Cybersecurity threats in the cryptocurrency industry are no longer limited to smart contract exploits and technical vulnerabilities. Artificial intelligence (AI)-enabled fraud, fake identities, deepfakes and social engineering are emerging as major risks. According to Chainalysis data, crypto scams generated at least $14 billion in on-chain inflows in 2025. However, the entire amount cannot be attributed to AI-driven fraud.
How Is AI Changing the Way Crypto Scams Operate?
Criminals are increasingly using AI to create fake identities, impersonate investors and conduct convincing interactions with potential victims. Experts say AI is no longer a separate category of cybercrime technology but is becoming embedded across multiple stages of fraudulent operations. Deepfakes, face-swapping software and large language models can allow criminals to create and operate convincing fake identities at scale.
Chainalysis data indicates that scams with on-chain links to AI vendors involved an average of around $3.2 million per operation, compared with approximately $719,000 for scams without such links. The figures show a correlation between AI-related activity and higher-value scams, but do not establish that the use of AI itself caused the larger losses.
Why Are People Becoming a Bigger Target Than Smart Contract Code?
Renowned cyber crime expert and former IPS officer Prof. Triveni Singh said the most concerning aspect of AI-enabled cybercrime is that criminals are using the technology not merely to generate messages or content, but to establish trust and influence victims’ decision-making. He said that when a victim personally authorises a crypto transfer after being deceived, it can be difficult for the underlying system to determine that the transaction was made under fraudulent influence.
The nature of conventional crypto attacks is also changing. According to Binance Research, around two-thirds of the approximately $621 million lost in DeFi exploits in April 2026 resulted from access-control failures. This means attackers do not necessarily need to break smart contract code. Instead, they can target people, wallets, credentials or governance systems that have authority over a protocol.
Binance Chief Security Officer Jimmy Su has said that as smart contract security improves, attackers are increasingly shifting their attention towards people, credentials and governance systems. This has expanded the scope of crypto security beyond protecting code to securing the individuals, infrastructure and control mechanisms responsible for operating it.
Why Is Tracing Crypto Fraud Still Difficult Despite Blockchain Transparency?
Blockchain transparency remains an important advantage for investigators because transactions can be traced on-chain. However, identifying the real person or organisation behind a wallet remains challenging. Mixing services and other techniques can complicate efforts to determine the ultimate source and beneficiary of funds. Experts point out that while blockchain records can reveal the movement of money, those records alone do not automatically establish the identity of the person responsible for a crime.
Could AI Agents Create a New Security Problem for Crypto Transactions?
The growing use of AI agents is creating another potential security challenge. AI agents could increasingly conduct purchases, make payments and execute other financial transactions on behalf of users. In such an environment, counterparties may struggle to verify whether a real and accountable human is behind a transaction.
Companies are therefore exploring systems that link AI agents to verified human owners. However, balancing identity verification with privacy and accountability remains a significant challenge. Experts say it will not be enough to establish that a transaction was technically valid on a blockchain. Systems will also need to determine whether the person or agent initiating the transaction was properly authorised and accountable.
How Is AI Being Used to Fight Crypto Fraud?
AI is also being deployed on the defensive side of the cryptocurrency ecosystem. Banks and crypto businesses are using automated systems to identify suspicious wallets, known scam destinations and unusual transaction patterns. Such tools can potentially help detect risks before fraudulent funds are moved further through the financial network.
The crypto industry is now facing a dual challenge. Criminals are using AI to make fraudulent schemes more convincing and scalable, while security teams are increasingly relying on AI to detect and disrupt those schemes. As this technological arms race develops, the weakest point may no longer be the code itself, but the people, identities and authorisation processes surrounding financial transactions.
About the author — Ayesha Aayat writes on cybercrime, digital safety, and emerging online threats. Her work focuses on public awareness, legal clarity, and technology-driven risks.
