Closes the documented gap where EXIF/XMP fields inside AVIF/HEIF/JXL went
unparsed. metadata.exif_generator extracts the EXIF Software/Artist tag
(via PIL+piexif, which opens AVIF natively) and the XMP CreatorTool (via a
container-agnostic raw-byte scan that also covers HEIF/JXL that PIL can't
open), and matches against AI_GENERATOR_TOKENS so only generator names
(Firefly, DALL-E, Midjourney, ComfyUI, ...) fire -- a plain 'Adobe
Photoshop' or 'GIMP' tag is not flagged.
identify() surfaces it as a high-confidence signal and uses it for
platform attribution when no C2PA names a platform, so an AVIF/HEIF whose
only AI signal is an EXIF/XMP generator tag is now caught.
Validated with synthesized fixtures (the 'no positive fixtures' blocker
was self-imposed): real AVIF and JPEG written with EXIF Software via PIL,
plus an XMP CreatorTool raw-scan fixture. Zero false positives across the
109-image corpus (real iPhone photos carry no AI generator token).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Collected live C2PA positives from Bing Image Creator and Stability Brand
Studio (DreamStudio successor) and learned two things our scan got wrong:
- Bing now runs Microsoft's own MAI-Image model, not DALL-E, and signs
C2PA as 'Microsoft'. The scan caught it, but the platform label claimed
'Microsoft Designer (DALL-E / OpenAI backend)'. Relabeled model-neutral:
'Microsoft (Bing Image Creator / Designer)'.
- Stability signs C2PA as 'Stability AI' (cert 'Stability AI Ltd'), which
was not in C2PA_ISSUERS, so it read as 'unknown signer'. Added the issuer
and a platform mapping. Stability uses no SynthID and (on its current
Stable Image model) no imwatermark watermark -- verified, both negative.
Both ingested as SynthID-negative corpus fixtures (they are AI but not
SynthID) for issuer-coverage. Canva skipped: its downloads are re-encoded
design exports that strip C2PA, so a Canva sample would be inconclusive.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Research found one locally-fillable detection gap: Stable Diffusion, SDXL,
and FLUX all embed an open DWT-DCT watermark via the invisible-watermark
(imwatermark) library -- a PUBLIC decoder, no secret key, unlike SynthID.
New invisible_watermark.py decodes the known fixed patterns (verified
against upstream source: diffusers SDXL WATERMARK_MESSAGE, FLUX.2
src/flux2/watermark.py, and the 'StableDiffusionV1' default string) and
identify() reports the scheme as a high-confidence signal.
Verified locally end-to-end: embedding SDXL's exact 48-bit message and
decoding it back recovers 48/48 bits; a clean image and our own fal-SDXL
outputs decode to ~21/48 (no match). Caveat baked into the report: the
watermark is fragile -- gone after JPEG q90 -- so it confirms origin only
on pristine files; absence is never proof.
imwatermark is an optional dep (extra 'detect'; pulls non-headless opencv),
so the import is guarded and the signal is skipped when absent. CLI
--no-visible now means metadata-only (skips both pixel-domain detectors).
Also records the broader watermarking landscape in CLAUDE.md: which
services are locally detectable (SD/SDXL/FLUX), C2PA-covered (Bing/Canva/
Getty/Shutterstock unsampled), or proprietary-only like SynthID (Amazon
Titan/Nova, Kakao). Midjourney embeds neither C2PA nor an invisible mark.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Adds 20 tests around the new provenance path:
- identify(): local SD/ComfyUI params -> local-pipeline attribution;
visible-sparkle gating at the 0.5 threshold (mocked detector: above,
below, unavailable, opt-out); metadata verdict not downgraded by a
sparkle hit; OpenAI/SynthID caveats + dedup; ProvenanceReport is
JSON-serializable (the CLI --json path); and the honest edge where a
C2PA manifest without an AI source marker stays 'unknown'.
- CLI 'identify': help, clean PNG, AI PNG platform, valid --json,
missing file.
- gemini_engine.detect_sparkle_confidence: float in range for a real
image, None for an unreadable file.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
New 'identify' command and identify.py module: upload an image, get one
ProvenanceReport answering where it was made and what watermarks it
carries. Aggregates every locally-readable signal:
- C2PA Content Credentials -> generating platform (issuer + generator).
- IPTC digitalSourceType 'Made with AI' (Meta and others).
- Embedded SD/ComfyUI generation parameters (local pipelines).
- SynthID metadata proxy (Google / OpenAI C2PA companion).
- Visible Gemini sparkle (cv2 fallback for the stripped-metadata case),
promoted only at confidence >= 0.5 (corpus-tuned: Gemini sparkles
score >= 0.56, non-sparkle <= 0.49).
is_ai_generated is True or None, never asserted False -- stripped
metadata leaves no local proof of a clean origin, so absence of signals
is reported as 'unknown' with an explicit caveat. The SynthID *pixel*
watermark remains locally undecodable; the report says so.
Non-PNG containers (JPEG/WebP/AVIF/HEIF/JXL) get the same issuer +
generator attribution via a binary scan (the caBX parser is PNG-only).
The cv2 dependency is isolated in gemini_engine.detect_sparkle_confidence
so identify.py stays type-clean. CLI supports --json and --no-visible.
Validated against the 109-image corpus: 14/14 positives flagged AI,
93/94 negatives clean (the one 'neg' flagged is a Meta image that
genuinely carries the IPTC tag -- correct), zero true errors.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
test-user