C2PA
C2PA is a content provenance standard used to attach authenticity and editing history information to media assets.
Coverage
Text, images, audio, video, and code in one product.
Access
A web checker for direct use and an API for integrations.
Interpretation
Probabilistic evidence that should be reviewed with source context.
Definition
C2PA is a content provenance standard used to attach authenticity and editing history information to media assets.
- Signed provenance metadata
- Content credentials
- Camera and editing history
- Tamper-evident media records
Why it matters for detection
C2PA affects how teams interpret evidence, route review decisions, and explain authenticity findings to users or stakeholders.
- It can change which signals are reliable.
- It often requires context outside the media file.
- It should be represented clearly in review reports.
Related concepts
Synthetic media detection is strongest when glossary concepts are connected to concrete review workflows.
- Confidence scoring
- Provenance and metadata
- Human review and appeals
Common use cases
Reviewer training
Policy documentation
Technical onboarding for authenticity workflows
Methodology and limitations
How to read a result
Detection output is probabilistic evidence. A high score means the observed signals are consistent with synthetic or manipulated content under the current model and sample conditions. It does not prove authorship or intent.
When review is required
Short samples, heavy editing, compression, translation, re-recording, mixed human and AI content, and new generators can reduce confidence. Use human review before high-impact decisions.
Try ZeroTrue
Run a browser check, inspect the public API example, or create an account to keep results and generate an API key.
Frequently asked questions
Is c2pa always malicious?
No. Many synthetic media techniques have legitimate uses. Risk depends on disclosure, consent, context, and downstream harm.
How does ZeroTrue use this concept?
ZeroTrue connects glossary concepts to evidence in detection reports so reviewers can understand why a signal matters.
Why include glossary pages?
They help users, search engines, and AI answer systems understand the domain vocabulary around authenticity and synthetic media.