Deepfake Detector — Detect AI-Generated Images and Videos
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Supports JPG, PNG, WebP images, MP4, WebM videos (max 50MB)
Detect pixel anomalies, edge artifacts, facial geometry inconsistencies in images/videos. AI-generated images typically leave traces in details such as eyes, teeth, and backgrounds.
Inspect DCT-based frequency-domain patterns. AI-generated images often produce spectral distributions that differ from natural photos, which helps flag suspicious media.
Detect AI-generated and manipulated images using deep learning analysis. Identify deepfakes with confidence scoring. Free. This page is built for people who want a fast path to a working result, not a vague prompt-and-pray workflow. If you need a more reliable first draft, cleaner output, or a repeatable workflow you can hand to a teammate, Deepfake Detector is designed to shorten that path.
Most visitors use Deepfake Detector because they need something specific done now: a deliverable, a decision, or a workflow checkpoint. The sections below show the fastest way to get value from the tool and the adjacent pages that help you keep going.
Upload an image to check if it was AI-generated or manipulated.
For journalists, researchers, and anyone wanting to verify image authenticity.
Verify image authenticity before publishing
Check suspicious viral images
Verify profile photos of applicants
Run screenshots, photos, and memes through a quick authenticity check before reposting or citing them.
Use the probability score and visual indicators as one signal in a broader image verification workflow.
Review applicant, creator, or community-submitted images for obvious manipulation before relying on them.
A strong outcome from Deepfake Detector is not just “some output.” It should be usable with minimal cleanup, aligned to the task you opened the page for, and specific enough that you can paste it into the next step of your workflow without rewriting everything from scratch.
If the first pass feels too generic, use the use cases, FAQs, and related pages here to tighten the scope. That usually produces better results faster than starting over in a blank chat.
Compare the strongest deepfake detection workflows before deciding which verification path fits your risk level.
Open page →Follow the practical video verification workflow when a clip looks suspicious but you need stronger review steps.
Open page →Use a task-focused playbook for screening manipulated, synthetic, or suspicious still images.
Open page →