Generative AI and Cybersecurity: How Does It Work?

The possibilities for generative AI and cybersecurity measures to better protect critical data appear limitless. Generative AI has the ability to learn from existing information and patterns that can help cybersecurity professionals close gaps and cure vulnerabilities. Although AI has become trendy due to clever and entertaining applications such as ChatGPT, the technology has been hovering around for more than a half-century. During the last decade, it has begun to reach its potential and generative AI cybersecurity appears to be the future.

What is Generative AI?

Generative AI has its roots in early chatbots during the 1960s. Underused for decades, it was re-introduced through generative adversarial networks, called GANs, in 2014. Over the last 10 years, it has risen to prominence as an effective machine learning tool. Generative AI can use existing images, audio and text to create likenesses in seconds. The technology is so powerful it has been misused to make harmful deep fakes.

Cybersecurity experts have come to recognize that AI can be used in an ethical fashion. With a lightning-fast ability to identify patterns and trends, it delivers predictive information. Rather than wait to get hit by a ransomware attack or spend hours combing through alerts in search of realistic threats, generative AI cybersecurity processes help anticipate the movement of hackers. If you’ve seen the feature film “Minority Report,” starring Tom Cruise, that’s essentially what generative AI brings to the table. It can predict future threats by analyzing existing data and focused algorithms.

How Can Generative AI Be Used in Cybersecurity?

It’s important to understand that generative AI cybersecurity is, to some degree, a reaction to what sophisticated hackers are doing. Bad actors immediately saw the potential of using generative AI to commit crimes. A recent report indicates that 75 percent of cybersecurity experts saw a 12-month rise in attacks. Upwards of 85 percent of them attributed the escalation to hackers using generative AI.

Deep fakes have created chaos, and their powerful replication abilities have made them a darling among digital scammers. By the same token, security professionals are using this advanced technology against online thieves. As the adage goes, turnabout is fair play.

Ways Hackers Misuse Generative AI

The global digital chess match between cybercriminals and data protection experts has spilled into the AI and machine learning landscape. These are ways cybercriminals are using generative AI to hoodwink internet users and breach business networks.

• Phishing Schemes: Crafting massive amounts of content that appears to be human driven allows digital con artists to troll out tens of thousands of realistic phishing emails without delay. Because generative AI can rapidly create realistic images, audio and text, it is being used to imitate friends, family members and business colleagues. It accomplishes this by assessing content on social media platforms, emails and other messaging. Along with sending out look-alike prompts, it can also orchestrate phony login pages and platforms. People believe they are logging in to a company network only to hand a legitimate username and password to awaiting criminals.
• Malware Deployment: One of the unfortunate byproducts of a technology that was built for positive use is its ability to craft an aggressive class of malware. In the wrong hands, generative AI can develop malware code with machine learning capabilities. Should a malicious file be dispatched and fail to infiltrate or take control of a network, it can learn from the experience and mutate. This process can repeat until the malware finds a vulnerability and exploits it.
• Identity Deception: Deep fakes, look-alike platforms and abuses of personal information posted online can all be weaponized. Everyday people are sometimes tricked into transmitting sensitive identity information such as birthdates, Social Security numbers, login information and financial records. With these and other personal identity assets in hand, hackers can use generative AI to create driver’s licenses, passports and other sensitive documents. The fakes are virtually indistinguishable from the real thing.

Ways Cybersecurity Professionals are Fighting Back with Generative AI

The notion that cybercriminals will see the error of their ways and use their skills for good is wishful thinking. Mosquitoes bite, snakes slither and hackers are going to use every technological advancement for wrongdoing and thievery. While this class of criminals bangs away on keyboards and thinks up ways to use generative AI for ill-gotten gains, security professionals are using this type of machine learning for good. These are ways cybersecurity professionals are deploying generative AI as a defensive tool.

