure transaction trails by analyzing blockchain patterns and dynamically adjusting transaction flows to evade detection. These AI-enabled laundering strategies make it increasingly difficult to track illicit funds.

Deepfake scams and identity fraud

Deepfake technology — which uses AI to generate highly realistic fake videos, audio, and images — is increasingly being leveraged for social engineering attacks. Criminals use deepfake voice cloning and synthetic media to bypass Know Your Customer (KYC) procedures, impersonate executives in phishing attacks, or manipulate biometric authentication systems.

AI-aided pig butchering scams

Scammers can leverage AI to scrape data from social media and dating platforms to identify vulnerable targets (e.g. lonely individuals, recent retirees, or people interested in finance) for pig butchering scams. AI chatbots can also be fine-tuned and programmed for romance and investment-related conversations — enabling them to convincingly engage with victims across text, messaging apps, and voice calls. These bots can sustain long-term, emotionally persuasive conversations without tiring or making mistakes, making the scam more scalable.

AI-generated phishing attacks

Phishing scams have become more sophisticated with AI. Machine learning algorithms can now analyze online behavior and personalize fraudulent emails or messages, increasing the likelihood of victims falling prey to credential theft. AI-enabled phishing tools can also generate convincing fake customer support chats, automating large-scale scams that target crypto wallet users and exchanges. And because AI agents have eliminated the need for human manpower to make contact with victims and carry out these kinds of schemes, these attacks can now happen more quickly than ever before — and at massive scale.

Smart contract exploitation and AI-driven hacking

AI is accelerating the discovery and exploitation of vulnerabilities in smart contracts and decentralized finance (DeFi) protocols. Automated tools scan blockchain networks for flaws and execute exploits faster than human hackers can. This has led to AI-powered attacks on DeFi platforms, resulting in substantial financial losses.

AI bots for market manipulation

AI-driven trading bots can manipulate crypto markets by engaging in practices such as wash trading, spoofing, and front-running. These bots analyze market trends in real time, making thousands of trades per second to create false market signals, deceive investors, and profit from artificial price movements.

What can law enforcement, national security / defense agencies, crypto businesses, and regulators do to fight AI-enabled crime?

As AI tools become more sophisticated, so do AI-enabled crimes. Global law enforcement and national security / defense agencies, crypto businesses, regulators, and policymakers need to stay current on developments in the AI space and learn to leverage AI-enabled tools to counter these growing threats — in other words, fighting AI with AI.

Here are some key opportunities and considerations for each group.

Law enforcement

Enhanced investigative tools: Law enforcement agencies must integrate AI-powered blockchain intelligence tools to counter AI-enabled financial crime. This includes machine learning-driven transaction analysis and behavioral anomaly detection.
Collaboration with private sector: Cooperation with blockchain analytics firms, crypto exchanges, and AI security researchers is crucial for tracking and mitigating AI-facilitated threats.
Adaptation to AI-powered cybercrime: Law enforcement must stay ahead of adversarial AI by continuously updating forensic methodologies and training personnel in AI crime detection.

National security and defense

Defensive AI for threat detection: National security agencies must integrate AI-powered analytics to identify suspicious blockchain activity, track illicit networks, and disrupt AI-enhanced cybercriminal operations — including misinformation campaigns that can destabilize financial markets, manipulate public perception, and undermine confidence in digital assets.
International cooperation: Given the borderless nature of AI-driven financial crime, defense agencies must collaborate with global partners, intelligence-sharing networks, and blockchain intelligence firms to mitigate AI-powered threats.
Counter-terrorism financing (CTF): AI-driven laundering techniques can be used to obscure the financial activities of terrorist organizations, requiring advanced tracking tools for fund movement analysis. National security agencies must leverage advanced blockchain intelligence tools to detect and interdict these threats.

Crypto businesses

AI-driven compliance solutions: Exchanges and financial institutions should implement AI-enhanced anti-money laundering (AML) monitoring systems to detect suspicious transactions in real time.
Advanced fraud prevention: Businesses need to employ AI-powered identity verification solutions to combat synthetic identity fraud and deepfake scams, and learn to recognize the signs of AI-enabled fraud.
Threat intelligence integration: Deploying blockchain intelligence solutions that leverage AI for risk scoring and anomaly detection can help mitigate AI-enabled illicit finance risks.

Regulators

Developing AI-centric regulations: Regulatory frameworks must evolve to address AI-driven financial crime, ensuring compliance measures are effective against AI-powered laundering and fraud schemes.
Promoting AI transparency and ethics: Establishing guidelines for responsible AI use in financial institutions and crypto platforms can help reduce the risk of AI exploitation by criminals.
Encouraging information sharing: Public-private partnerships and cross-border intelligence sharing can enhance global efforts to combat AI-enabled crime in the cryptocurrency space.

‍

What is the role of blockchain intelligence in mitigating AI-enabled crime?

Blockchain intelligence plays a critical role in detecting, preventing, and mitigating AI-enabled crime by leveraging advanced analytics and machine learning to counteract illicit financial activities. Key functions include:

Real-time monitoring: AI-powered blockchain intelligence tools analyze transactions in real time, identifying suspicious patterns and flagging potential illicit activity before it escalates.
Behavioral anomaly detection: Machine learning models detect deviations from normal transaction behaviors, helping to uncover money laundering schemes and AI-driven fraud. TRM Labs’ Signatures® leverages machine learning to identify distinct transaction patterns and behavioral anomalies on the blockchain — detecting unique characteristics associated with illicit activity, such as fraud, money laundering, or sanctions evasion.
Enhanced risk scoring: Blockchain intelligence platforms like TRM Labs use AI to assign risk scores to wallets, exchanges, and counterparties — enabling proactive mitigation or investigation of potential threats.
Attribution and investigative support: By analyzing blockchain data, intelligence tools and teams help trace illicit funds, link addresses to known criminal entities, and provide actionable insights for law enforcement and regulators.

To learn more about what TRM is doing to help agencies and organizations counter AI-enabled crime, check out this report.