ZONN.ai Forensic Report

Case · 9B94718F · 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 ConfidenceWeak · 30/100

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.

Multiple detectors unreachable

Note

2 ML detectors did not respond (Ml Python Siglip, Ml Commfor). The verdict was computed with reduced evidence; reliability is lower than usual.

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).

Weak overall confidence

Note

Aggregate verdict confidence is 30/100. Several detectors returned uncertain answers or were offline. Read the verdict as a guideline, not as a final answer.

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

  • Noise Patternflagged AI · 91/100

    Sensor-noise (PRNU) fingerprint check. Real cameras leave camera-unique noise.

  • Pixel Analysisread real · 17/100

    Low-level pixel statistics: saturation cliffs, channel histograms, banding.

Model Agreement

100%

Variance across 3 ML detectors. Higher agreement means the models converged on the same reading; lower agreement means treat the verdict with care.

Evidence — 13 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 Models3 detectors · mean 50
▸ expand
Manipulation Map (IML-ViT)
50
SigLIP AI Detector
50
CommFor (4803 Generators)
50
Pixel & Frequency Forensics7 detectors · mean 51
▸ expand
Noise Pattern
91
Pixel Analysis
17
Frequency Analysis
72
Error Level Analysis
31
Color Distribution
32
Compression Quality
65
Edge Consistency
48
Provenance & Metadata3 detectors · mean 54
▸ expand
ICC Profile
62
Metadata
50
C2PA Provenance
50

Image Quality

Dimensions
460 × 460 px
Aspect
1.000
File size
820.2 KB
Bytes / pixel
3.969

Frequency Analysis

Radial1.000
DCT0.854
Upsampling1.000
Cross-channel0.026
Power-law β
-3.63
Grid energy
0.218

Edge Consistency

CV 0.548
Cell 1: 3.1256Cell 2: 6.4706Cell 3: 3.3009Cell 4: 2.1862Cell 5: 7.9456Cell 6: 9.8389Cell 7: 6.8141Cell 8: 2.2625Cell 9: 3.3593Cell 10: 11.2357Cell 11: 6.6514Cell 12: 1.8163Cell 13: 2.9158Cell 14: 10.5998Cell 15: 8.1420Cell 16: 3.8391

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

Range: 1.816311.2357

Noise Fingerprint

Variance
16.11
Std deviation
4.01
Mean
-0.0
Spatial corr.
1.280
Mean Δ
1.19
σ
1.24
CV
1.040
Uniformity
-0.040

Provenance

Source Dossier

PlatformDirect upload
Author
Content Typeimage
Analyzed OnMay 11, 2026, 9:00 PM
Analyzed byAnonymous