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The rise of AI-powered fraud: How AI and deepfakes are changing the landscape of cybercrime

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The rapid development of artificial intelligence (AI) has revolutionized various aspects of our daily lives, from shopping and banking to entertainment and content creation. However, this progress also brings new and dangerous opportunities for cybercriminals to exploit AI technology in social engineering attacks, making it increasingly difficult to differentiate between real and fabricated information.

The growing threat of AI-driven fraud

According to the 2025 Identity Fraud Report, deepfake fraud attempts occur every five minutes on average. The World Economic Forum predicts that by 2026, 90% of online content could be artificially generated. Initially, deepfake attacks might appear to be targeting celebrities or public figures, but the real victims remain individuals and businesses, as always, with personal and financial information as the primary objectives.

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How AI is used in fraud: Three major tactics

  1. AI-enhanced phishing attacks
    Phishing scams have long been a common method for cybercriminals to trick individuals and companies into revealing sensitive information, like login credentials or payment card details. Traditionally, phishing emails were often generic, with poor grammar and spelling. Now, advanced language models (LLMs) allow fraudsters to create highly personalized and convincing phishing messages in multiple languages, even mimicking the style of known individuals by analyzing social media and online content. Additionally, AI tools can generate convincing visuals, further enhancing the effectiveness of phishing attacks.
  2. Audio deepfake scams
    Deepfake technology allows attackers to create synthetic media that mimics a person’s voice with disturbing accuracy. By using just a few seconds of audio, fraudsters can replicate someone’s voice and create fake voice messages that appear to come from trusted sources like family members or colleagues. In a dangerous scenario, a criminal could use a victim’s voice to ask for a financial transfer or confidential information. This can lead to substantial personal and corporate losses.
  3. Video deepfake scams
    Deepfake videos, created using AI tools, can replace faces, modify lip movements, and even add realistic voices. With a single photo, AI can produce a video of someone speaking or acting in a manner that is completely fabricated. Fraudsters can use this technology to create fake advertisements, conduct deceptive calls, or even impersonate people in live video calls. This opens the door to highly manipulative scams that could result in financial fraud or reputational damage.

Real-life examples of AI-powered fraud

At Kaspersky, the misuse of large-scale language models (LLMs) for phishing and fraud is already evident. Fraudsters are using AI-generated content to create plausible phishing websites, making their scams more convincing. There are also high-profile deepfake attacks: for instance, a victim was tricked by a deepfake version of Elon Musk, who supposedly invited him to invest in a project, leading to significant financial losses.

Deepfake technology has also been used for more personal scams, such as AI-driven romance scams. Fraudsters use fake identities to interact with victims via video calls, building trust before asking for money for supposed emergencies. In one recent case, a group of scammers stole $46 million across Taiwan, Singapore, and India using these tactics.

How to protect yourself from AI-powered threats

As AI technology continues to evolve, so must our defenses. There are technical and non-technical strategies to mitigate the risks posed by AI-driven scams:

  1. AI-generated content detection
    Future models of AI may include watermarks, invisible to the human eye, which algorithms can detect to identify and flag AI-generated content. While this could help in detecting content created by major AI companies, malicious actors may circumvent these safeguards by developing their own language models.
  2. Deepfake detection tools
    Deepfake detection technology recognizes anomalies in images, voices, and text that suggest manipulation. However, these tools must evolve as fast as AI technologies to remain effective.
  3. Digital signatures for video and audio
    Digital signatures, already used for banking transactions, could be applied to video and audio content. This technology would verify the authenticity of media, ensuring that videos and voice messages are legitimate.

Education: The key to defending against AI threats

While technical measures are crucial, education and awareness remain the most effective defenses against AI-powered scams. Many people are still unaware of how easily AI can be used to create fraudulent content. Cybercriminals exploit this lack of knowledge, underscoring the importance of open dialogue and educational campaigns to raise awareness about these emerging risks.

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Conclusion: Staying safe in an AI-driven world

Although AI-powered threats, including deepfakes, are becoming more sophisticated, understanding these risks is the first step in mitigating them. By staying informed and vigilant, individuals can better protect themselves from fraud, while organizations can implement improved security practices. Through cooperation and awareness, we can build a safer, more resilient digital world that counters the growing threat of AI-driven crime.

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