Photo Authenticity Checker

This edited image checker examines four categories of evidence. EXIF consistency — do metadata fields contradict each other (for example, a camera model that doesn't match the reported resolution)? Software traces — the photoshop checker detects whether the file was opened or saved by editing tools like Photoshop, Lightroom, or GIMP. Timestamp logic — do creation and modification dates follow a realistic sequence? Compression patterns — has the image been re-saved multiple times, suggesting intermediate edits? Results highlight specific findings rather than a simple yes-or-no verdict.

Start here for a quick assessment, then drill deeper with related tools. Use the EXIF Checker to inspect raw metadata fields. If you suspect the image was made by an AI generator rather than edited, run the AI Image Detector to check for AI-generation signals. Generate a SHA-256 hash to prove file integrity and detect any byte-level changes. For visual tampering, run the Similarity Scanner to compare a suspect image against a known original and pinpoint altered regions.

Journalists verifying user-submitted photos before publication. Insurance adjusters using a photo edit checker to review claim images for signs of manipulation. Legal teams preparing photographic evidence for court. HR departments screening submitted documents and ID photos. Marketplace moderators filtering doctored product images. Anyone receiving a photo and asking "is this image edited?" before trusting its contents. The tool is particularly valuable when the stakes are high — financial claims, published reporting, or evidence documentation.

Traditional approaches to detect edited photos involve pixel-level forensics — error level analysis, noise pattern checks — which require specialized software and expertise. If you're wondering how to tell if a photo was photoshopped, Scanly's Authenticity Checker focuses on metadata-level signals that are faster to analyze and easier to interpret. The tradeoff: metadata checks catch editing software traces and timeline inconsistencies, but won't detect pixel-level cloning or inpainting. For maximum coverage, pair metadata analysis with visual inspection techniques from the edited photo detection guide.

Different edits leave different fingerprints, so the fake photo checker cross-references several signals. A full re-save in Photoshop or Lightroom usually writes a software tag and re-compresses the whole frame. Splicing or compositing — dropping one photo into another — tends to break noise uniformity and error-level consistency at the seams. Object removal and content-aware fill disturb local compression and cloning patterns. A modified-after-capture edit shows up as a timestamp that sits later than the original creation date. Screenshots and re-exports strip the camera EXIF block entirely, which is itself a signal. No single flag proves manipulation; the verdict weighs how many independent checks agree.

The score is a summary of eight checks, not a lie-detector reading. A high score means the signals are consistent with an unaltered file — original camera metadata, no editing tags, timelines that line up. A low score means one or more checks disagree and the specific findings are worth reading. The key nuance: editing is not the same as faking. A cropped, colour-corrected, or exported photo can score low simply because it passed through software, even though nothing deceptive happened. Treat the score as a prompt to look closer, and lean on confidence — how many signals agree — rather than any one flag in isolation.