ZONN.ai Forensic Report

Case · 9D44B8A4 · IMAGE

Analyzed byAnonymous
ZONN Analysis
0

Inconclusive

Signals are mixed or weak. We can't tell with confidence — context, source, and your own judgement matter here.

Signal ConfidenceLimited · 46/100

Analysed Specimen

Original analysed image
Forensic suspicion heatmap
OriginalHeatmap
POS55/100
No flagged regions
Camera
Redmi 13

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.

ML detectors disagree with each other

Note

2 models confidently say "AI" (Ml Python Siglip, Xrayon Convnext) while 2 confidently say "real" (Ml Commfor, Itsnotai V2). This image sits at the edge of what ML can decide — manual review is recommended.

Just above the real threshold

Note

The score (42/100) is between real (40) and inconclusive. There is not enough confidence to call this a clean "real" verdict.

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 (0–96). 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.

Why this verdict

  • CommFor (4803 Generators)read real · 0/100

    CommFor detector trained across 4,803 generator variants for broad coverage.

  • INA v2 (FLUX/MJ)read real · 3/100

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

Model Agreement

29%

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 44
▸ expand
CommFor (4803 Generators)
0
INA v2 (FLUX/MJ)
3
xRayon ConvNeXtV2
96
SigLIP AI Detector
78
Bombek1 SigLIP+DINOv2
39
Manipulation Map (IML-ViT)
50
Pixel & Frequency Forensics7 detectors · mean 48
▸ expand
Color Distribution
22
Noise Pattern
75
Error Level Analysis
28
Frequency Analysis
70
Pixel Analysis
45
Edge Consistency
47
Compression Quality
48
Provenance & Metadata3 detectors · mean 54
▸ expand
ICC Profile
62
Metadata
50
C2PA Provenance
50

Image Quality

Dimensions
3000 × 4000 px
Aspect
0.750
File size
3.13 MB
Bytes / pixel
0.273

Frequency Analysis

Radial1.000
DCT0.803
Upsampling1.000
Cross-channel0.015
Power-law β
-3.19
Grid energy
0.295

Edge Consistency

CV 0.587
Cell 1: 3.4129Cell 2: 2.8299Cell 3: 2.6904Cell 4: 3.0788Cell 5: 12.9759Cell 6: 8.0540Cell 7: 9.2974Cell 8: 16.6039Cell 9: 20.0986Cell 10: 20.0987Cell 11: 9.6171Cell 12: 10.8015Cell 13: 8.8724Cell 14: 20.6495Cell 15: 21.8232Cell 16: 8.4009

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

Range: 2.690421.8232

Noise Fingerprint

Variance
56.06
Std deviation
7.49
Mean
-0.0
Spatial corr.
2.622
Mean Δ
1.54
σ
1.65
CV
1.075
Uniformity
-0.075

Provenance

Source Dossier

PlatformDirect upload
Author
Content Typeimage
Analyzed OnMay 15, 2026, 8:19 AM
Analyzed byAnonymous