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No single checker can prove that an image or video is real or fake. A reliable assessment combines the original file, provenance records such as C2PA Content Credentials, a watermark check matched to the suspected generator, source and reverse-image research, visual inspection, and independent confirmation of the event. A positive signal can show that a covered AI system created or edited some media; a negative result cannot certify camera capture or truthful context.
Use the workflow below to separate four different questions: whether AI was involved, whether the file was altered, whether the depicted event happened, and whether the caption or date is accurate.
What “authentic” means for an image or video
Authenticity is not a single yes-or-no property. A file can be an untouched camera original, an authentic photograph with a false caption, a real recording that was cropped or enhanced, an AI-assisted edit of a real scene, or a completely synthetic creation. AI involvement alone does not make a post false; a generated illustration may be honestly labeled, while a genuine disaster video can be misleading when attached to the wrong country or year.
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- Was an AI system involved? Watermarks and provenance records can sometimes answer this for supported systems.
- Has the file changed? Content Credentials and file history may document edits, but copies and social-media processing can remove that evidence.
- Did the depicted event occur? Only independent reporting, records, or additional footage can establish this.
- Is the caption correct? Date, location, identity, and sequence require source and context checks.
State conclusions narrowly. “A supported watermark was detected” is evidence of covered-tool use. It is not proof that every frame was generated, that the scene is fictional, or that the post is deceptive.
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The verification sequence
Work in this order. Each step preserves evidence for the next and reduces the chance that a re-encoded copy will mislead you.
1. Preserve the best available copy
Download the original file when possible. Prefer the file supplied by the camera, editor, journalist, creator, or platform upload rather than a screenshot, screen recording, messaging-app copy, or social-media preview. Keep the original unchanged and make a working copy for analysis. Record the filename, download time, account that posted it, post URL if available, and any caption exactly as shown.
Copying, converting, trimming, recompressing, or taking a screenshot can remove metadata and weaken or destroy watermark signals. If you only have a screenshot or preview, say so in your notes; a missing credential in that copy is not evidence that the source never had one.
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2. Inspect provenance and Content Credentials
Look for a Content Credentials or C2PA indicator in the file viewer, publishing platform, or a compatible verification page. A valid manifest may identify a signer, the originating device or application, and a sequence of edits, including AI operations. Check the signer identity, the manifest’s validation status, and whether the file format and product appear on the verifier’s supported list.
A valid history can show that a particular workflow produced the file, but it does not certify that the scene or caption is truthful. An invalid, unsupported, or missing manifest is inconclusive. Google’s documentation notes that compatible Content Credentials version 2.2 and later are supported from products on its conforming list; other files may not be recognized. OpenAI also warns that ordinary handling can remove metadata.
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3. Use a watermark checker that covers the suspected system
Invisible watermarks are intentionally narrow signals. Use the service associated with the tool family you are investigating, and read exactly what a positive or negative result means. Google’s SynthID tools look for supported Google or partner watermarks; OpenAI’s checker looks for OpenAI-associated provenance signals and supported C2PA metadata. Neither is a universal detector for every model.
For Google Gemini, upload supported media and ask, “Was this image/video/audio created or edited by Google AI?” Gemini currently recognizes content created by Google AI tools and can report portions of a video where a watermark was detected. The stated rolling allowance is approximately 10 image checks, 10 video checks totaling up to five minutes, and 10 audio checks totaling up to three hours per 24 hours. Limits and supported formats can change.
Google DeepMind said on October 7, 2026 that its public SynthID Detector was expanding globally in English for images, video, and audio made with Google or partner AI. The announcement named OpenAI, NVIDIA, and Kakao as partners and said Apple support was planned. Google reported more than 180 billion watermarked images and videos and 240,000 years of watermarked audio, plus more than one million daily verification requests across Search, Gemini, and Chrome. These are company-reported scale figures, not independent accuracy measurements, and they do not imply coverage of every generator.
