---
title: "Is This Video AI? Check Its Metadata | metadata.video"
description: "How to tell if a video is AI: check Content Credentials, watermarks, metadata, visual tells and the source, and what each can’t prove. Free checker, no upload."
url: https://metadata.video/is-this-video-ai
---

Free · runs in your browser

# Is this video AI? How to check, and what no test can tell you

A practical order of checks, from provenance data to the source of the clip, with an honest note on what each one can and cannot prove.

There is no reliable one-click test that tells you whether a video is AI-generated. The strongest evidence is provenance: a signed Content Credentials (C2PA) manifest or a maker’s watermark that says an AI tool made the clip; after that come the file’s other metadata, what you can see and hear, and above all where the video came from.

Each of those checks can confirm an AI origin when it finds something, and none of them can prove a clip is real when it finds nothing. Most videos you meet online have been re-uploaded, and platforms strip metadata as a matter of routine, so a genuine phone clip and an AI clip downloaded from social media often look identical at the file level.

This site can help with the metadata part. Open a video here and the **Provenance** section shows any Content Credentials, the AI-generation assertion if there is one, encoder and software tags, and signs of re-saving. It reads the file in your browser and uploads nothing. It does not judge pixels, does not verify signatures and cannot read invisible watermarks; this guide says where to go for those.

## How to check whether a video is AI, step by step

Work through these in order. Stop when you have strong evidence either way, and treat “nothing found” as “unknown”.

1. ### Find the earliest copy
Trace the clip back to whoever posted it first, and get that file if you can. A copy of a copy has lost most of its metadata; the original upload, or the file from the person who recorded it, is worth far more.
2. ### Check Content Credentials
Open the file at contentcredentials.org/verify, in the Gemini app, or in Google Photos under **More** → **About** (“How this was made”). A valid manifest that names an AI tool, or says the content was created by a generative model, is the strongest evidence available.
3. ### Look for a maker’s watermark
For Google AI tools, ask the Gemini app whether the video was made with Google AI; it checks for the SynthID watermark in clips under 100 MB and 90 seconds. Some generators also add a visible watermark or logo that crops and re-uploads may have removed.
4. ### Read the rest of the metadata
Check for camera make and model, location, recording dates and the encoder tag. A camera original with consistent device data is a point in its favour; an editor or generic encoder tag only shows the file was re-saved.
5. ### Watch, listen and check the story
Look for physical and continuity errors, listen for odd audio, and compare the claims made about the clip with other reporting of the same event. Weigh everything together rather than trusting any single sign.

## What each check can and cannot prove

__An honest summary. Only provenance and source work can settle the question; everything else adds weight.__
| Check                                        | If it finds something                                            | If it finds nothing                           | How easy to defeat                                          |
| -------------------------------------------- | ---------------------------------------------------------------- | --------------------------------------------- | ----------------------------------------------------------- |
| Content Credentials (C2PA) naming an AI tool | Strong evidence, once the signature verifies                     | Nothing: most real and AI clips carry none    | Easy to strip; very hard to forge a valid signature         |
| Invisible watermark (such as SynthID)        | Strong evidence for that vendor’s tools                          | Nothing about other vendors’ tools            | Designed to survive compression; may fail after heavy edits |
| Visible logo or watermark                    | Suggestive; logos can be added to anything                       | Nothing; it may have been cropped             | Very easy                                                   |
| Camera make, model, location, dates          | Weak evidence of a real camera; tags can be typed in             | Nothing; uploads strip them                   | Easy, with any metadata editor                              |
| Encoder or software tag                      | Shows which app last saved it                                    | Nothing                                       | Easy                                                        |
| Visual and audio tells                       | Suggestive, sometimes conclusive (impossible physics)            | Nothing; good generators avoid obvious errors | Improving every few months                                  |
| “AI detector” websites                       | A probability score of unclear accuracy                          | A probability score of unclear accuracy       | Compression and edits move the score                        |
| Source and context                           | Often decisive: an original uploader, other angles, news reports | Unverified, not disproved                     | Hard to fake convincingly across many sources               |

No metadata means no conclusion. A clip with no camera data and no credentials is exactly what both a re-uploaded phone video and a re-uploaded AI video look like.

