ZONN.ai Forensic Report

Case · A3FE4BF6 · IMAGE

Analyzed byAnonymous
ZONN Analysis
0

Probably AI-generated

More signals lean toward AI generation than real, but some give weaker readings. Treat with caution.

Signal ConfidenceLimited · 44/100

Analysed Specimen

Original analysed image
Forensic suspicion heatmap
OriginalHeatmap
POS55/100
No flagged regions

Heads up — 4 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.

No metadata at all

AI evidence

The file has no EXIF, XMP, IPTC, or ICC metadata. This is common for social-media re-uploads and for many generator outputs — real camera files almost always carry an ICC profile.

Upsampling artifacts in the frequency domain

AI evidence

FFT analysis found strong upsampling patterns — a fingerprint of diffusion-model VAE decoders (latent → pixel-space upscale).

ML detectors see this image differently

Note

ML scores span a wide range (1–96). Different architectures read different feature spaces; the majority vote strengthens the consensus, but no single model is fully reliable here.

No ICC color profile

AI evidence

The image does not embed an ICC color profile. Real camera files almost always carry sRGB or Adobe RGB profiles — a missing profile is often a sign of generator output or re-encoded media.

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.

Why this verdict

  • SigLIP AI Detectorread real · 1/100

    SigLIP visual-language model probing semantic vs perceptual coherence.

  • INA v2 (FLUX/MJ)read real · 3/100

    BEiT-Large dual-head classifier trained on FLUX, Midjourney, and real photo corpora.

Model Agreement

34%

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 37
▸ expand
SigLIP AI Detector
1
INA v2 (FLUX/MJ)
3
xRayon ConvNeXtV2
96
CommFor (4803 Generators)
22
Bombek1 SigLIP+DINOv2
52
Manipulation Map (IML-ViT)
50
Pixel & Frequency Forensics7 detectors · mean 50
▸ expand
Frequency Analysis
70
Color Distribution
31
Error Level Analysis
34
Noise Pattern
66
Pixel Analysis
35
Edge Consistency
58
Compression Quality
55
Provenance & Metadata3 detectors · mean 54
▸ expand
ICC Profile
62
Metadata
50
C2PA Provenance
50

Image Quality

Dimensions
960 × 1720 px
Aspect
0.558
File size
3.33 MB
Bytes / pixel
2.116

Frequency Analysis

Radial1.000
DCT0.773
Upsampling1.000
Cross-channel0.034
Power-law β
-3.40
Grid energy
0.341

Edge Consistency

CV 0.346
Cell 1: 17.9453Cell 2: 16.2826Cell 3: 18.0209Cell 4: 10.2864Cell 5: 19.3750Cell 6: 14.7449Cell 7: 13.1216Cell 8: 5.4127Cell 9: 15.8727Cell 10: 16.6516Cell 11: 11.0461Cell 12: 5.9891Cell 13: 7.0453Cell 14: 7.7670Cell 15: 11.7763Cell 16: 11.5487

Per-region edge density (4 × 4 grid). Uneven distribution may indicate localized editing or splicing; uniform fields are typical of fully synthetic outputs.

Range: 5.412719.3750

Noise Fingerprint

Variance
82.01
Std deviation
9.06
Mean
-0.0
Spatial corr.
3.155
Mean Δ
1.63
σ
1.62
CV
0.989
Uniformity
0.011

Provenance

Source Dossier

PlatformDirect upload
Author
Content Typeimage
Analyzed OnMay 27, 2026, 10:44 PM
Analyzed byAnonymous