Original title: Cybercrime 3.0: the rise of artificial intelligence crime
George Zlati · September 2026
Criminals are now using artificial intelligence, or AI, which creates a huge shift in cybercrime. Researchers wanted to map out this new wave of digital illegal activity. They named it Cybercrime 3.0, coming after earlier eras that focused on standardizing criminal laws and policing blockchain offenses. To show how this works, the authors sorted AI-related crimes into three distinct groups. First, criminals can use AI as their underlying infrastructure to run operations. Second, they can wield AI as a direct tool to commit digital or traditional crimes. Third, bad actors can make AI itself the target of adversarial attacks, aiming to manipulate or break the system. Finally, the authors found that these evolving AI methods create possible tensions with substantive criminal law.
Imagine a bank has three kinds of security problems. First, a robber uses a crowbar to break in—that is a tool. Second, the robber breaks the bank's alarm system itself—that is a target. Third, the robber builds a fake bank branch that looks real and funnels all customers to it—that is infrastructure. In this paper, AI plays all three roles in cybercrime: it is the tool criminals use, the target they attack, or the infrastructure they build their whole operation on.
If you use AI tools or rely on systems that do, you are already in the crosshairs. Criminals can weaponize AI to automate scams, break into systems, or attack the AI models themselves. This paper gives law enforcement and lawmakers a way to categorize these new threats so they can write laws that actually work.
The abstract is descriptive only—it does not test or evaluate any specific AI crime or countermeasure. It highlights tensions with existing law but does not propose new legislation or enforcement strategies. The taxonomy is conceptual and may not cover all possible AI crime scenarios.
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Cybercrime 3.0: the rise of artificial intelligence crime — George Zlati — ERA Forum — doi:10.1007/s12027-026-00897-5
Abstract licence: CC BY
Explanation generated by Synthesis from the abstract — it is not the original paper.