Episode

Can Voice Deepfake Detection Keep Up With the 1600% Surge in Fraud Attacks?

Podcast
The Good Tech Companies
Published
May 24, 2026
Duration seconds
984
Processing state
not_requested
Canonical source
https://share.transistor.fm/s/92865d1e
Audio
https://media.transistor.fm/92865d1e/b28dd4c5.mp3
JSON
/v1/public/podcasts/the-good-tech-companies-6882802/episodes/can-voice-deepfake-detection-keep-up-with-the-1600-surge-in-fraud-attacks
Markdown
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Summary

This story was originally published on HackerNoon at: https://hackernoon.com/can-voice-deepfake-detection-keep-up-with-the-1600percent-surge-in-fraud-attacks . Deepfake vishing surged 1600% in 2025. Most detection tools analyze text, not audio — and miss what matters. Here's how voice-native detection actually works. Check more stories related to cybersecurity at: https://hackernoon.com/c/cybersecurity . You can also check exclusive content about #fraud-detection , #voice-fraud , #enterprise-security , #audio-native-detection , #vishing-attacks , #synthetic-voice-fraud , #spectrogram-analysis , #good-company , and more. This story was written by: @modulate . Learn more about this writer by checking @modulate's about page, and for more stories, please visit hackernoon.com . Deepfake fraud is accelerating and most detection systems are built wrong — they analyze transcripts instead of raw audio, missing the synthetic speech artifacts that actually reveal a fake. This piece breaks down how attacks work in production, why text-first detection fails, and how audio-native models like Modulate's Deepfake Detection API catch what humans and biometrics can't.