Video Forensics Studio
By Ned Walsch · Last updated:
The video counterpart to the Photo Forensics Studio. Load a clip and run a battery of forensic filters — temporal checks that only video makes possible (flicker, motion, frozen and duplicate frames) plus per-frame spatial passes (ELA, noise, JPEG grid) on any frame you pick. Everything runs in your browser; the video is never uploaded. An optional AI detector adds a second opinion.
How do I check whether a video has been edited or AI-generated? Run temporal checks that only video makes possible: frame-to-frame difference, optical-flow motion magnitude, luminance flicker, and frozen or duplicate frame detection. Video Forensics Studio samples 24, 48, or 96 frames entirely in your browser, then applies per-frame spatial passes — Error Level Analysis, noise residual, and JPEG grid — to any frame you pick. An optional AI detector (onnx-community/deepfake-detection-model) runs on WebGPU when available. No single signal is proof; treat every result as a lead.
A quick read of the automated checks. Amber or red flags are reasons to look closer — not verdicts. Scroll down for the detail behind each.
No single clue is proof — triangulate. Real forensic work combines visual inspection, metadata, geometry, and several independent analyses, and trusts a conclusion only when they agree. Social-media compression erases many of these traces, and authentic footage can trip every filter here. Use this studio to find where to look and what to question, then corroborate. For anything with real stakes, bring in a qualified examiner.
Where the processing happens
Your browser decodes the video and steps through sampled frames on a canvas. The temporal charts and per-frame passes are plain pixel math — no model, no upload. If you enable the optional AI detector, a model downloads once from a public CDN, is cached, and runs locally too. Nothing is ever sent to a server; you can confirm this in your browser’s network tab.
Temporal checks (flicker, motion, frozen/duplicate)
These exploit the fact that manipulations rarely stay perfectly consistent across time. Inserted or deleted frames break the difference rhythm; face-swaps and composites warp or flicker; loops and padding show as duplicate frames. They are strong leads, but ordinary things — cuts, fast motion, static tripod shots, low frame rates — can mimic them, so read the charts in context.
Per-frame spatial checks (ELA, noise, JPEG grid)
Applied to a single frame, these are the same passes as the Photo Forensics Studio. ELA is familiar but weak — edges glow regardless of tampering and recompression erases it. Noise and grid checks can reveal a spliced region that came from another source. Video compression is harsher than JPEG, so treat these as supporting context, never as standalone proof.
The optional AI detector
It is off by default for a reason: it downloads a model of tens of megabytes and is much slower and more resource-hungry than the canvas checks, especially without WebGPU. It scores frames for how synthetic they look, but it can be wrong in both directions — missing a careful fake and flagging clean footage — and it does not explain itself. Use it as one more voice, not the deciding one.
Responsible use
A flag here is not an accusation. Do not publish a manipulation claim on the strength of these automated signals alone, be careful about conclusions that could harm someone, and remember the tool cannot make a determination. Only analyze footage you have the right to. See Is OSINT legal? and, for provenance signals, C2PA & content credentials.
Can this tool prove a video is a deepfake?
No. It surfaces signals consistent with manipulation, CGI, AI, or editing, but no single signal is proof. Compression erases traces and real footage can false-positive. Corroborate across analyses and, for real stakes, consult a qualified examiner.
How does the temporal analysis work?
It samples frames and compares them over time — difference, motion, luminance flicker, and near-identical frames. Manipulated regions flicker or warp; inserted, deleted, or duplicated frames break the natural rhythm. These clues exist only in video, not a single image.
Is my video uploaded to a server?
No. Decoding and every analysis run in your browser on a canvas, plus an optional local model. The file never leaves your device.
What is the optional AI detector, and why is it off by default?
It runs a neural network over sampled frames to estimate how AI-generated or face-manipulated they look. It is off by default because it downloads a model of tens of megabytes and is much slower and heavier than the canvas analyses, especially without WebGPU. The built-in checks are instant; enable the AI detector only for a second opinion.