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Evolution of stronger cyber threat actors: The flip side of Gen AI story

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By Kumar Ritesh, Founder & CEO, CYFIRMA

In the ever-evolving landscape of cybersecurity, staying ahead of malicious actors is an ongoing challenge. While we have witnessed the tremendous benefits of artificial intelligence (AI) and machine learning (ML) in enhancing cybersecurity defenses, threat actors have also embraced these technologies to develop more sophisticated and dangerous attack vectors. One such subset of AI, known as Generative AI, has gained popularity among cybercriminals. Let’s explore how Generative AI is being utilised by threat actors and delve into the top cyber threats it presents to organisations like social engineering, deepfake, and phishing attacks, advanced malware, and password cracking.

More effective phishing with Generative AI

Phishing attacks have long been a favorite among cybercriminals due to their effectiveness in tricking individuals into divulging sensitive information or downloading malware. Generative AI has taken these attacks to new heights by enabling threat actors to create highly convincing, personalised phishing emails and websites.

With the help of Generative AI, attackers can craft emails that mimic the writing style and tone of a victim’s colleagues or superiors. They can also generate fake login pages that look nearly identical to legitimate ones, making it extremely difficult for users to distinguish between genuine and malicious communications. As a result, organisations are facing a significant increase in successful phishing attacks, leading to data breaches and financial losses.

Realistic disguise with deepfake

Deepfake technology, a subset of Generative AI, allows threat actors to create convincing video and audio forgeries. This presents a substantial threat to organisations as deepfake attacks can tarnish reputations, manipulate public opinion, and even influence financial markets.

Imagine a scenario where a CEO’s voice is convincingly mimicked, disseminating false information that impacts stock prices; or consider a deepfake video of a prominent figure endorsing a product or idea they never actually supported. Such manipulations can lead to severe consequences for businesses and society at large.

Tailored malware for effective attacks 

Generative AI is revolutionising the way malware is created. Threat actors can use AI algorithms to generate highly evasive and adaptable malware variants that can easily evade traditional signature-based antivirus solutions. These AI-generated malware strains constantly evolve, making detection and containment a significant challenge for cybersecurity professionals.

Moreover, Generative AI allows for the customisation of malware based on the target environment. Attackers can create malware tailored to specific operating systems, applications, or even individual organisations, increasing the likelihood of successful infiltration and data exfiltration.

Password security in question 

Password cracking is a fundamental technique used by cybercriminals to gain unauthorised access to systems and accounts. Generative AI has accelerated the process by enabling the rapid generation of password lists and the use of sophisticated attack methods such as dictionary attacks, brute-force attacks, and credential stuffing.

AI-driven password-cracking tools can learn from previous breach data and adapt their strategies to bypass security measures. This poses a severe threat to individuals and organisations alike, as weak or reused passwords become easy targets for AI-powered attacks. Organisations must employ robust password policies and multifactor authentication to mitigate this threat.

Impactful convincing through social engineering attacks

Social engineering attacks have always relied on manipulating human psychology to deceive victims into taking actions that benefit attackers. Generative AI has made it easier for threat actors to conduct these attacks at scale, exploiting vulnerabilities in human judgment and trust.

Generative AI can craft highly convincing social engineering messages, imitating the style, tone, and context of genuine communications. These messages may exploit current events, leverage personal information, or impersonate trusted individuals, making it challenging for users to identify them as threats. As a result, employees and individuals are more susceptible to falling victim to social engineering attacks, which can lead to data breaches and other security incidents.

In a nutshell…

The rapid advancement of Generative AI is reshaping the threat landscape in cyberspace. While AI and ML have played pivotal roles in strengthening cybersecurity, threat actors are leveraging these same technologies to launch more sophisticated and dangerous attacks. The top five cyber threats presented by Generative AI – phishing attacks, deepfake assaults, advanced malware generation, password cracking, and automated social engineering attacks – underscore the urgent need for organisations to enhance their cybersecurity defenses.

To combat these threats, organisations must adopt a proactive cybersecurity posture that includes user education, AI-driven threat detection, and continuous monitoring. Staying ahead of cybercriminals requires constant vigilance and the adoption of cutting-edge security technologies. As Generative AI continues to evolve, the ability to defend against AI-driven threats will become increasingly crucial, and this involves using AI to fight AI.

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