ZONN.ai Forensic Report
Case · 01A7CF0C · IMAGE
Probably real
More signals lean toward real than AI, but some give weaker readings. Worth a second look on close inspection.
Analysed Specimen
Heads up — 2 things to know
Why this analysis might be off
We highlight every disagreement and unusual signal we found so you can judge for yourself. Stronger warnings come first; informational notes are at the bottom.
Upsampling artifacts in the frequency domain
AI evidenceFFT analysis found strong upsampling patterns — a fingerprint of diffusion-model VAE decoders (latent → pixel-space upscale).
ML detectors see this image differently
NoteML scores span a wide range (6–97). Different architectures read different feature spaces; the majority vote strengthens the consensus, but no single model is fully reliable here.
Origin Check
Trace this image elsewhere
Cross-reference the source against major reverse-image services. Each link opens in a new tab with the image URL preloaded — ZONN.ai does not re-upload the image.
Google Lens
Yandex
TinEye
Bing VisualWhy this verdict
- xRayon ConvNeXtV2flagged AI · 97/100
ConvNeXtV2 detector trained on FLUX, DALL-E 3, SDXL, SD3.5, and Midjourney v6.
- SigLIP AI Detectorread real · 6/100
SigLIP visual-language model probing semantic vs perceptual coherence.
Model Agreement
Variance across 6 ML detectors. Higher agreement means the models converged on the same reading; lower agreement means treat the verdict with care.
Evidence — 16 detectors reviewed
What each detector saw
Each detector independently gave this imagea score from 0 (definitely real) to 100 (definitely AI). The score above is their weighted consensus — detectors with higher confidence count more. No single detector decides; you read the spread.
ML Models6 detectors · mean 36▸ expand▾ collapse
Pixel & Frequency Forensics7 detectors · mean 43▸ expand▾ collapse
Provenance & Metadata3 detectors · mean 54▸ expand▾ collapse
Image Quality
- Dimensions
- 895 × 960 px
- Aspect
- 0.932
- File size
- 173.2 KB
- Bytes / pixel
- 0.206
Frequency Analysis
Edge Consistency
Per-region edge density (4 × 4 grid). Uneven distribution may indicate localized editing or splicing; uniform fields are typical of fully synthetic outputs.
Range: 4.7482 – 30.6968
Noise Fingerprint
- Variance
- 139.63
- Std deviation
- 11.82
- Mean
- -0.0
- Spatial corr.
- 4.412
- Mean Δ
- 2.26
- σ
- 2.27
- CV
- 1.005
- Uniformity
- -0.005