## Check 1: provenance (Content Credentials and watermarks)

Content Credentials are a signed record inside the file that says how it was made. Several AI video tools now attach them by default, and a few cameras sign what they record, so this is the check most likely to give a firm answer when it finds something.

How Content Credentials build a history: the generator or camera signs the first record, each supporting editor adds its own, and a verifier checks every signature and hash along the chain.

### Who says they add provenance to video

* **Adobe** says Firefly Video Model outputs include Content Credentials.
* **Microsoft** says every Bing Video Creator video carries C2PA content credentials.
* **Google** says all Flow outputs carry an invisible SynthID watermark, and content made or edited with its Omni model in the Gemini app, Flow or YouTube also carries C2PA credentials.
* **OpenAI** said Sora videos carried C2PA metadata and, on downloads, a moving visible watermark. It announced in March 2026 that it is discontinuing Sora, but clips made earlier are still circulating.
* **TikTok** says it reads Content Credentials to label AI content made with other tools, and **LinkedIn** shows a C2PA icon on signed image and video posts.

These are the vendors’ own statements, checked on 7 November 2026\. Open-source and self-hosted video models usually add nothing at all, so the absence of credentials is common for AI clips too.

### Reading versus verifying

The [Content Credentials viewer](https://metadata.video/content-credentials-viewer) here reads the manifest and explains it, including the digitalSourceType, where `trainedAlgorithmicMedia` means “created by a generative AI model”. It does not check the signature, so a manifest could in principle be forged. For that, use contentcredentials.org/verify or the Gemini app, which verify signatures against a trust list.

## Check 2: the rest of the metadata

Without credentials, the ordinary metadata gives weaker hints. It is still worth a look, mainly because a genuine camera original tends to be rich and internally consistent, and because the encoder tag tells you what last touched the file.

The layers a video file can carry: container data, stream details, descriptive tags, device and location data, and provenance. Each re-save or upload can strip one or more of them.

__Signals in ordinary metadata, from strongest to weakest.__
| What you see                                                                     | What it suggests                                      | Why it is not proof                                      |
| -------------------------------------------------------------------------------- | ----------------------------------------------------- | -------------------------------------------------------- |
| Make, model, lens and software of a phone, with a location and a local time zone | Probably recorded on that device                      | All of it can be typed in with a metadata editor         |
| Telemetry tracks from a drone or action camera                                   | Very likely a real recording from that kind of device | Rarely faked, but rarely present after sharing           |
| An editing app or a generic library such as Lavf in the encoder field            | The file was re-saved or converted                    | Every platform and most editors re-save real footage too |
| No device data, a round duration, no audio track                                 | Consistent with a generator’s output                  | Also consistent with any re-upload or screen recording   |
| Dates that disagree, or a 1904 or 1970 default                                   | The file was rewritten by software                    | Common on innocent files sent through apps               |

The [video forensics guide](https://metadata.video/video-forensics) goes deeper into dates, encoder tags and re-encoding signs. The [file info report](https://metadata.video/video-file-info) lists every field, and [where was this video taken](https://metadata.video/where-was-this-video-taken) shows any location on a map.

## Check 3: look and listen carefully

Generated video has improved fast, and the classic tells (extra fingers, melting faces) are much rarer than they were. Look for errors that come from the model not understanding the world:

* Objects that appear, vanish or change shape between frames, especially behind something that passes in front.
* Text on signs, clothing or screens that is garbled or changes as the camera moves.
* Physics that is slightly off: water, smoke, cloth or hair moving in a way that ignores wind and gravity.
* Reflections and shadows that do not match the scene, or that move independently.
* Lip movements that drift from the speech, voices with no room echo, or background sound that does not match the place.
* Shots that last a few seconds each, with cuts that hide where one generation ends and the next starts.

