Detect Deepfakesby Resemble AI

Check if it's a deepfake.

Detect deepfakes in audio, images, and video — free, from Resemble AI. Drop a file and get a verdict, plus the reasoning behind it.

Free detector · Cited incidents · Enterprise API
Multimodal deepfake detection

Select an audio, image, or video file.

Opt in to depth analysis on the why behind the results.

Deepfake Incident Database

Deepfake incidents Resemble is built to stop.

The strongest signal on this site is the public record: real voice-clone scams, synthetic images, video-call impersonation, election disinformation, and platform abuse. The database refreshes as new verified incidents are added, so the homepage stays grounded in what attackers are doing now.

4865
verified incidents
672
audio cases
1292
video cases
1593
image cases
Latest verified incidents

Fresh examples for deepfake fraud, AI voice scams, and synthetic media abuse.

Each incident links to cited sources and a breakdown of where detection, provenance, watermarking, or workflow controls could have helped. This is why the detector exists: not as a demo, but as a public front door into Resemble's deepfake intelligence stack.

mixed

hospital systems, banks, and various corporate entities

Three individuals were indicted for a global fraud scheme using AI voice and image impersonation to steal approximately $129 million from corporate entities

Multimodal detection · 1 cited source →
mixed

Mirza Rahmath Baig

Six individuals were arrested in Hyderabad for attempting to extort 5 crore from MLC Mirza Rahmath Baig using threats of releasing morphed photos and deepfake.

Multimodal detection · 1 cited source →
mixed

LeBron James

LeBron James legal team demanded the removal of an unauthorized AI-generated advertisement featuring his likeness and voice used by the Bron AI betting.

Multimodal detection · 1 cited source →
image

Hinge dating app users

Hinge users are reporting deceptive dating profiles featuring AI-generated faces superimposed onto photographs of other men to create fake identities

Image provenance · 1 cited source →
image

Laura

A woman targeted by a sheriff impersonation scam used AI to generate and send a fake arrest photo of herself to the caller after realizing the threat was.

Image provenance · 1 cited source →
mixed

Missouri hospital system, Rhode Island bank, California hospital system, British financial technology company, Massachusetts mutual fund company, Florida pet food manufacturer

An international criminal network used AI-generated voices and faces to impersonate executives and lawyers, defrauding global organizations of over $129.

Multimodal detection · 1 cited source →
Deepfake detection guide

A free detector backed by real attack intelligence.

What the detector checks

Deepfake detection works best when several signals are considered together. Audio files can expose vocoder fingerprints, unusually regular timing, or cloned-speaker artifacts. Images can reveal diffusion-model texture, inconsistent camera noise, manipulated faces, missing provenance, or repeated compression patterns. Video adds temporal evidence: identity drift, lip-sync mismatch, unstable lighting, and frame artifacts that are hard to see by eye.

Why the incident database matters

Search results for deepfake detection are full of generic tools. The difference here is the incident record underneath the interface. Each verified case shows the attack pattern, the affected victim or organization, the media type, and the public sources behind the report. That makes the homepage useful for people searching for a free deepfake detector, deepfake fraud examples, AI voice scam evidence, or a cited database of synthetic-media abuse.

When to move from a free check to Resemble AI

A one-off upload is enough for a suspicious voicemail or viral image. Organizations need a different layer: API-based screening, media-intelligence workflows, watermarking and provenance checks, model updates, and reporting that fits fraud, trust-and-safety, newsroom, or compliance operations. That is the role of Resemble AI behind this public detector.

Questions

Frequently asked questions

+How does the free deepfake detector work?

Upload audio, image, or video and the detector looks for synthetic-media signals such as voice-clone artifacts, diffusion fingerprints, face-swap traces, and inconsistent provenance signals.

+Why feature deepfake incidents on the homepage?

The incident database shows the real attacks behind the tool: voice-clone fraud, election robocalls, synthetic images, video-call impersonation, and other AI-media abuse cases.

+Can Resemble prevent every incident listed here?

No single product prevents every attack. Resemble provides detection, watermarking, verification, and intelligence layers that help organizations identify and reduce deepfake risk.

+Is the incident database updated?

Yes. The Deepfake Incident Database is maintained as a continuously updated public reference with cited sources and stable incident URLs.

From public check to production layer

Need deepfake detection inside your product or workflow?

Resemble AI gives teams the detection API, watermarking and provenance checks, media intelligence, and operational workflows needed to respond to the same attack patterns tracked in the incident database.