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arXiv · 2609.11404

Deep-Fake CAPTCHA: Mitigating Next-Generation Social Engineering Attacks

Guy Frankovits·Lior Yasur·Fred M. Grabovski·Yisroel Mirsky
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Abstract

This paper presents DF-CAPTCHA, an active defense against real-time deepfake impersonation in voice and video calls. Instead of passively searching for artifacts, DF-CAPTCHA prompts the caller to perform simple challenge-response tasks that are easy for humans but difficult for current real-time deepfake systems to generate convincingly. The framework verifies the response using four criteria: realism, identity consistency, task completion, and response time. We evaluate the approach across both audio and video modalities using user studies and experiments with real-time deepfake models. Results show that people often struggle to distinguish real-time deepfakes from authentic media, while DF-CAPTCHA substantially improves detection performance over passive methods, reaching high accuracy in both modalities. These findings suggest that active challenge-based verification is a practical and robust defense against next-generation social engineering attacks based on real-time deepfakes.

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Guy Frankovits, Lior Yasur, Fred M. Grabovski, Yisroel Mirsky. 2026-09-10. Deep-Fake CAPTCHA: Mitigating Next-Generation Social Engineering Attacks. https://arxiv.org/abs/2609.11404

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