GoKawiilSeptember, 2026
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 built a camera with proof of capture. Apple introduced yesterday: 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)
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. Our approach flips the problem: instead of trying to detect what's fake after the fact, prove what's real at the moment of capture.
The complexity of this is not at the technical level but in how to handle photo edits (should a cropped photo keep its signature?) and metadata: the moment you share an image, the EXIF gets stripped for privacy reasons, and any signature stored there is gone.
Steganography and perceptual hashes
For our camera we used steganography: an invisible watermark hidden in the image pixels themselves, containing a signed perceptual hash (a hash of what the photo looks like, not its exact bytes). Because nothing lives in the metadata, the signature survives compression and resizing. Our first version hid an exact SHA-256 hash in the last bit of each pixel, and any JPEG recompression destroyed it; the current one signs a pHash and spreads it across the whole image as a frequency-domain watermark (DWT + DCT), which survives WhatsApp-grade compression and still detects content edits.
Simplified illustration: LSB replacement is shown for clarity, the actual embedding spreads the signature across a DWT + DCT watermark.
The ATECC608 chip
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