ZONN.ai Forensic Report

Case · E5ED45CC · 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 · 49/100

Analysed Specimen

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

Heads up — 3 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).

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 · 100/100

    SigLIP visual-language model probing semantic vs perceptual coherence.

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

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

Model Agreement

47%

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 80
▸ expand
SigLIP AI Detector
100
INA v2 (FLUX/MJ)
100
xRayon ConvNeXtV2
98
Bombek1 SigLIP+DINOv2
96
CommFor (4803 Generators)
36
Manipulation Map (IML-ViT)
50
Pixel & Frequency Forensics7 detectors · mean 41
▸ expand
Color Distribution
9
Error Level Analysis
15
Frequency Analysis
72
Pixel Analysis
35
Noise Pattern
58
Edge Consistency
44
Compression Quality
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
107.4 KB
Bytes / pixel
0.105

Frequency Analysis

Radial1.000
DCT0.742
Upsampling1.000
Cross-channel0.138
Power-law β
-3.08
Grid energy
0.387

Edge Consistency

CV 0.692
Cell 1: 1.2014Cell 2: 3.1318Cell 3: 1.8693Cell 4: 0.7681Cell 5: 8.8693Cell 6: 23.0019Cell 7: 19.4593Cell 8: 10.2254Cell 9: 16.8440Cell 10: 27.0407Cell 11: 24.5944Cell 12: 11.5837Cell 13: 27.6677Cell 14: 25.7637Cell 15: 16.4374Cell 16: 4.0687

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

Range: 0.768127.6677

Noise Fingerprint

Variance
113.12
Std deviation
10.64
Mean
-0.0
Spatial corr.
3.324
Mean Δ
1.56
σ
1.98
CV
1.273
Uniformity
-0.273

Provenance

Source Dossier

PlatformDirect upload
Author
Content Typeimage
Analyzed OnMay 16, 2026, 10:18 PM
Analyzed byAnonymous