Is This Photo AI Generated?

Upload any image to check for AI generation signals. Our detector analyzes metadata, compression patterns, and visual artifacts to estimate probability.

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What we check

AI-generated images have distinctive fingerprints: missing camera EXIF (no aperture, ISO, focal length), unusual resolution patterns that don't match any real camera, software metadata pointing to generation tools, and compression characteristics different from real photographs. Our detector scores each signal and gives you an overall probability. For the full breakdown, see our AI detection guide.

When to use this

Verify profile pictures on dating apps and social media. Check news images for AI manipulation. Evaluate content authenticity for journalism. Screen submissions in photography contests. Detect AI art being sold as original work. Combine with the Authenticity Checker and stock photo detection for a complete verification workflow.

Multi-Signal

Reads metadata, software tags and C2PA credentials, then the pixels themselves.

A Verdict, Not a Guess

Says AI, real, or unknown — and shows the evidence behind it. Stripped metadata is never counted against a photo.

Privacy Focused

Metadata extracted server-side, auto-deleted within 1 hour. Scoring runs in your browser.

How AI image detection works

AI generators like DALL-E, Midjourney, and Stable Diffusion produce images that look convincing to the human eye — but they leave traces in the file itself. Our detector examines multiple signals: metadata patterns (AI tools often embed specific software tags or lack standard camera EXIF fields entirely), compression signatures unique to generation pipelines, and statistical anomalies in pixel noise that differ from real camera sensor output. No single signal is conclusive — the tool combines them into a probability estimate. Detection is harder when images have been resized, re-saved, or passed through social media compression. For a deeper dive into the techniques, see our guide on how to detect AI-generated images, or open the full AI Image Detector for the complete signal-by-signal breakdown. If you also need to verify whether a photo has been manually edited, try the Photo Authenticity Checker.

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How it works

How AI detection works

Scanly analyzes metadata fingerprints that distinguish real camera photos from AI-generated images. Genuine photos carry EXIF data — camera model, lens info, shutter speed, GPS coordinates — while AI outputs from Midjourney, DALL·E, and Stable Diffusion typically lack these fields or contain telltale software signatures. The tool also checks image resolution against known camera sensor dimensions and examines compression patterns that differ between rendered and photographed images. Each signal is combined into an overall probability score.

Common use cases

Verify profile photos on dating apps and social media platforms where fake AI-generated profiles are increasingly common. Screen user-submitted images in journalism and legal contexts where image provenance matters. Check photography contest entries for AI-generated submissions that violate competition rules. Review stock photography submissions to ensure images are genuine captures rather than generated outputs.

Visual clues to look for

Beyond metadata, AI-generated images often have visual tells: inconsistent reflections in eyes, unusual hand anatomy, text that doesn't read correctly, repeating patterns in backgrounds, and asymmetric accessories like earrings or glasses. Combining Scanly's metadata analysis with your own visual inspection gives the best results. Our AI detection guide covers these visual techniques in detail with example images. The more signals you check, the higher your confidence in the result.

Limitations to know

Images downloaded from social media often have metadata stripped, which reduces the signals available for detection. Screenshots of AI images lose generation tool signatures. Re-saved or edited AI images may pick up new software tags that complicate analysis. For the most accurate results, use original files when possible. If confidence is medium, cross-check with the Authenticity Checker and the Screenshot Scanner. No single tool catches every AI generator, so layering multiple checks gives the most reliable assessment.

The question "is this photo real?" has become one of the most common digital literacy challenges. AI-generated images — including deepfake portraits, synthetic landscapes, and artificial product photos — have reached a level where casual viewers can't distinguish them from real photographs, making automated detection tools essential for trust and verification. Scanly's metadata-based approach complements pixel-analysis tools by catching different types of signals — no single method catches everything, but combining metadata forensics with visual inspection covers the widest range of AI generators and post-processing scenarios. For the full AI detection toolkit, start with the AI Image Detector, read the detection guide for manual techniques, and visit the photo forensics hub for a broader verification framework. See also the AI generation check page for generator-specific details.

