As we step into 2025, we have already witnessed that Generative AI causes phenomenal changes in content creation, as it can facilitate the creation of unbelievably realistic synthetic media popularly referred to as deepfakes.
The audio, videos, and images produced by this AI will imitate real individuals so accurately as to make it increasingly difficult to tell what is real and what is not. Economic accessibility to such simple-to-use but powerful GenAI tools is largely blamed for the reduced entry barriers that have led to the creation of deepfakes by malicious actors.
Such deepfakes are being put to very evil uses in cyberattacks. Now that such synthetic media are fast taking their place, a question that arises is whether we are ready to deal with a variety of cyberthreat-propagating deepfakes.
These generative AI models, including Generative Adversarial Networks (GANs) and diffusion models, are known for producing highly realistic synthetic media by learning patterns from massive datasets. With tools like DeepFaceLab, Synthesia, and ElevenLabs, the barrier to creating deepfakes has dramatically lowered, enabling even those with minimal technical expertise to generate convincing audio and video impersonations.
What was once seen as novelty or entertainment now poses serious cybersecurity threats. These deepfakes can mimic voices, replicate faces, and even forge biometric features, creating new avenues for cybercriminals to bypass authentication systems, compromise personal privacy, and infiltrate secure environments. Given these risks, Generative AI in cybersecurity certification has become crucial for professionals aiming to understand, mitigate, and secure against these evolving threats in modern cyber landscapes.
As a result of incorporating deepfakes into the toolbox of cybercrime, new vectors were opened and incorporated:
These vectors demonstrate the wide-ranging threats deepfakes present to any organizational environment and the need for proactive defenses.
In 2024, highly publicized occurrences in Hong Kong drew attention to how the increasing use of deepfake technology for cybercrime has ramifications. Fraudsters used high-end deepfake software to impersonate the CFO of a multinational corporation in a video call; the scam artists convincingly mimicked the CFO's voice and face to gain the trust of a finance clerk.
Under the impression that they were dealing with a bona fide executive, the clerk authorized the transfer of $25 million into the hands of the criminals. This attack further exposes the potential of deepfake technology to circumvent traditional security measures such as voice and facial recognition, thereby posing serious implications for businesses, while simultaneously growing more sophisticated in their cyber threat activities.
The report from CrowdStrike in 2025 also noted a sharp 442% rise in voice phishing attacks, wherein almost half of the Chief Information Security Officers reported facing threats related to deepfakes. These figures point to the increasing prevalence and sophistication of cyberattacks using deepfakes.
The conventional tools for Generative AI Cybersecurity, such as phishing filters and antivirus software, are poorly suited to detect and act against deepfake threats. Their prime concern is known malware signatures and not synthetic media made by advanced AI models.
Besides, the human factor could remain an insecurity; well-trained professionals can still be tricked by high-quality deepfakes, putting them in a position unable to be countered by any traditional systems. Such a gap stands in the way of creating and integrating specialized tools and protocols.
The study conducted by CSIRO and Sungkyunkwan University highlights the fact that existing deepfake detection tools only manage to correctly identify AI-generated content 69% of the time in real-world conditions. This essentially means that the deepfake detection models are also having trouble keeping up with the rapid advances made in deepfake technology.
The organizations have adopted various measures in the fight against the threats posed by deepfakes:
AI vs AI: The detection of AI-based threats by AI is on its way to becoming a new trend. Maintaining security integrity requires the installation of systems that can analyze anomalies in content, indicative of deepfakes.
GenAI-enabled deepfakes don't sound like future threats anymore; these malicious technologies are already here and can wreak havoc in the present by eroding trust, security, and integrity across all industry sectors. Organizations must move forward by embracing advanced detection tools, modified authentication protocols, and fostering a mindset of awareness to mitigate these risks. GSDC offers crucial training and certification programs to help professionals develop the necessary skills to safeguard against the growing threat of deepfakes and other generative AI-driven cyber risks.
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