Photographers
Your portrait, re-uploaded without your terms attached.
A chain-of-custody ledger for media consent
Choose how your photos, videos, and audio may be used. Register the permission, trace it back from an edited copy, and keep a record when consent changes.
Follow a single illustrative file through its whole lifecycle — registered, chained, shared, checked, and withdrawn.
Illustrative walkthrough using a stock photo, not a live verification result. Matching depends on the file and the edits made to it; a fingerprint match is not a guarantee that every altered copy can be identified.
Any file that leaves your hands can lose its terms along the way. These are the four we hear about most.
Your portrait, re-uploaded without your terms attached.
A clip lifted into someone else's track, credit stripped.
A face used to train a model you never agreed to.
Work scraped into a dataset with the byline removed.
Private personal use only. Opts out of all display, dissemination, AI, or likeness extraction.
Public display for organic viewing. Prohibits monetization, AI crawl, copy, or likeness harvesting.
Allows commercial use on approved platforms subject to mandatory smart-contract royalties.
Allows unrestricted use, redistribution, and commercial dataset training on opt-in media.
Set monetization and AI training independently instead of picking a preset combination — e.g. non-monetized but AI-trainable, a combination none of the four presets cover.
Setting terms during registration looks like this — four preset consent levels plus independently configurable custom terms, each a W3C ODRL policy signed with a wallet or email-derived key.
The rights holder sets terms — commercial use, AI training, derivative works, monetization split — as a W3C ODRL policy, then signs it with a wallet or email-derived key. Fingerprints are computed from the file itself, client-side.
Every action — registration, amendment, revocation — is appended as a SHA-256-linked block in a real Firestore-backed ledger, then anchored to the public Sigstore Rekor transparency log: an independent, permanent record outside ProveConsent's own database. Each entry's hash depends on the one before it, so earlier history can't be quietly edited without breaking the chain.
An uploaded copy is resolved back to its original registration by what it is — perceptual and content-derived fingerprints — not by filename, embedded tags, or metadata that a platform may have already discarded. In our own measurements against this matching code: 95–100% of lightly re-encoded or resized copies, 80–90% of heavily cropped or recompressed ones, with 0% false matches across unrelated images in the same test.
Consent can be withdrawn at any time. The revocation is itself a permanent, timestamped ledger entry — never a silent deletion of the record.
Versus a C2PA manifest: a manifest travels attached to the file, so it's gone the moment a platform strips it or a screenshot is taken. ProveConsent is built to complement that approach, not replace it — resolution and revocation status come from the content itself, so the record is still reachable after the manifest isn't.
Methodology for the match-rate figures above: measured directly against this app's own production matching code (real perceptual hashing and real content-derived embeddings — never a simulated stand-in) across 7 real photographs and 10 realistic transformations (JPEG recompression, resize round-trips, center crops, and brightness/contrast shifts, at light/moderate/heavy severity), plus every cross-pair among those 7 photos for the false-match figure. A small sample from an early-stage product, not a large-scale study — re-measured whenever the matching code changes.
Register a file, set its terms, and know the record is still reachable — long after the metadata isn't.