How AI is Reshaping Cybersecurity

Artificial Intelligence (AI) enables cybersecurity companies to discover and address security risks more quickly than ever. However, it is essential to understand the many risks that AI poses to the cybersecurity industry. Like many other forms of technology, cybercriminals can utilize AI to reveal flaws, uncover vulnerabilities, and perform social engineering attacks. 

97% of Business Owners and 64% of business organizations believe that AI tools will help their business and improve productivity. With AI tools poised to become influential business assets, companies, and individuals need to keep up with these new risks and understand how they can use the same tech to protect themselves. Let’s look at how AI is used, its benefits to professionals, and the newfound risks of criminals using it.

What is AI?

While modern AI doesn’t have flashing blue lights or robotic voices, what it can do is much more impressive than what most people imagine. The expansion of AI into business and our everyday lives feels revolutionary but it is the result of decades’ worth of technological advancement and evolution. After all, computers have been wiping the floor with us in tasks like chess for over a quarter of a century. 

In a broad sense, AI refers to any program that accomplishes a reasonably complicated task and is agnostic about how this task is achieved. In that sense, some complex, deterministic, fixed algorithms would be considered AI. These days, when we talk about AI, we’re typically talking about some form of Machine Learning program, i.e., a program that can incorporate feedback on how well it completes a task and change how it performs the task to get better results. Most machine learning tools use neural network models to achieve this. Unlike fixed algorithms, the random nature of neural network training means they can produce slightly different results to the same request based on how they have evolved. 

Benefits of AI in Cybersecurity

As we delve into the transformative impact of artificial intelligence on cybersecurity, it’s crucial to explore its advantages for security professionals first. From automating mundane tasks to enhancing threat detection, AI is a powerful ally in fortifying an organization’s security measures.

Automation

One of the most compelling advantages of integrating AI into cybersecurity is the automation of repetitive tasks. Security professionals often get bogged down with routine activities like patch management and rules orchestration. AI can significantly lighten this load. For instance, AI-driven tools can automatically identify and apply critical patches in real-time, freeing human resources for more complex problem-solving. Similarly, AI can automate the orchestration of security policies and rules, ensuring the network is consistently secure without requiring manual oversight.

Filtering and Responding

Another area where AI shines is filtering and prioritizing alerts for critical threats. Traditional security systems often generate an unmanageable number of alerts, including many false positives. This can lead to “alert fatigue,” where important warnings might be overlooked and remain trapped in the haystack of low-priority alerts. SIEM (Security Information and Event Managment) tools have long existed to create automated rules to reduce the number of rules that need to be manually resolved. These vendors are increasingly leveraging AI functionality to provide a more flexible automation tool that can “learn on the job” by creating new automation rules based on analyst feedback.

Software Security Review

DevSecOps has long been a thorny and challenging domain of the cybersecurity field.  It is critical that new software doesn’t introduce vulnerabilities to environments, but the code review process to prevent this is often laborious and time-consuming. Software scanning tools that leverage AI promise to rapidly and accurately review large amounts of code for patterns and structures that indicate secure or insecure code, highlighting areas for further review and automatically suggesting or implementing edits.  

By automating mundane tasks and enhancing the quality of threat detection, AI allows security professionals to focus on strategic activities that require human intuition and expertise. This makes the security team more efficient and fortifies the organization’s overall security posture.

How Criminals Use AI         

AI has real, meaningful potential benefits for legitimate work, and security-minded organizations need to consider how it fits into their workflow and processes.  One thing can be guaranteed.  Threat actors are and will continue to be innovative with applications of AI in their attacks, so unless we intend to find ourselves technically outmatched, we need to apply it, too.  Let’s explore how cybercriminals are weaponizing AI to compromise security measures and see what new attack surfaces AI may generate.

Scaling Social Engineering Attacks

While AI offers numerous benefits to cybersecurity, it’s a double-edged sword that can empower cybercriminals. One of the most concerning uses is in scaling social engineering attacks. Large language models like ChatGPT have beaten the “Turing Test” (i.e., regular people are not reliably able to distinguish them from human communication). This has the potential for threat actors to combine spear phishing attacks’ targeted, personalized phishing emails with the scale of more old-fashioned spam emails. Most successful cyberattacks originate from a single account breach or phishing email that went undetected. These AI-driven attacks can simultaneously target many individuals or organizations, increasing the likelihood of a successful breach.

Accelerating Malware Development

AI can also accelerate malware development by generating code variations that evade traditional security measures. Threat Intelligence teams have already observed threat actors creating multiple, yet subtly different, versions of malicious code. AI enables cybercriminals to produce a dramatically more extensive variety of code more quickly than before, reducing the cost of failure and allowing them to launch more attacks faster.

Data Poisoning

Using complex AI models also produces the potential for a new type of threat. It is often challenging or impossible to determine how a machine learning program solves a prompt or input; the results are very contingent on the training data used.  As AI tools become increasingly essential for business operations, the potential exists for threat actors to target the AI solutions themselves by “poisoning the well” of the training data. By introducing artificial data to the training set, threat actors can cause AI tools to malfunction or produce erroneous and detrimental results. This undermines an organization’s security infrastructure, ability to leverage AI tools, and can lead to significant vulnerabilities.

The potential for AI to be weaponized by threat actors underscores the need for a balanced approach to its adoption in cybersecurity. While AI can be a powerful tool for defense, organizations must remain vigilant to the evolving tactics that cybercriminals employ, often using the same advanced technologies.

Conclusion

The increasing business relevance of AI is both filled with both promise and peril. On the one hand, AI technologies offer cybersecurity teams unprecedented capabilities to automate tasks, enhance threat detection, and streamline security operations. On the other hand, the same technology is being co-opted by cybercriminals to launch sophisticated attacks and compromise security measures. Organizations must adopt a balanced, informed approach as we navigate this new frontier. Leveraging AI’s strengths while staying vigilant to its potential misuse is not just a best practice—it’s necessary to maintain a robust cybersecurity posture in today’s digital age.