AI Art Detector
Check whether an illustration, drawing or digital painting was made by a human or generated by AI. FakeSec runs 12 independent forensic methods — including three neural networks trained on 240,000 images — and shows you exactly which signals fired.
What gives AI art away
Generated artwork fails in places a human artist never would. These are the signals our analyzers weight most heavily on illustrations and paintings:
Signature that isn't a signature
Diffusion models learned that paintings have a signature in the corner, so they draw a smudge that looks like handwriting but spells nothing. One of the single strongest tells in AI art.
Brushwork with no direction
A human builds a stroke with pressure and direction. Generated texture is statistically uniform — our texture analyzer measures stroke coherence across the canvas and flags art where it stays flat.
Anatomy that drifts
Hands, ears, jewellery and teeth are where generators still fail: six fingers, an earring on one side only, a bracelet that merges into the wrist.
Detail that doesn't decay
In real art, detail drops off away from the focal point. AI keeps the same density everywhere, which shows up clearly in a frequency (FFT) analysis.
Broken background logic
Architecture that doesn't line up, patterns that shift mid-repeat, text on signs that dissolves into letter-like shapes.
Too-clean colour statistics
Scanned and photographed art carries sensor noise and colour drift. Generated images have an unnaturally tidy colour distribution — measurable, not a guess.
How the analysis works
Upload the original file
Full resolution, straight from the source. Screenshots and re-saved copies destroy most of the evidence we measure.
12 independent methods run in parallel
Three neural networks look at the image as a whole. Nine forensic methods examine it as a signal: frequency (FFT) analysis, noise pattern, pixel-level statistics, EXIF metadata, Error Level Analysis, texture coherence, colour distribution, Benford's Law and edge detection.
You see the breakdown, not just a number
Every method reports separately, so you can tell whether the verdict rests on one weak signal or on nine that agree.
How much each method counts
Most detectors give you one number from one model. We run twelve independent analyzers and weight them — three neural networks carry the majority, but nine forensic methods examine the file as a signal and can overrule them. Here is the exact weighting we use in production:
| Method | Weight in final score |
|---|---|
| Neural network #2 | 25% |
| Neural network #1 | 15% |
| Neural network #3 | 15% |
| EXIF metadata | 10% |
| Frequency (FFT) | 6% |
| Benford's Law | 6% |
| Noise pattern | 5% |
| Error Level Analysis | 4% |
| Texture coherence | 4% |
| Edge detection | 4% |
| Pixel statistics | 3% |
| Colour distribution | 3% |
What people actually upload
These are our own numbers, not an industry estimate — every check run through FakeSec since launch. The split is closer than most people expect: roughly four in ten uploads really do turn out to be generated.
Who checks AI art
- Commission clients — You paid for original illustration and want to be sure you didn't receive a generated image.
- Art platforms & contests — Many galleries and competitions now ban or require disclosure of AI entries.
- Buyers on marketplaces — Prints and digital assets sold as hand-made.
- Artists protecting a portfolio — Proving your own work is human-made when accused of using AI.
Accuracy — and where it breaks down
On our internal benchmark of 240,000 images (120,000 AI-generated, 120,000 real) the combined score reaches up to 98% on unedited, full-resolution files. That number drops, sometimes sharply, in four situations — and you should know them before trusting any result:
- Heavy compression. Social platforms re-encode everything. A photo pulled from Instagram has already lost much of its noise signature.
- Screenshots. A screenshot is a new image of an image. Original metadata and compression history are gone.
- Stylised content. Flat colour and clean lines remove the texture and noise evidence forensic methods depend on.
- Post-processing. Added grain, filters, upscaling and manual retouching all mask generation traces.
No detector on the market is 100% accurate — ours included. Treat a high score as strong evidence, not as proof. When a decision matters, look at which of the 12 methods agreed.
Frequently asked questions
Related tools
Check your first image now
Create a free account and get 3 checks. Full breakdown across all 12 methods, no card required.