ZONN.ai Forensic Report

Case · 9E79FD6E · IMAGE

Analyzed byAnonymous
ZONN Analysis
0

Very likely AI-generated

Most signals point to AI generation. Detection tools are not perfect — treat this as a strong indication, not a verdict.

Signal ConfidenceLimited · 50/100

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 (15–99). 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 Detectorflagged AI · 99/100

    SigLIP visual-language model probing semantic vs perceptual coherence.

  • INA v2 (FLUX/MJ)flagged AI · 97/100

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

Model Agreement

38%

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 73
▸ expand
SigLIP AI Detector
99
INA v2 (FLUX/MJ)
97
xRayon ConvNeXtV2
95
CommFor (4803 Generators)
15
Bombek1 SigLIP+DINOv2
84
Manipulation Map (IML-ViT)
50
Pixel & Frequency Forensics7 detectors · mean 49
▸ expand
Color Distribution
11
Noise Pattern
85
Error Level Analysis
21
Frequency Analysis
79
Pixel Analysis
35
Compression Quality
58
Edge Consistency
53
Provenance & Metadata3 detectors · mean 54
▸ expand
ICC Profile
62
Metadata
50
C2PA Provenance
50

Image Quality

AI-typical dimensions
Dimensions
1024 × 1024 px
Aspect
1.000
File size
1.40 MB
Bytes / pixel
1.396

Frequency Analysis

Radial1.000
DCT0.863
Upsampling1.000
Cross-channel0.315
Power-law β
-3.65
Grid energy
0.205

Edge Consistency

CV 0.437
Cell 1: 7.4454Cell 2: 5.7957Cell 3: 5.6516Cell 4: 4.7000Cell 5: 6.9679Cell 6: 2.2114Cell 7: 2.1765Cell 8: 4.6400Cell 9: 8.7025Cell 10: 1.7656Cell 11: 1.7977Cell 12: 7.9528Cell 13: 7.4678Cell 14: 8.5468Cell 15: 9.1011Cell 16: 7.4965

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

Range: 1.76569.1011

Noise Fingerprint

Variance
37.24
Std deviation
6.10
Mean
0.0
Spatial corr.
1.334
Mean Δ
1.68
σ
1.98
CV
1.181
Uniformity
-0.181

Provenance

Source Dossier

PlatformDirect upload
Author
Content Typeimage
Analyzed OnMay 16, 2026, 10:12 PM
Analyzed byAnonymous