So maybe I follow the link and I see an image and since I trust you, I have reason to believe that the events depicted in the image are not AI generated.
I'm building something similar. I've been avoiding URLs though because the above arrangement depends on site.com reliably serving the same image to all users. If you end up with a different image when you browse there, and you can falsify the claim, you don't know if I'm a liar, or if the underlying site changed.
So my plan is to gossip fuzzy hashes around and use patterns in the data (rabin fingerpints, perceptual hashes, etc) to then go look up whether there are any claims about that data, attaching them after the DOM has rendered. Or maybe there's no DOM, maybe you're looking at a physical page of a book or something.
Do you have any thoughts maybe supporting claims about a site's content rather than about its URL? I'm imagining something like:
That way it decomposes into separate claims which we can then verify or falsify separately, and I don't have to look like a liar when actually the site is the unreliable one. Also, if the site takes the image down, I might be able to use the hash in the claim to find whatever the claims refer to independently of where it's hosted.
it's basically an OIDC provider as an identity wallet using verifiable credentials, but I've got a "share link" system built in where you can share specific credentials/proofs with others.
Unfortunately, AMP itself was controversial and the system was not really adopted elsewhere, but it is something.
Web of trust use case example: https://bsky.app/profile/bitlooter.bsky.social
Experimenting with Keybase key holders as CAs:
https://www.reddit.com/r/Keybase/comments/1q5ys71/using_keyb...
Cryptographic Implementation of Exclusivity Agreements: https://github.com/CipherTrustee/certisfy-claim-recipes/tree...
Build Your Own Trust Chain: https://blog.certisfy.com/2026/04/build-your-own-trust-chain...
Some other examples of how you could leverage it: https://blog.certisfy.com/
Happy to answer questions.
If I've understood it, certisfy makes it possible to do something like this:
So maybe I follow the link and I see an image and since I trust you, I have reason to believe that the events depicted in the image are not AI generated.I'm building something similar. I've been avoiding URLs though because the above arrangement depends on site.com reliably serving the same image to all users. If you end up with a different image when you browse there, and you can falsify the claim, you don't know if I'm a liar, or if the underlying site changed.
So my plan is to gossip fuzzy hashes around and use patterns in the data (rabin fingerpints, perceptual hashes, etc) to then go look up whether there are any claims about that data, attaching them after the DOM has rendered. Or maybe there's no DOM, maybe you're looking at a physical page of a book or something.
Do you have any thoughts maybe supporting claims about a site's content rather than about its URL? I'm imagining something like:
That way it decomposes into separate claims which we can then verify or falsify separately, and I don't have to look like a liar when actually the site is the unreliable one. Also, if the site takes the image down, I might be able to use the hash in the claim to find whatever the claims refer to independently of where it's hosted.it's basically an OIDC provider as an identity wallet using verifiable credentials, but I've got a "share link" system built in where you can share specific credentials/proofs with others.
But I wouldn't characterize it in terms of being hard.
It's been a work in progress for many years,... so more of a problem solving and exploratory endeavor.