About the project
A provenance-first image review tool, not a black-box AI detector.
AI Image Evidence Checker helps people inspect evidence attached to an image file: C2PA Content Credentials, metadata, raw byte markers, camera-like signals, and frequency clues. It is designed to explain what is present, what is missing, and what remains inconclusive.
What it is for
- Creators checking whether a file still carries useful provenance before publishing.
- Journalists, moderators, and researchers triaging online images before deeper review.
- Teams explaining why an image report is inconclusive instead of forcing a fake-or-real label.
Evidence hierarchy
The checker treats cryptographically verifiable provenance as stronger than marker-only or content-derived signals. That hierarchy keeps the report useful without pretending every image can receive a definitive attribution.
- Layer 1
Trusted C2PA Content Credentials and asset binding when available.
- Layer 2
OpenAI-style or other provenance marker strings that need verification context.
- Layer 3
EXIF, XMP, camera-like formation clues, and byte-level marker evidence.
- Layer 4
Frequency-domain clues that can support review but are not standalone probabilities.
Limits and privacy posture
Missing metadata does not prove an image is AI-generated. Screenshots, reposts, edits, compression, and privacy tools can remove provenance. Frequency clues are forensic context, not legal attribution or a probability score.
Uploads are processed temporarily for the requested report and are not used for model training or persistent galleries in the current product flow.
How this project is maintained
Img2det Project is maintained under a project name rather than a public personal identity. AI may assist with drafting or organizing material; a human reviewer is responsible for source checks, product testing, and final publication. Corrections and reproducible evidence are handled through the public project record.