• Fast Data Analysis: The advanced technology helps security operations process tremendous amounts of data in real time. Generative AI can pull from network traffic, user activity and alerts, among others. It promptly sees patterns that humans might otherwise miss. Recognizing trends and unusual activity gives security teams actionable intel.
• Identifying Vulnerabilities: Hackers are trolling out malware driven by generative AI to seek vulnerabilities and breach business networks. There is no reason ethical security experts cannot do the same. Firms that understand generative AI cybersecurity applications are placing it in their risk assessment toolkit. When employed for penetration testing purposes, generative AI can identify security gaps. It can also be deployed on an ongoing basis to cure vulnerabilities as they emerge. In this fashion, generative AI checkmates hackers before they can launch a cyberattack.
• Automated Efficiency: One of the issues that plagues industry leaders across sectors involves redundancies. Repetition breeds inefficiency and needlessly eating up the time of security professionals creates risk. Generative AI streamlines wide-reaching tasks humans find tedious and energy-sapping. Eliminating what feels like copying and pasting over and over keeps cybersecurity professionals fresh-minded and laser-focused.
• Improved Data Privacy: Cybersecurity professionals can leverage generative AI to employ the old bait-and-switch trick on hackers. Because the technology can mimic authentic images, audio, text and sensitive data, it can also build a better honey pot. A honey pot, or “Honey Bot,” lures online thieves away from valuable and confidential digital assets. Hackers get a whiff of the Honey Bot and pursue it instead of real information. While champing at the bit to steal an ethical deep fake, they give their position away.

The x-factor in many companies’ security postures involves endpoint devices. Employees have a terrible habit of logging into business networks from unvetted handheld devices and laptops with subpar security defenses. Managed IT firms with cybersecurity expertise grow frustrated with this practice. Even when a virtual security operations center (vSOC) is established, vulnerable endpoint devices can create short-term security gaps.

Generative AI cybersecurity measures can quickly identify and react to new and unproven endpoint usage. It can identify the presence of malware quickly and alert vSOC staff members about credible threats in real time. In this fashion, it tamps down the timeline between recognizing and expelling threats.

Risks Associated with Generative AI Cybersecurity Practices

The importance of working with an experienced managed IT firm with cybersecurity expertise cannot be understated. Merging generative AI and cybersecurity efforts cracks the door for data privacy errors that could have the opposite intended result. Generative AI collects wide-reaching data indiscriminately, unless properly programmed.

It can overreach and onboard sensitive personal identity information that could violate mandates such as the Health Insurance Portability and Accountability Act (HIPAA), Gramm-Leach-Bliley Act, Payment Card Industry Data Security Standard or the General Data Protection Regulation that applies to American companies collecting data from EU residents. It can also pull together information from organizations in the military industrial base that could violate the Pentagon’s Cybersecurity Maturity Model Certification (CMMC). Failing to protect military-related data can result in a company losing contracts and incurring hefty penalties. Unless generative AI is strategically rolled out by experts, it can also gather and inadvertently expose intellectual property data.

How to Use Generative AI Effectively

In inexperienced hands, generative AI cybersecurity measures can backfire. That does not mean industry leaders should shy away from this advanced technology and give hackers the upper hand. Working with a firm that has skilled professionals who possess an intimate knowledge of generative AI and cybersecurity can be a risk-free means to combat data breaches and ransomware attacks. These are ways experts use generative AI to benefit your cybersecurity posture.

Cybersecurity Training: Using generative AI within a confined environment, the technology can simulate a wide range of cyberattacks in real time. The process tests the decision-making and reaction times of security professionals. By honing human skills, companies get better-prepared security professionals.

Reporting Recommendations: Using generative AI to assess networks and endpoint devices for gaps and vulnerabilities streamlines the security reporting process. Cybersecurity experts can leverage this tool to acquire information quickly, more frequently and cost-effectively. Generative AI makes cybersecurity reporting and recommendations easier.

Supply Chain Risk Management: The U.S. experienced its highest number of supply chain attacks in 2023 at 2,769. Just two years earlier, this wide-net approach saw only a mere 521 reported incidents. What this means to companies is that supply chain partners could become infected with malware that spreads to your system. Fortunately, generative AI can be outwardly focused to detect supply chain threats.

Generative AI and cybersecurity awareness training can also go hand-in-hand. It can be used as a tool to educate employees about persuasive phishing schemes and how to detect them. When front-line workers realize they can not necessarily trust a text note, email or voice message asking them to provide critical information, they will be more inclined to look before leaping. In the right hands, generative AI proves a transformative force for good. It delivers advanced threat intelligence, helps close gaps and provides predictive information that can stop cyberattacks before they happen.

Red River Offers Generative AI Cybersecurity Solutions

Protecting valuable and confidential data grows increasingly difficult as hackers revise their criminal schemes. The financial losses, downtime, regulatory fines and tarnished reputation accompanying a data breach or ransomware takeover can hamstring an otherwise productive enterprise. If you are interested in learning more about how generative AI can improve your security posture, Red River has answers. Contact us today, and let’s get the process started.