kennethbspringer.au
@kennethspringer@infosec.exchange
Founder of snapWONDERS and builder of Vaultify — a digital media forensics platform running across clearnet, Tor, and I2P. What I work on: metadata excavation, JPEG encoder fingerprinting (identifying camera model and encoding software from compression structure alone — no EXIF needed), steganography detection and hiding, GPS triangulation, and manipulation detection. The core idea: standard metadata stripping tools remove the labels but leave the fingerprint. The quantisation tables baked into JPEG compression by camera firmware survive every strip. Vaultify finds them. Senior full-stack developer and tech lead by day. Building snapWONDERS on the side — forensics, privacy, and deep dives into file format internals. snapwonders.com · vaultify.snapwonders.com #digitalforensics #OSINT #steganography #infosec #privacy #metadata
infosec.exchange
1930s fraud-detection mathematics, still working today — just aimed at a target it was never built for.
Challenge: catch an AI-generated JPEG using nothing but a 1938 statistical law. No neural network involved.
Benford's Law: in real-world numerical data, the leading digit isn't uniformly distributed — 1 shows up ~30% of the time, 9 under 5%. Holds for river lengths, electricity bills, physical constants... and, it turns out, for the AC coefficients in a JPEG's DCT blocks, if the image actually came from a capture-and-compress pipeline.
I run this as one of six checks in snapWONDERS' analyse pipeline: 8×8 DCT on every block, absolute value of the AC coefficients (DC term excluded — it doesn't follow Benford), leading digit extracted, binned against the classic log10(1 + 1/d) curve, then a chi-squared goodness-of-fit test. Above threshold, it's flagged.
It's not a standalone verdict — heavy resampling or repeated re-saves can trip it too, same as a genuinely synthetic image would. So it feeds a combined score alongside five other signals rather than deciding anything alone. But as a zero-training, zero-black-box check, it's a genuinely satisfying one: an accounting fraud-detection tool from 1938 has something real to say about whether a photo actually came out of a camera.
Full technical breakdown (with the formula) → https://kennethbspringer.au/2026/08/05/benfords-law-detecting-ai-generated-images-without-ai/?utm_source=mastodon&utm_medium=social&utm_campaign=article-16
#digitalforensics #OSINT #infosec #aiimages #deepfake #snapWONDERS
