Written by Jithu Joseph, Information Security Analyst and Member of the CSA Bangalore Chapter.

Artificial Intelligence (AI) is revolutionizing cybersecurity, providing tools and techniques that can detect, prevent, and respond to cyber threats with unimaginable speed and precision. While AI empowers security professionals to defend against increasingly sophisticated attacks, it also offers cybercriminals new ways to enhance their malicious activities. This dual role of AI makes it a crucial component in modern cybersecurity—a double-edged sword that can both protect and harm.

In this blog, we will explore how AI is shaping the future of cybersecurity on both ends: empowering defenders and assisting attackers. We will also have a look into a few real-world examples, and see how AI is being used for both defence and offense.

AI’s Role in Enhancing Cybersecurity Defences

1. AI in Vulnerability Assessments and Penetration Testing

AI has transformed the world of vulnerability assessments by automating the process of identifying security weaknesses within systems, networks, or applications. AI enhances the assessments by quickly scanning for vulnerabilities and, most importantly, continuously improving its models based on its historical data. This in turn helps reduce the issues often faced by traditional manual methods, which are time-consuming and quite often miss certain attack vectors, especially in a large-scale organization or environment.

As for pen testing, we can take for example tools like Synack, which integrates with AI algorithms to reduce the manual effort involved. Tools like these automatically create test scenarios and assess system vulnerabilities which helps the security team focus on remediation.

With these AI-enabled tools, organizations can address security gaps faster and much more effectively.

2. Threat Detection and Incident Response

Traditional security systems heavily rely on rule-based models or signature detection, which sometimes struggles to keep up with rapidly evolving cyberattacks. AI offers a more dynamic approach to this by constantly learning and adapting to new attack patterns.

For example, tools like Darktrace use ML algorithms to detect anomalies in the network. Darktrace creates a model of typical behavior and interactions within a network to establish a baseline. When an event or activity occurs which is different from this baseline, it alerts the security team. This enables them to identify and address threats more quickly than traditional methods.

The Dark Side: How Hackers Are Leveraging AI

1. AI-Enhanced Malware

One of the most trending and feared developments in cybercrime is AI-enhanced malware. This new version of malware is often referred to as polymorphic malware, which, unlike traditional malware, can alter its code while maintaining its core functionality.

The “Emotet Botnet” is one of the most dangerous malware in the world and is a variation of polymorphic malware. It disguises itself in a Word document, acting as a door opener for a Trojan, which copies the required data, and finally forwards the information to Ryuk ransomware. The important point to note here is that Emotet’s code changes slightly each time it's used.

2. AI-Driven Social Engineering and Phishing

AI also has found a way into social engineering attacks, especially in generating phishing emails. Hackers use AI to analyze the online behaviour of their targets and based on that, generate personalized emails which mimic the content or style of their trusted sources.

For instance, AI-powered NLP models are used to write phishing emails that closely resemble the communication style of a colleague or business partner. By personalizing the messages in such a convincing way, attackers increase their chances of tricking victims into clicking on malicious links or sharing sensitive information.

DeepLocker is one notable example of AI-driven social engineering. It is a malware that keeps itself hidden until it identifies a specific target based on pre-defined characteristics or factors like facial recognition or geolocation.

3. Automated Reconnaissance and Attack Execution

AI allows cybercriminals to automate many of the steps that are part of the reconnaissance and attack execution process. Tools like Deep Exploit leverage AI to scan for vulnerabilities and launch attacks based on the data that is being collected, with minimal need for human intervention. Automation processes like these drastically reduce the manual effort and time needed to execute a successful breach.

Moreover, AI-driven reconnaissance tools can gather detailed information about potential targets, including network configurations, software versions, and employee behaviours. This data is used to refine attack strategies, making them more effective and difficult to detect.

Real-World Examples of AI-Driven Attacks

AI-powered attacks are no longer a myth – they are happening in the real world. A few notable examples include:

• DeepPhish – This is a tool that automates the process of creating a “Spear-Phishing” email. By analyzing the data of a target through their social media accounts and other communications, DeepPhish is able to generate highly accurate phishing emails that are personalized based on the data collected.
• TrickBot – Originally a banking Trojan, TrickBot later evolved to use AI-based models to enhance its evasion techniques. The malware collects data on its victims and uses machine learning to better understand which types of attacks will be most successful, adapting dynamically to the environment and spreading laterally within networks to evade detection.
• Satori Botnet - A variant of the infamous Mirai botnet, Satori is notable for its use of AI and machine learning algorithms to identify vulnerabilities in IoT devices. It automates the process of finding weak points in connected devices, which allows it to infect a wide range of targets at a much faster pace compared to traditional methods.

Conclusion: Embracing AI as a Double-Edged Sword in Cybersecurity

Throughout the blog, we’ve explored the duality of AI in the world of cybersecurity – offering both immense opportunities and significant risks. From its ability to enhance threat detection and other defense mechanisms, to its potential for being misused in sophisticated cyberattacks.

Embracing AI means using it carefully in our cybersecurity efforts, making sure we take advantage of its strengths to improve protection and innovation, while also staying alert to its risks.

The next step for us all is to accept and ‘Embrace AI as a Double-Edged Sword in Cybersecurity’ by understanding its potential, while remaining vigilant about its threats. By using AI to strengthen our security strategies and to counter its misuse, we can turn these challenges into opportunities for advancement.