What Error Level Analysis Actually Tells You
ELA is the most misread tool in image forensics. Here is what the colours mean, what they don't, and how to avoid the classic false positive.
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Practical guides to verification — how the techniques work, where they fail, and how to read a result responsibly.
ELA is the most misread tool in image forensics. Here is what the colours mean, what they don't, and how to avoid the classic false positive.
Read articleGenerators have fixed most of the obvious tells. These are the artefacts that survive into 2026, and the ones that no longer work.
Read articleEvery verification service asks you to hand over the file. We built the opposite, and the architecture is the whole argument.
Read articleA number between 0 and 100 invites false confidence. Here is how to interpret the score, the bands, and the layer breakdown responsibly.
Read articleReal photographs are noisy in a very specific way. Understanding that specificity is the foundation of generative-artefact detection.
Read articleFace-swap quality has improved enormously. These are the boundaries, blend seams and temporal artefacts that still betray it.
Read articleForensics is step four, not step one. The workflow that catches the most fakes starts somewhere else entirely.
Read articleEvery save writes a signature into an image. Reading those signatures reveals how many times a file has been through an editor.
Read articleCamera metadata is rich, useful and trivially forged. A guide to using it without over-trusting it.
Read articleAuthentic photographs fail forensic tests constantly. Knowing exactly why is the difference between analysis and accusation.
Read articleDetection is a losing arms race. Cryptographic provenance changes the question, and it is arriving faster than most people realise.
Read articleThe vocabulary you need to read forensic output, research papers and expert reports without getting lost.
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