Proof of Capture: Apple Reference Image, but open source and using steganography
A developer describes an open-source project that uses steganography to embed cryptographic signatures into images at the moment of capture. This approach aims to verify the authenticity of photos and combat AI-generated misinformation by ensuring the signature survives compression and editing.
Why it matters
As AI-generated imagery becomes indistinguishable from reality, hardware-level provenance and verifiable metadata are becoming critical tools for digital trust.
September, 2026 Apple Reference Image, but open source and using steganography
Apple introduced yesterday Apple Reference Image : a way to cryptographically prove a photo was actually taken by a camera, instead of AI generated.
During my time at the Recurse Center this summer, Alex Hornstein and I (two camera lovers) built a camera with proof of capture .
The camera: a Raspberry Pi Zero, a display board, an ATECC608 crypto chip, a shutter button, and a 3D-printed enclosure.
Prove what’s real at capture time Back in 2019 I was deploying ML fact-checking tools, and even in the Will-Smith-eating-spaghetti era it was obvious that generators outrun detectors . Detection is a losing race: every improvement in the detector is training signal for the next generator.
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