Deepfake Video Detector
Detect AI-generated videos in under 60 seconds.
Spot AI-generated and manipulated videos before they become a risk. Upload MP4, MOV, WEBM files and get a detailed report instantly. No complicated setup, just fast analysis with clear, actionable results.
By uploading a file you agree to the Terms of Service and Privacy Policy.
Three steps from file to verdict.
Upload your video
Drag and drop or browse for MP4, MOV, WEBM files, up to 200 MB. No technical setup. Agree to the terms and get a verdict in under a minute.
AI-powered analysis
The detector runs a deep scan across several forensic and biological signals at once.
- Facial
- Blink patterns, micro-expressions, and lip-sync consistency
- Motion
- Motion artifacts and temporal inconsistencies across frames
- Generators
- Fingerprints matched against HeyGen, Sora, RunwayML, and more
Get your verdict
A verdict, a detection summary, and a confidence score, with an overview of the suspect regions detected in the file.
Likely Synthetic (High) means strong evidence of AI manipulation. Likely Synthetic (Low) suggests further review. Real (no AI) means no synthetic media was detected.
Who uses the deepfake video detector.
Six teams that verify a video before the decision that follows.
Banks & financial institutions
Verify customer-verification videos, reduce impersonation fraud, and strengthen identity checks during onboarding and high-value transactions.
Enterprise security teams
Catch deepfake videos before they become part of phishing attempts, executive impersonation scams, or internal security incidents.
Law enforcement agencies
Review suspicious digital evidence and identify videos that show signs of synthetic manipulation during investigations.
KYC verification teams
Improve digital onboarding by identifying face swaps and AI-generated identity videos before they enter verification workflows.
News & media organizations
Confirm the authenticity of user-generated videos before publication and reduce the risk of spreading manipulated content.
Compliance & risk teams
Add another layer of verification to existing fraud-prevention processes and strengthen trust across business operations.
Why online deepfake video detection matters.
Deepfake video has moved from novelty to a working fraud tool. The losses are documented.
In 2024, a finance worker at a Hong Kong multinational joined a video call where every colleague on screen, including the CFO, was a deepfake. He approved 15 transfers worth roughly $25.6 million before anyone realized the only real person on the call was him.
The FBI has warned that criminals now use generative AI to make these schemes more convincing and easier to run at scale. A recorded video that looks and sounds right is no longer proof that the person on it is real.
Verify the video before you act on it.
Why use the Diopter deepfake video detector.
Fast, secure, and tuned to the way synthetic media actually fails.
AI-powered video analysis
Advanced models process uploads in under a minute and return a verdict with a confidence score, so you can decide quickly.
Face-swap and forensic detection
Forensic analysis catches visual anomalies, expression mismatches, and synthetic artifacts that manual review tends to miss.
Trained against the tools attackers actually use.
Retrained against updated generator outputs before a new model reaches widespread deployment.
Explore other deepfake detection tools.
Same detection stack, tuned for each kind of media.
Deepfake Audio Detector
Detect cloned voices and synthetic speech by evaluating pitch, formants, and spectral patterns against known AI signatures.
Analyze audioDeepfake Image Detector
Check images for AI generation and manipulation using generator fingerprints, pixel irregularities, and suspect-region analysis.
Scan an imageDeepfake Video Detector FAQ.
Yes. It identifies multiple forms of video manipulation, including face swaps, AI-generated video, and synthetic visual artifacts. Rather than relying on a single indicator, it weighs several forensic and biological signals to judge whether a video is likely authentic or manipulated.
Every upload gets a confidence score alongside the result, not a simple yes or no. Depending on the analysis, results read as Likely Synthetic or Real, each with High or Low confidence, to support security and verification decisions.
The free video detector focuses on uploaded files. The Diopter enterprise platform extends detection to live voice and video conversations on Zoom, Teams, Meet, Webex, and phone calls by analyzing synthetic media, identity signals, and conversation behavior throughout a session. Book a walkthrough to see live monitoring.
Yes. Upload a supported video and receive a free detection report with insight on potential AI-generated content.
The free tool works through uploads for quick, individual checks. For integration, the full Diopter platform provides APIs to automate detection and connect it to your applications.
Yes. The detector supports secure, end-to-end encrypted processing to protect uploaded media and sensitive information, backed by robust security practices.
Yes. Diopter continuously evolves its detection to address emerging generation techniques, so coverage keeps pace as new deepfake models appear.
Research behind video deepfake detection
All research →Deepfake Video Detection Explained: How to Spot Them and How to Stay Safe
How deepfake video detection works in 2026: seven method families, what each catches, where each breaks, and how to layer them across your stack.
Deepfake Detection Methods
How deepfake detection actually works: six method families, what each catches, where each fails, and why your stack needs all of them.
Deepfake Detection for Video Conferencing: Zoom, Teams, Meet, and Webex
How deepfake attacks run on Zoom, Teams, Meet and Webex, why single-frame checks miss them, and what continuous detection during a live call looks at.
Real-time deepfake video defense for live calls.
The detector you just used is part of the Diopter platform, built for live-call video and voice defense on Zoom, Teams, Meet, and phone calls, with conversation scoring and high-volume batch processing.