Individual skill
detecting-deepfake-audio-in-vishing-attacks
Detect AI-generated deepfake audio used in voice phishing (vishing) by extracting spectral features (MFCC, spectral centroid, spectral contrast, zero-crossing rate) and classifying samples with machine learning models, supporting batch audio analysis, confidence scoring, and forensic reporting. Use for deepfake voice detection, vishing investigations, AI-generated speech analysis, voice cloning detection, or audio authenticity verification.
skills/detecting-deepfake-audio-in-vishing-attacks/SKILL.md
Source commit 54a798831d2266a3ca61ce68a7acb80b81160d57
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- Last checked
- Nov 9, 2026
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- Repository stars (not skill ratings)
- 35,887
- Repository last updated
- Aug 31, 2026
- License
- Apache-2.0
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- ai-agents Repository topic
- claude-code Repository topic
- cybersecurity Repository topic
- incident-response Repository topic
- mitre-attack Repository topic
- penetration-testing Repository topic
- red-team Repository topic
- security Repository topic
- cloud-security Repository topic
- malware-analysis Repository topic
- deepfake-detection Declared skill tag
- vishing Declared skill tag
- audio-forensics Declared skill tag
- mfcc Declared skill tag
- spectral-analysis Declared skill tag
- voice-cloning Declared skill tag
- education Derived category
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Read excerpt
# Detecting Deepfake Audio in Vishing Attacks
## When to Use
- A suspected vishing call used an AI-cloned executive voice to authorize a wire transfer
- Security operations received a voicemail that sounds like the CEO but the tone seems off
- Incident response needs to determine whether a recorded phone call contains synthetic speech
- Fraud investigation requires forensic proof that audio was AI-generated
- Red team exercises use voice cloning and blue team needs detection capability
**Do not use** for text-based phishing (email/SMS); use email header analysis or URL detonation tools instead.
## Prerequisites
