# DeepFake Audio Detector — Detect cloning voice

> Detect cloning voice (iPhone/iPad app by Hanva,LLC.)

- Source: https://appshunter.io/ios/app/deepfake-audio-detector/id6783680623 (this page in markdown: same URL + `.md`)
- Developer: [Hanva,LLC](https://appshunter.io/developer/1808930111)
- Category: Productivity, Lifestyle
- Price: Free with in-app purchases
- Age rating: 4+
- Requires: iOS 17.0 · 2 MB
- Languages: American English
- Released: 2026-06-26
- Data updated: 2026-07-02
- User reviews in markdown: https://appshunter.io/ios/app/deepfake-audio-detector/id6783680623/reviews.md

## What is DeepFake Audio Detector?

Spot potential AI‑generated voices before they trick you.
DeepFake Audio Detector uses on‑device machine learning to estimate whether a voice recording is more likely real or synthetically generated (deepfake).

Use it when you receive suspicious voice messages, audio files, or calls recorded from another device — and get an instant AI‑based risk assessment.

How it works
DeepFake Audio Detector runs a custom Core ML model directly on your iPhone.
Simply:

Analyze live microphone audio – tap “Microphone analysis” and speak or play audio near your phone.
Analyze an audio file – import a .wav, .m4a or .mp3 file from Files, iCloud or other apps.
See a clear result: “Real voice” or “Deepfake (synthetic)” with a confidence score.
No audio is sent to external servers; analysis is performed locally on your device where possible.

Key Features
AI‑powered deepfake voice detection
Custom machine learning model trained to distinguish natural human speech from synthetic / cloned voices.

Live microphone analysis
Check voices in real time using your iPhone’s microphone — useful for quick checks during conversations or calls on speaker.

File analysis
Import recordings from Files, iCloud Drive and other apps to test voice messages, podcasts, clips and more.

Clear confidence score
See how confident the model is in its prediction, so you can better judge the level of risk.

Detection history
Review your recent checks with date, source (microphone or file) and model confidence.

Modern, privacy‑first design
All analysis runs on‑device using Apple’s Core ML and SoundAnalysis frameworks. Your audio stays under your control.

Designed for security‑aware users
Helpful for journalists, creators, security professionals and anyone who wants an extra layer of protection against voice scams.

Important Disclaimer
DeepFake Audio Detector provides probabilistic estimates based on a machine learning model.
Results are not 100% accurate and:

should not be used as legal proof or for biometric identification;
should not be the only basis for critical decisions;
are meant as an additional signal to help you evaluate potential deepfake audio.
Always combine the app’s output with your own judgment and other sources of information.

Subscription Plans:
- Payment will be charged to your App Store Account at confirmation of purchase. 
- Your subscription will automatically renew unless auto-renew is turned off at least 24 hours before the end of the current subscription period.
- Your account will be charged for renewal within 24 hours prior to the end of the current subscription period. Automatic renewals will cost the same price you were originally charged for the subscription. 
- Manage or cancel your subscription from your user settings in the App Store at any time after purchasing.
- Any unused portion of a free trial will be forfeited if you purchase a subscription.

Privacy Policy: https://sunteame.com/privacy-policy/
Terms And Conditions:https://sunteame.com/terms-of-service/

## Pricing and in-app purchases

Base price: Free.

**Subscriptions**

| Subscription | Price | Period |
| --- | --- | --- |
| Weekly Subscription Plan | $1.99 | per 7 days |
| Monthly Subscription Plan | $8.99 | per month |
| Yearly Subscription Plan | $49.99 | per year |



## Version history (last 1 release)

### 1.0 — 2026-06-26

No release notes.

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All apps by Hanva,LLC: https://appshunter.io/developer/1808930111

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*Data collected daily from the US App Store and indexed by [AppsHunter](https://appshunter.io/). User reviews are verbatim App Store reviews. Ratings, prices and chart positions refresh continuously; this snapshot is from 2026-07-02.*