AI and Cybersecurity: Fighting Deepfakes with Intelligence

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A real-world look at how AI-driven cyberattacks are evolving—and why integrating AI into cybersecurity is essential for modern defense.

AI as a New Cybersecurity Threat

As technology and particularly Artificial Intelligence have matured, in recent years AI has shifted from simple theoretical threat to a major tool in the arsenal of cyber hackers.

Attackers are using AI to bypass the human element of security.

Two (2) significant examples are discussed below:

1. The Ferrari Deepfake Attempt (July 2024)

In one of the most high-profile near-misses of 2024, a senior executive at Ferrari was targeted by a sophisticated voice-cloning scam.

• The Attack: A threat actor used AI to perfectly mimic the voice of Ferrari’s CEO, Benedetto Vigna. The scammer called the executive, claiming a "top-secret acquisition" required an urgent and confidential fund transfer.
• The AI Twist: The deepfake was so convincing that it captured the CEO's specific Italian accent and precise speaking style.
• The Outcome: The executive became suspicious because the "CEO" sounded slightly too mechanical during a moment of pressure.4 He asked a specific personal question about a book they had recently discussed, which the AI could not answer, causing the attacker to hang up.

2. The Arup Deepfake Video Heist (Early 2024)

The British engineering firm Arup was not as lucky, losing $25 million to an AI-driven scheme.

• The Attack: An employee in the Hong Kong office was invited to a video conference call with what appeared to be the company’s Chief Financial Officer and several other colleagues.
• The AI Twist: Every person on that call—except the victim—was a deepfake recreation. The attackers used publicly available footage of the executives to create live, moving avatars that could interact in real-time.
• The Outcome: Believing he had received direct orders from his superiors during a live meeting, the employee carried out 15 transfers to five different bank accounts before the fraud was discovered.

What Is the Solution?

Leverage the same AI tools that hackers use and integrate AI with cybersecurity.

Why?

• AI’s ability to process vast data in real-time speeds up cybersecurity incident response by automating alert triage and executing response playbooks, which reduces detection and response times.
• Today’s complex IT environments require proactive, adaptive security systems.
• AI excels at recognizing attack patterns, detecting anomalies, and automating tasks—key capabilities for modern cybersecurity.

Real-World Applications of AI in Cybersecurity

• AI is already used in intrusion detection systems (IDS), phishing detection and prevention, and malware classification and analysis. These applications show its practical value.
• Machine Learning (ML) models detect threats by learning from historical data and adapting to new attack patterns.
• What’s the gotcha? Despite its benefits, AI poses risks such as adversarial attacks, biased data, and over-reliance on automation. These risks must be managed through implementing the principles of Zero Trust.