Forensics Toolset

ELA re-saves the image as JPEG and measures per-pixel differences. Areas that were edited or composited often show higher error levels than undisturbed regions.

Does not indicate editing: Text, sharp edges, highly-textured regions (fabric, foliage), and repeated saves at the same quality all produce high ELA values naturally.

ELA is one indicator among many and should never be used in isolation.

Identifies copy-move forgery by finding visually similar regions at different positions. Matched blocks are highlighted with colour-coded overlays.

Limitations: Smooth areas (sky, walls, solid colours) may produce false positives at higher sensitivity. Does not detect AI inpainting or content-aware fill. Start with Low sensitivity.

Re-encodes the image through the browser canvas, which strips all embedded metadata. Optionally re-injects a limited set of fields after stripping.

Compiles findings from all completed analyses into a printable document. Use your browser's Print → Save as PDF to export.

Disclaimer: This is an automated analysis to assist human review. Findings are indicators only and must be interpreted by a qualified analyst.