OpenAI Verify is a public checker for images and audio that looks for supported C2PA metadata and SynthID signals associated with OpenAI tools. OpenAI says submitted files are processed for signal checking and are not stored unless legally required or used to train its models. Its supported formats and functions should be confirmed on the live service. The OpenAI Content Provenance API similarly checks supported image and audio signals; a not_detected response does not rule out OpenAI use or generation by another system. The API is explicitly not a general-purpose detector.
4. Search for the source and context
Run a reverse-image search using the highest-resolution frame or still you can obtain. Try a full image and distinctive crops (a sign, building, uniform, or landscape). Record the earliest credible appearance, not merely the first result returned. Compare publication dates, account history, captions, weather, landmarks, and the claimed location.
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For video, extract several representative frames: opening, middle, ending, and any frame containing text or a landmark. Search those frames separately and look for longer or earlier uploads. A match can reveal an old event, a different country, or an edited excerpt. No search result is an authenticity certificate; search indexes are incomplete and synthetic media may be newly generated.
5. Inspect visual details as clues
Zoom in, but treat anomalies as prompts for further checking rather than proof. Google identifies common warning signs such as garbled or inconsistent text, errors in small details (including hands, teeth, and background objects), contradictory shadows or lighting, and unnatural repetition of people or patterns.
Compression, resizing, motion blur, low light, rolling-shutter effects, and ordinary post-processing can create similar defects. Conversely, modern generators can produce convincing details. Note the exact frame and feature that raised suspicion, then seek provenance or independent confirmation instead of assigning a probability from appearance alone.
6. Corroborate consequential claims independently
When the post could affect safety, elections, markets, reputations, or emergency decisions, verify the event itself. Seek independent footage from an unrelated source, contemporaneous reporting, public records, weather or transport data, and statements from identifiable organizations. Check whether the claimed location had the reported conditions and whether the timeline is physically plausible.
Ofcom’s Deepfake Defences 2: The Attribution Toolkit describes visible labels, invisible watermarks, provenance metadata, and contextual annotations as complementary systems. Its discussion paper is not formal regulatory guidance. Attribution helps explain where media came from; it does not replace ordinary fact-checking.
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How to interpret each result
| Result | What it supports | What it does not establish | Next action |
|---|---|---|---|
| Supported watermark detected | Some or all checked media was created or edited by the covered system. Google states that a detected SynthID watermark means all or part of the image or video was created or edited by Google’s AI models. | That the whole file is synthetic, that the depicted event is false, or that the caption is accurate. | Inspect provenance and verify the event and context independently. |
| No watermark detected | The service found no signal it supports in the submitted copy. | Camera capture, human authorship, or truth. | Check other generator families, the original file, credentials, and source history. |
| Valid Content Credentials | A signed history linking the file to a creator, tool, device, or edit sequence, subject to the manifest’s scope. | That the scene happened as shown or that every edit is documented. | Read the signer, actions, timestamps, and validation state; corroborate the claim. |
| Missing, invalid, or unsupported credentials | Nothing definitive about origin. | That metadata was never present or that the file is synthetic. | Compare with an original and account for conversion, stripping, or unsupported formats. |
| Visual anomaly | A reason to investigate a particular region or frame. | Reliable proof of generation. | Seek provenance, source matches, and independent evidence. |
| Conflicting tool results | Only that the tools have different coverage or the file has mixed history. | A forced real/fake verdict. | Preserve copies, document each tool’s coverage, and report the uncertainty. |
The safest wording mirrors the evidence: “The checker detected a supported signal,” “No supported signal was found in this copy,” or “The origin remains unverified.” Avoid converting any of those statements into “real” or “fake.”
