Artificial Intelligence is giving cybersecurity teams new tools to detect threats and automate routine work, but it’s also allowing cybercriminals to launch more convincing attacks faster and on a larger scale. While AI models developed by companies such as Anthropic, OpenAI, and Google can help hackers identify vulnerabilities in computer systems faster than before, security teams are using similar models to detect and fix those same weaknesses.
Anthropic reported last November that Chinese hackers used its AI model for a highly sophisticated espionage campaign. According to the company, attackers used the model to gather intelligence and support vulnerability research, illustrating how AI can accelerate multiple stages of sophisticated cyber operations.
The biggest shift is not that AI allows attackers to do something entirely new, but that it dramatically reduces the time and expertise required. Tasks that once demanded specialized knowledge, such as writing convincing phishing emails in multiple languages and analyzing source code for vulnerabilities, can now be completed in minutes.
A recent report from AI-native threat intelligence firm Cyble recorded 69 ransomware attacks against the US banking, finance, and insurance sector in the first half of 2026. These attacks were carried out by 20 separate groups, fifteen of which managed just one attack each, a fragmentation that shows a low barrier to entry and an evolving system of threats.
Domininkas Virbickas, product director at VPN provider NordVPN, said AI was not necessarily creating new attack strategies by enhancing those that already existed. He noted that the most common AI-assisted scams involve fake online shops and fraudulent websites, where victims pay for products that never arrive.
AI writes beautiful texts in various languages, and that raises the bar. Virbickas noted that AI boosts current scam methods because they require time, effort, hosting a website, contacting people, sending emails or messages. It makes the activities cheaper and faster.
Cybersecurity companies, VPN providers, and hosting services also use the technology to detect phishing websites and identify suspicious activity. Virbickas said large language models are used as tools to review code, but are not allowed to operate without human oversight.
Mantas Lukauskas, AI tech lead at Hostinger, a Lithuanian web-hosting company, said developers need to understand the risks that AI introduces and design systems that detect them. They worked on a phishing detector, and one of the features that they developed was discovering whether a domain name was real or phishing.
Until recently, analyzing website imagery required specialized computer-vision models. Now, you can just send screenshots to any large language model, and it will do the work.
Mantas Lukauskas said developers need to understand the risks that AI introduces and design systems that detect them.
Thinking critically is one of the most important things at a time when AI has become so widely used for scams and malicious activities on the web, according to Lukauskas. Even if an email or a logo looks good, you’re not safe.
As AI continues to develop, Middle East tensions and other global factors influence the creditor setting, and users can no longer rely on obvious warning signs such as poor grammar or awkward translations. Instead, they need to verify the source of emails, websites, and requests for sensitive information, even when they might appear legitimate.
Building trust is essential for cybersecurity companies. Virbickas said it involves independent audits, transparency, and continuous testing. One approach used by NordVPN is commissioning no-log reports, which include the types of information the company does not collect, store, or record any user activities.
The company also commissions assessments of the security of its code. Such external reviews are intended to give users evidence that a company’s security and privacy claims have been independently examined, which is something that, in the context of this rapidly changing environment, becomes increasingly important for users to consider when choosing a cybersecurity provider, much like considering the impact of AI on the industry.
