Registry tokens were raw substrings, so the Canva token matched the "Nova
Canvas" agent of an Amazon Bedrock image. Raw manifest bytes cannot take a
word-boundary rule: across the 1,379 C2PA files in the local corpus, 374 of
37,325 store matches had a letter or digit beside them, nearly all CBOR text
headers and DER tags. Decoded strings have no such framing.
- Match signer, claim-generator, agent and video-marker strings with
registry_word_matches.
- When the reader decoded the manifest, never re-derive the signer from raw
bytes: an unregistered signer stays unknown. Bytes decide only for
manifests the reader cannot open.
- Add fal's signer "Features & Labels"; its attribution had relied on the byte
fallback finding the "fal-ai" generator prefix.
Verdicts over 468 images and 365 videos are unchanged.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Nova Canvas images published in aws-samples were reported as Canva: with no
Amazon row, the byte fallback matched the Canva token inside the "Nova
Canvas" software agent. Add an Amazon Web Services row ahead of Canva, which
also names Nova Reel video.
When the reader cannot open a manifest, scan for signers in the C2PA store
the container locates (JPEG APP11, PNG caBX) instead of the whole metadata
region. A vivo X300 camera capture was labeled "C2PA signer: Adobe" from its
XMP toolkit string. The SynthID provenance scan reads the same store.
Adds the Nova Canvas and Nova Reel samples as MIT-0 fixtures and records the
public-sample search for the other conformance-list signers.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Collect provider samples from Higgsfield, Runway and Dreamina plus Google
Photos, Gemini, Grok and YouTube re-encodes into data/captures/2026-09 with
a hash-checked manifest, and use them to fix attribution and false positives:
- Attribute aggregator outputs: Higgsfield job metadata, Dreamina's
re-signed manifests, Runway's own C2PA signer, TC260 video producers.
- Veto any visible video mark when a valid C2PA claim names another vendor
(a Gemini Omni clip read as Sora on steam), and gate Kling and Hailuo
matches on edge, anchor and white-label evidence.
- Veto the Gemini sparkle when trusted provenance names another vendor.
- Report SynthID as present for Google Photos AI edits: Google's checker
found it on all four measured edits, though manifests record no action.
- Add Vidu video and Wan image marks, TC260 audio placements, and record
the AIGC key in metadata records.
- Document the research sweep, the Dreamina badge decision, and verified
Google statements on SynthID in Photos.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
scripts/sync_c2pa_soft_bindings.py --check hits api.github.com to resolve
the latest upstream commit SHA, unauthenticated. That endpoint's 60/hour
rate limit is per source IP, which GitHub Actions runners exhaust fast
since many workflows share the runner IP pool -- this was failing the
lint job with "403: rate limit exceeded" on every push regardless of
whether the change touched anything related.
Send an Authorization: Bearer header built from GITHUB_TOKEN/GH_TOKEN
when set, scoped to api.github.com only (raw.githubusercontent.com is a
separate, much higher-limit CDN and doesn't need it). Wire the workflow's
own GITHUB_TOKEN secret into that step's env so CI actually has one to
send, raising the limit to 5000/hour.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
The OpenArt visible-mark engine (commit 9d29d2c) was registered without
a data/fixtures/visible/openart/example.png gallery canary and without
an _ALTERNATE_SIZE entry in test_visible_fill_quality.py, breaking
TestGallery::test_every_registered_mark_has_an_example,
TestGallery::test_engine_detects_its_own_example[openart], and
test_cv2_mask_quality_smoke[alternate-openart] on every CI platform.
Generate the fixture via render_visible_examples.py (self-detects at
conf=0.968) and add the missing size entry.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Every existing text-mark engine (Doubao, Jimeng, Qwen, Baidu, Kling,
Yuanbao) is tuned to one vendor's exact wordmark silhouette, so none of
them match a bare "AI生成" strip with no brand name in front of it.
Confirmed on raiw-app production: a free `visible` run left a bottom-right
"AI生成" watermark completely unremoved because no detector fired.
Research found the wording is not tied to one dominant generator: vivo's
own support documentation confirms its Gallery stamps a bare "AI生成"
label after AI消除/AI扩图/大片模式 editing, and independent reporting
documents the same watermark on Xiaomi Gallery's AI-edit output. Since
the label is a GB 45438-2025/TC260 compliance stamp rather than one
vendor's brand mark, this adds one generic fallback (`generic_ai_label`)
instead of another per-OEM tuned config.
