AI and Ransomware Prevention: How Smart Tech can Outsmart Cybercriminals

The use of artificial intelligence (AI) is opening up a new front in the ongoing fight against ransomware. Both cybercriminals and security professionals have opportunities to use this technology to improve their performance, and with cybercriminals quick to embrace the possibilities this technology offers, security teams must do the same.

​The escalating arms race between cybercriminals and security teams has seen both sides leveraging AI. In 2024, researchers noted AI was used to lower the barriers to entry for hackers, create more personalized tactics, exploit vulnerabilities and demand higher ransoms. Ransomware attacks reached record highs last year and it’s highly probable that AI will exacerbate this trend in 2025.

Attackers employ these tools to automate their ransomware strategies and develop more sophisticated attacks, enabling rapid identification of vulnerabilities and deployment of highly personalized phishing campaigns. In response, cybersecurity professionals use the technology to enhance their threat detection and automate their responses. 

The result is a battle played out without any human intervention. Imagine AI ransomware capable of evolving and adjusting its code to evade detection in real-time, facing off against AI defenses that can anticipate these moves and take the necessary steps to tackle them before security pros are even aware of it.

That’s the future security pros face in the AI-driven era. However, the question remains: can AI truly prevent ransomware?

The first step in combating AI-driven ransomware is to understand how hackers are using the technology and the techniques used to bypass traditional security methods. Among the more common applications for AI in ransomware attacks are:

• Polymorphic AI ransomware: Traditional ransomware detection methods look for known signatures or patterns. However, AI-powered ransomware can continuously modify its code to evade these efforts. By dynamically reshaping itself, AI-enhanced ransomware can remain undetected by antimalware programs, increasing the time before security systems can recognize and respond to the threat. In turn, this allows for more data to be exfiltrated or greater damage to be done within systems.
• Social engineering: AI is increasingly being used to trick employees into handing over data or passwords. According to VIPRE, 40 percent of phishing emails targeting businesses are now AI-generated, while the Harvard Business Review notes 60 percent of recipients fall victim to these highly-convincing tactics. These can even be used to create deepfake audio or video to impersonate executives or other contacts.
• Attack automation: AI enables hackers to automate ransomware campaigns, allowing for rapid deployment at a very large scale. Automation tools can scan for vulnerabilities, execute attacks and adapt in real time based on the defenses the target has in place. This makes mass ransomware campaigns more efficient as hackers are able to attack multiple organizations simultaneously, without the need to create individual campaigns.

These tactics are also increasingly available as part of Ransomware-as-a-Service offerings. These platforms enable almost anyone to launch a ransomware attack by buying prebuilt tools, with a percentage of the profits going back to the ransomware authors. As AI reduces the need for human involvement, it makes this model more effective by ensuring even low-skill attackers can execute highly sophisticated, difficult-to-detect ransomware campaigns.

While AI-driven tools can help with ransomware detection by looking for unusual behavior and blocking data exfiltration attempts in real-time, they can also be used as a proactive defense mechanism to prevent attacks before they happen. Here are some of the most powerful AI ransomware mitigation and prevention tactics that are set to make their way into mainstream use in the coming years:

• AI-driven deception technology: This involves creating false digital assets, such as decoy files, fake credentials and deceptive network environments. Sometimes known as honeypots, these act as bait to divert ransomware away from genuine systems. While the concept is not new, AI can make these traps much more realistic, fooling even advanced ransomware tools. As well as keeping sensitive data safe, this allows security teams to gather intelligence on attack methods and improve their defenses accordingly by learning more about ransomware behavior.
• Self-healing systems: AI can automate restoration and recovery processes to help businesses recover from ransomware attacks in seconds. Self-healing AI continuously monitors endpoints and network activity, for example to detect unauthorized data modification or encryption attempts. It can then revert affected files to their original state instantly, reducing downtime and preventing data loss.
• Enhancing zero-trust models: Zero-trust approaches ensure access to confidential data is restricted to only individuals who need the data and can verify their identity. AI enables adaptive ransomware protection by evaluating user behavior in real-time. If unusual behavior such as multiple access requests are spotted, it can revoke permissions to restrict access or isolate infected devices from the rest of the network. This plays a vital role in preventing ransomware from spreading laterally within a network, as AI-based authentication systems detect and isolate threats before they can cause widespread damage.

As well as using AI and machine learning for ransomware defense, another potential application for this technology is in actually negotiating payments with hackers. While law enforcement agencies and security experts advise against paying ransoms, as it encourages criminals and makes firms a target for future attacks, some firms may feel they have no choice but to pay up in order to restore services and minimize disruption.

If this is the case, AI can offer a range of benefits, whether by reducing payments or buying time while companies work on recovering encrypted files.

For example, the use of tools such as natural language processing can analyze the demands received and the hackers’ psychology to assess how serious they are and whether criminals are likely to lower their demands. It can then take action such as using bots to negotiate a better deal for the firm, or even detect whether the criminals are bluffing.

This is still an emerging and controversial application for AI, but with many AI-powered ransomware attacks using bots to automate their own demands, it could help manage processes and give firms vital information about an attack.

While AI can offer businesses another powerful addition to their cybersecurity toolbox, there will still be a need for human oversight of the systems. This will be important in guiding the strategies of AI, ensuring the actions it takes are correct and managing how it responds to emerging threats.

For example, in the coming years, anticipated advancements that will likely have an impact on how security teams approach ransomware prevention include:

• Quantum AI security: The use of quantum technology has been flagged as a major threat to traditional encryption, allowing hackers to crack even the toughest defenses. But AI-powered technology could also be used to create unbreakable security solutions.
• Improved ethical hacking: ‘White hat’ ethical hacking and penetration testing is a great way to spot security vulnerabilities, but adding AI to this process helps identify and fix any flaws quickly, using the same techniques ransomware groups would use to find and exploit them.
• Automated AI playbooks: The ability to build up a database of what to do in the event of an attack – with detailed, attack-specific responses that adapt to every scenario – will ensure businesses can keep up with whatever new techniques hackers develop.

Ultimately, AI-powered ransomware is not something any business can afford to ignore. Hackers and the tools they use are getting smarter all the time – but so are the defenses. Incorporating next-generation ransomware prevention that includes AI early will therefore be critical in spotting and responding to attacks such as ransomware and data exfiltration before they have a chance to do damage.

However, it must be remembered that the technology is not foolproof. Continuous learning that ensures security pros are up-to-date with the latest threats and understand what their technology is and is not capable of will be critical in keeping up with the next generation of ransomware.