On this site, **Frames** shows a filmstrip and **Save frame** keeps a still as a PNG, which helps you study details and run a reverse image search. **Find scene changes** in **AI insights** marks the cuts. Those tools describe what is in the video; they do not detect AI and do not give a verdict.

## Check 4: the source and the story

1. Search for the clip’s key frames with a reverse image search to find earlier or longer versions.
2. Find the first account that posted it and look at its history: does it post original footage from that place, or a stream of viral clips?
3. Look for other angles of the same event, and for reporting by news organisations that verified it.
4. Ask the person who posted it for the original file. A camera original with consistent metadata, or a signed one, carries real weight.
5. Check whether the place, weather, time of day and people match what is known about the event.

This is slower than uploading a clip to a detector, but it is how professional verification teams work, and it is the one method that gets better, not worse, as generators improve.

### About “AI video detector” websites

Detector sites run a classifier over the pixels and return a percentage. They can be a useful extra signal, but their accuracy on new generators and on heavily compressed social media copies is rarely published in a way you can check, and real footage can score high. Never treat a percentage as a verdict, and be careful about uploading private videos to them.

## AI video checks: honest answers

### Can metadata prove a video is real?

No. Ordinary metadata can be edited by anyone, and a missing camera tag is normal after sharing. The closest thing to proof is a camera original with a valid Content Credentials signature from the camera maker, plus a trustworthy source.

### What does a C2PA “AI-generated” assertion mean?

The signer states the content was made by a generative AI model (`trainedAlgorithmicMedia`) or mixes AI elements into other material (`compositeWithTrainedAlgorithmicMedia`). Once the signature verifies, that is strong evidence about where the file came from.

### If a video has no metadata, is it AI?

No. Messaging apps and social platforms strip most metadata from every video, real or generated. No metadata means you need other checks, nothing more.

### Why do platforms label some videos as AI-generated?

Platforms such as TikTok and LinkedIn say they read Content Credentials attached by AI tools, and some also apply labels when creators disclose AI use or when the platform’s own AI effects were used. A label means one of those signals was found; no label means none was found.

### Can metadata.video detect AI-generated video?

It reads provenance data (Content Credentials, encoder and software tags) and explains it. It does not analyse pixels for AI, cannot read invisible watermarks such as SynthID, and does not verify signatures.

### Can someone remove AI labels from a video?

They can strip Content Credentials, which are metadata, and crop a visible logo. Invisible watermarks such as SynthID are built into the pixels and sound and are designed to survive that. A missing label is therefore not a clean bill of health.

### Is the video uploaded when I check it here?

No. The file is read in your browser and nothing is sent. Third-party verifiers and detector sites are separate services with their own terms, so check before you upload anything private to them.

## Related metadata guides

* [ Video metadata viewer See, explain, edit and remove everything a video or photo says about itself. ](https://metadata.video/)
* [ Content Credentials (C2PA) viewer Read a file’s C2PA manifest: claim generator, actions, AI assertions, ingredients and signer. ](https://metadata.video/content-credentials-viewer)
* [ Video forensics with metadata Dates, encoder tags, GOP and bitrate changes and C2PA history that reveal re-saving. ](https://metadata.video/video-forensics)
* [ Find where a video was taken Read a video’s GPS location and see it on a map, with altitude, accuracy and country. ](https://metadata.video/where-was-this-video-taken)
* [ Full video file info report A MediaInfo-style text report, JSON and box tree for any video, with hashes on request. ](https://metadata.video/video-file-info)
* [ Do apps remove video metadata? What Discord, WhatsApp, Instagram, Telegram and others say about stripping metadata, and how to test. ](https://metadata.video/do-apps-remove-video-metadata)
* [ What video metadata is Every family of video metadata explained, with links to check or change each one. ](https://metadata.video/what-is-video-metadata)