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Use This ToolWhat is AI Image Forensics?
Analyze images for signs of AI generation or digital manipulation using Error Level Analysis (ELA), Fast Fourier Transform (FFT), and noise pattern detection. Identify deepfakes, edited photos, and AI-generated content instantly in your browser.
Key Features
Error Level Analysis (ELA) to highlight inconsistent compression artifacts
Fast Fourier Transform (FFT) frequency analysis for grid patterns
Noise pattern analysis to detect sensor inconsistencies
EXIF metadata inspection for tampering clues
Clone detection to find copy-pasted regions
AI probability score with confidence meter
Side-by-side comparison view
100% browser-based — your images never leave your device
How It Works
1
Upload Image
Drop your image onto the tool or click to select a file. Supports JPEG, PNG, WebP, and TIFF up to 20 MB.
2
Multi-Layer Analysis
The tool simultaneously runs ELA compression analysis, FFT frequency decomposition, and statistical noise mapping across the image.
3
AI Scoring
Results from each analysis layer are combined into an overall authenticity score, flagging suspicious regions with visual overlays.
4
Review Results
Examine the detailed report with annotated heatmaps, metadata summary, and a plain-language explanation of each finding.
Who Is This For?
- ▸Fact-checkers verifying news photos before publication
- ▸Social media moderators identifying manipulated viral content
- ▸Legal teams authenticating evidence images
- ▸Journalists investigating potentially altered imagery
- ▸Researchers studying AI image generation artifacts
Why Use AI Image Forensics?
Unlike cloud-based alternatives that upload your files to remote servers, AI Image Forensics runs entirely in your browser. Your data stays private. No account, no subscription, no upload limits — just instant results. Built with cutting-edge web technologies including WebAssembly and WebGL for near-native performance.
Technical Details
Runs entirely in WebAssembly and WebGL. ELA is computed via canvas re-compression at quality 70 and pixel-difference amplification. FFT is implemented using a radix-2 Cooley-Tukey algorithm. No data is ever transmitted to a server.
Frequently Asked Questions
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