Frequently Asked Questions

How accurate is the AI detection?

No AI detection is 100% accurate, and any tool claiming otherwise is selling you something. The metadata signals are certain when they are present (a Midjourney software tag is a Midjourney software tag) but absent on most images. The pixel-level Deep Check reads the image itself and returns a confidence figure with the specific reasons behind it; when the evidence is thin it says "uncertain" rather than guess, because wrongly calling a real photograph AI-generated is the worst error a detector can make.

Can you detect an AI image with no metadata?

Yes — that is what the Deep Check is for. It ignores metadata entirely and examines the pixels: diffusion artefacts, impossible or melted geometry, garbled text and signage, wrong finger and limb counts, physically inconsistent light and shadow, waxy skin, and the absence of real optical noise such as sensor grain and lens blur.

Does it work on a screenshot from Instagram, X or WhatsApp?

Yes. Every platform strips EXIF metadata on upload, and a screenshot never had any to begin with — which is why metadata-only checkers return "no signals found" on exactly the images people most want to check. Run the Deep Check on the screenshot; it reads the pixels, not the file header.

Which AI generators can be detected?

Midjourney, DALL-E, Stable Diffusion, Adobe Firefly, Flux, Leonardo and other popular generators. Where the file still carries metadata, the generator is often named outright in a software tag. Where it does not, the Deep Check judges the pixels and offers its closest generator match alongside the verdict.

Is my image stored?

No. The metadata analysis runs on our server and the upload is auto-deleted within an hour. If you run the Deep Check, a downscaled copy of the image is sent to our AI processing provider for that single request and is not retained by us. Nothing is kept long-term, shared, or used to train anything.

Can AI detection be fooled?

Metadata can be wiped or forged in seconds, so metadata alone is easy to defeat. Pixel-level detection is harder to fool but not impossible: heavy compression, small images, and aggressive re-editing all erase the evidence. Treat the verdict as evidence, not proof, and combine it with the ELA Scanner, FFT Spectrum and Noise Analysis when the answer matters.

How do I check if an image is AI-generated?

Upload it. The checker first reads what the file declares about itself — camera data, software tags, C2PA Content Credentials. If a generator named itself, you have your answer immediately. If the metadata is gone, that is not held against the image: the checker says so and stops, because a stripped file proves nothing. Then run the Deep Check, which analyses the pixels themselves and returns a verdict, a confidence figure, and the specific visible reasons.

Is this a free AI photo checker?

The metadata analysis is free, unlimited, and needs no signup. The pixel-level Deep Check runs a vision model, which costs us money per image, so each one costs a single credit. No subscription, no watermark on the answer.

What if an AI image has been re-saved or screenshotted?

Re-saving and screenshotting destroy metadata, so the metadata signals go quiet — that is expected, not a clean result. The Deep Check is the answer for these files: it works from the pixels, so a screenshot is a perfectly valid input. Very heavy compression or a very small image will still weaken any verdict.

Can it detect AI-enhanced or partially edited photos?

Partly. The Deep Check is strongest on fully AI-generated images; a real photo with an AI-retouched sky or a removed object may not trigger them. For localised edits, use the ELA Scanner, Clone Detection and Noise Analysis, which look for inconsistencies between regions rather than judging the image as a whole.

Why does it say "no answer" instead of giving me a percentage?

Because a percentage built from missing metadata is a lie with a decimal point. Every social platform strips EXIF, so "no camera data" describes the upload pipeline, not the image — a holiday snap from WhatsApp and a Midjourney render look identical to a metadata reader. Rather than invent a number, the checker tells you what the file does and does not prove, and sends you to the Deep Check, which reads the pixels. When the Deep Check does call an image AI-generated, that verdict is re-run on independent passes and only survives if they agree.

Is this an AI art detector for contest submissions?

It can screen contest entries: run the Deep Check on each submission and read the listed reasons, not just the verdict. For strongest confidence, combine it with FFT Spectrum analysis, which reveals frequency-domain GAN artifacts invisible to the eye. Never disqualify anyone on a single automated verdict.

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