David Tutin
|
February 20, 2024

The impact of AI on cybersecurity – opportunities and risks

In an era where cyber threats evolve as rapidly as the technology designed to counter them, Artificial Intelligence (AI) has quickly emerged as a major force in the future direction of both good and bad actors. On one hand, AI-driven technologies are significantly enhancing the capabilities of security teams to detect and respond to emerging threats with unprecedented speed and efficiency. On the other, advanced AI capabilities are also being exploited by cybercriminals to devise more convincing phishing campaigns, automate the exploitation of vulnerabilities and even influence electoral outcomes. 

So, where is AI taking cybersecurity this year and beyond? Here, we take some of the key  challenges and opportunities as AI technologies are integrated into the security ecosystem:

How AI will be used by cybercriminals

Advanced phishing attacks

AI's capabilities are being leveraged by cybercriminals to craft highly convincing phishing campaigns. By analyzing communication patterns, 'bad AI' can generate emails and messages that closely mimic legitimate sources, making them increasingly challenging to identify and raising significant concerns for security teams.

Automated exploit development

AI tools also now enable cybercriminals to scan for vulnerabilities and automate the exploitation process, facilitating password cracking, backdoor identification and zero-day vulnerability exploitation at unprecedented scales. This level of automation heightens the risk of large-scale attacks with minimal effort from the attackers.

Electoral interference

The ability of AI to generate convincing text, images and videos has broad societal implications, particularly in the manipulation of public opinion and interference in democratic processes. With significant elections on the horizon during 2024, the potential for AI to influence public discourse and policy-making is a real concern.

How AI will improve cybersecurity

Automated threat detection

AI-driven cybersecurity systems are adding to the capabilities of security teams to detect emerging cyber threats. By sifting through vast datasets, these systems leverage machine learning to identify patterns and anomalies indicative of new attack vectors. This capability is crucial for recognizing and neutralizing complex threats such as polymorphic malware or advanced ransomware strategies, which may evade traditional security measures.

Incident response and remediation

The rapid response capabilities of AI are transformative for organizations worldwide. Upon identifying a threat, AI systems can swiftly enact protocols to mitigate emerging risks and breaches, including automatic patching, system isolation and real-time attack neutralization. In particular, this can help reduce the attack window and limit potential damage, underlining AI's role in delivering proactive cybersecurity defense.

Knowledge sharing

AI-driven virtual assistants and chatbots are revolutionizing the accessibility of cybersecurity knowledge. Offering personalized advice and risk assessments, these tools democratize cybersecurity awareness, catering to users without technical expertise and enhancing the overall security posture of organizations and individuals alike.

Enhancing Human Oversight

AI not only automates and enhances cybersecurity processes but also significantly boosts the capabilities of human security teams. By providing security professionals with advanced analytical tools and real-time data insights, AI enables more informed decision-making and strategic oversight. This synergy between human expertise and AI-powered automation ensures a more resilient and responsive cybersecurity framework capable of adapting to new threats as they emerge.

To read more about how Glasswall CDR helps organizations deliver proactive protection against advanced file-based threats, click here.

Book a demo

Talk to us about our industry-leading CDR solutions

Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.