Choosing between available checkers
Compare services by coverage and evidence, not by claims of universal detection.
| Comparison question | Why it matters |
|---|---|
| Which model or watermark families are covered? | A tool can miss media made by an unrelated generator or an older model. |
| Which file types, codecs, and credential versions are accepted? | An unsupported upload can produce a meaningless negative result. |
| Does it inspect pixels, signed metadata, or both? | Pixel watermarks and provenance manifests survive different transformations. |
| Does it show validation state and edit history? | A signer and sequence are more informative than an unexplained badge. |
| How are uploads handled and how are limits applied? | Check retention, training use, privacy terms, file-size limits, and quotas before uploading sensitive material. |
| Can it inspect the relevant video portions? | A report about one segment may not describe every frame or soundtrack. |
Google’s and OpenAI’s services answer different, overlapping questions. A negative result from one should not be treated as a negative result from the other, and neither should be presented as a verdict on all AI systems.
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Sample more than one frame
Watermarks and artifacts can vary across a clip. Save frames from multiple timestamps, including transitions and overlays. Gemini may report portions where a watermark was detected; Google cautions that this does not mean every frame in the indicated portion contains the signal.
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Listen for abrupt changes in room tone, repeated phonemes, unnatural breaths, and lip movement that drifts from speech. These are clues only. If the service supports audio provenance, submit the original audio track rather than a screen-recorded soundtrack and record whether the result covers the audio, video, or both.
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Separate edits from fabrication
Slow motion, stabilization, color grading, subtitles, cuts, and object removal may be ordinary editing or AI-assisted work. Identify which portion is documented or detected instead of labeling the entire video. Compare the earliest upload with later versions to find inserted frames or a changed soundtrack.
Common failure modes and recovery
- Only a screenshot is available: request the original download or an uncompressed export; do not infer authenticity from absent metadata.
- The checker says “not detected”: verify format and coverage, try the relevant companion service, and continue with source research.
- A credential is invalid: preserve the file, inspect the signer and manifest details, and compare with a known original. Invalid signing is not proof of fabrication.
- A social platform changed the file: locate the earliest upload and ask the uploader for the camera or editing original.
- Search finds an older, similar image: compare distinctive details, dates, weather, and cropping; similarity alone does not prove reuse.
- Tools disagree: document the exact file, timestamp, service, and response. Mixed real and synthetic media or degraded signals can produce disagreement.
- The claim is urgent or dangerous: pause sharing, preserve evidence, and contact a qualified newsroom, emergency authority, or platform trust-and-safety channel rather than relying on a visual guess.
A compact decision procedure
- Save the highest-quality original and a hash or other record of the file you examined.
- Note the post, account, caption, claimed date, location, and event.
- Check C2PA Content Credentials and read validation and edit history.
- Run the watermark checker that matches the suspected tool family, recording coverage and limits.
- Extract video frames and run reverse-image searches on distinctive views.
- Inspect text, anatomy, lighting, reflections, repetition, audio, and synchronization as clues.
- Corroborate the event with independent sources and contemporaneous records.
- Publish only a scoped conclusion, such as “supported AI-edit signal detected,” “source context is false,” or “origin remains unverified.”
Privacy and evidence handling
Do not upload confidential documents, unreleased footage, biometric material, or personally identifying media to a service without checking its current terms. Keep an untouched local copy, work from duplicates, and record each transformation. When sharing a finding, include the file version and the precise result rather than distributing private originals. Service availability, partner coverage, quotas, and retention policies can change, so check the provider’s current help page at the time of use.
What a responsible conclusion looks like
Use calibrated language. A strong conclusion might say: “The submitted file contains a valid provenance record naming the creator and an AI edit, but the record does not establish that the captioned event occurred.” Another might say: “No supported watermark was detected in this re-encoded copy; because the service does not cover every generator and metadata may have been stripped, the origin is undetermined.” If independent reporting shows the scene occurred elsewhere, say that the media is authentic but miscaptioned rather than calling it AI-generated.
Attribution systems are improving, but interoperability, access restrictions, editing, and signal removal remain practical limits. The most defensible assessment combines technical signals with ordinary source criticism and independent evidence.
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