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Browser-Private · No Upload Required
Detect Fake Images.
Before They Fool You.
AI deepfake detection · Invoice fraud analysis · EXIF forensics — all processed locally in your browser first.
AI Deepfakes Invoice Fraud Metadata Forensics Hash Verification ELA Analysis
100% Client-Side TF.js Neural Optional AWS AI No Image Upload
Drop your image here, or click to browse
JPG · PNG · WEBP · HEIC · max 10 MB · never leaves your browser
Upload
Local Scan
Cloud AI
Run Cloud AI Analysis
AWS deepfake detection & invoice fraud analysis — optional, privacy-conscious
File Privacy: Your image is sent to AWS (Rekognition / Textract) over HTTPS. It is processed ephemerally — not stored, not logged, not retained after the analysis completes. We have no copy of your file.
How it works: AWS Rekognition (label + moderation detection) · TF.js texture analysis (Laplacian/Sobel) · EXIF cross-referencing. Signals are advisory — correlation ~80–85% on synthetic face datasets. Not forensic evidence.
Free to use · 5 cloud scans/hour · WAF rate-limited · images processed ephemerally
5 scans/hour as guest. for 25/hour or upgrade to Plus for 50/hour.
Frequently Asked Questions
Is my image sent to an external server for forensic analysis?
No. All forensic analysis — including metadata extraction, Error Level Analysis (ELA), and manipulation detection — runs entirely in your browser. Your images are never uploaded to our servers or any third-party service.
What does the Image Forensic Analyzer detect?
The tool performs several independent checks: EXIF metadata inspection (camera model, GPS coordinates, editing software), Error Level Analysis to highlight regions with inconsistent JPEG compression (a common indicator of compositing or local edits), and visual artifact inspection to spot copy-move manipulation.
What is Error Level Analysis (ELA) and how does it work?
Error Level Analysis re-compresses an image at a known JPEG quality level and computes the pixel-by-pixel difference between the original and re-compressed versions. Areas that have been digitally inserted or edited typically retain a different compression level than the unmodified background, appearing as brighter regions in the ELA visualisation.
Error Level Analysis (ELA)
ELA detects image manipulation by re-compressing a JPEG at a known quality level and comparing it to the original. Authentic images show uniform error levels across similar surface types. Edited regions typically show different compression artifacts and appear brighter in the ELA visualization, indicating they were saved at a different compression level — a sign of manipulation.
EXIF Metadata Analysis
EXIF data is embedded in JPEG and TIFF files by cameras and phones. It contains: camera model, GPS coordinates, date/time, lens settings, and software used. Removed or inconsistent EXIF data (e.g., no GPS on an outdoor photo, or editing software tags) can indicate the image has been processed. Entirely missing EXIF is common in screenshots or web-downloaded images.
AI Authenticity Detection
The AI model analyzes pixel-level patterns, lighting consistency, shadow geometry, face symmetry, and texture coherence. AI-generated images (deepfakes, GAN outputs, diffusion models) often show subtle artifacts in hair, teeth, backgrounds, and reflections that the model has been trained to detect.
Interpreting Results
No single indicator is definitive. A high ELA anomaly score with inconsistent EXIF and low AI authenticity together strongly suggest manipulation. But high ELA can also occur with legitimate heavy re-editing for artistic purposes. Treat the analysis as probabilistic evidence, not forensic proof. Always corroborate with other signals and context.