The detection silhouette is font-rendered (no logo element to capture)
via the shared scripts/render_vendor_silhouettes.py pipeline already
used for Qwen/Baidu/Kling/Yuanbao's own text-only marks. Calibration is
synthetic-only (no real captured generator screenshot was available);
the module docstring and DETECT_NCC_THRESHOLD comment carry that caveat
explicitly and this should be recalibrated once real captures exist.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
OpenArt.ai stamps free-plan generations with a semi-transparent white
"OpenArt" wordmark (bowtie/infinity icon + brand name) placed near the
CENTER of the frame rather than in a corner. Confirmed from a customer-
reported raiw-app production case where the mark went completely
undetected and unremoved, with no C2PA/EXIF/TC260 signal for identify
to fall back on.
- Add a new "cc" (frame-center) corner mode to the shared
TextMarkConfig/TextMarkEngine base, alongside the existing
corner/edge anchors.
- Add openart_engine.py, following the existing text-mark engine
pattern. No real capture exists (OpenArt requires an account, out of
scope to create), so the bundled alpha asset is a procedural
reconstruction of the public logo and the NCC threshold is an
explicitly-labeled provisional guess, not a measured calibration.
- Register the mark in watermark_registry.py, which auto-derives
identify's platform attribution.
- Add tests/test_openart_engine.py (synthetic composites only) plus
registry/identify test coverage, and document the mark and its
calibration caveats in README.md, docs/supported-signals.md,
docs/module-internals.md, and the skill's commands.md.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
A decorative sparkle/glint glyph in stylized typography (e.g. a book-cover
title) can clear the visible Gemini sparkle's false-positive gate at
confidence just under _SPARKLE_FP_CONF, since it shares the same bright,
near-white, sharp four-point signature the gate uses to recognize a genuine
sparkle. Confirmed against a raiw-app production incident (2026-08-27) where
this caused the removal step to permanently smudge unrelated cover art.
Investigated tightening _SPARKLE_FP_CONF and the margin/gradient/saturation
checks (plus a prototyped local edge-density signal); each was disproved by
a constructed counter-example showing a genuine weak Gemini sparkle over a
noisy/textured photo background lands in the same confidence band with the
same signature, so no safe targeted fix exists without a real labeled
corpus. No detection/removal behavior changed.
Adds DEBUG logging at the exact FP-gate bypass path for future calibration,
a regression test (TestDecorativeGlyphFalsePositive) pinning the confirmed
false positive and the blocking counter-example, and a docs record of the
finding in the Gemini sparkle section of module-internals.md.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
The video full-clip job needs ffmpeg from Ubuntu's own repositories, but its
apt-get update refreshed every source on the runner image, so a broken
third-party index failed the job twice on 2026-09-09: google-chrome.list
served a Hash Sum mismatch (bc1428ab... against 233e56de...) and both the run
and its rerun died at Install ffmpeg with ten otherwise-green jobs around
them. Remove every non-Ubuntu source definition from
/etc/apt/sources.list.d before updating, so no vendor's broken index can
fail a step that never needed it. The only apt-get in the workflows.
pre-commit: 1) maintain.sh - exit 2 at the uv-secure gate, the three triaged
no-fix advisories in docs/development.md (rechecked 2026-09-09 against PyPI);
ruff check+format clean, pyright src/ 0 errors, 2368 passed 3 skipped run
separately, same gate run as the preceding commit with no post-gate edit
between them; 2) /simplify - single pass, no fan-out available, no findings;
3) docs sync - grepped apt-get/google-chrome/Install ffmpeg across docs/,
README, .claude/rules/, tests/: no other references, the rationale lives in
the step's comment; 4) CLAUDE.md - audited against the structure rule, no
additions, revise-claude-md: no additions
The listing's MIT-0 next to the repository's Apache-2.0 was documented as a
drift to repair in the ClawHub listing itself. It is not repairable and not
drift: ClawHub's own client pins the platform skill license
(dist/schema/license.js sets PLATFORM_SKILL_LICENSE = "MIT-0", and the
version schema accepts only "MIT-0" or null), so every skill published there
is offered under MIT No Attribution. Publishing to ClawHub means offering
this skill on those terms in addition to Apache-2.0; the field is not
editable and the mismatch must not be read as drift.
pre-commit: 1) maintain.sh - exit 2 at the uv-secure gate, the three triaged
no-fix advisories in docs/development.md (rechecked 2026-09-09 against PyPI);
ruff check+format clean, pyright src/ 0 errors, 2368 passed 3 skipped run
separately; 2) /simplify - single pass, no fan-out available, prose-only
change, no findings; 3) docs sync - MIT-0/ClawHub grepped across docs/,
README, .claude/rules/, skills/: only release-and-distribution.md describes
the publish flow and stays accurate, the audit doc row is a dated snapshot,
no refs to update; 4) CLAUDE.md - audited against the structure rule, no
additions, revise-claude-md: no additions
pillow-heif's opener rewrites the EXIF orientation to 1 and stashes the real
value in info["original_orientation"], while libheif turns the raster on decode
exactly when the container declares an effective irot/imir transform. A camera
HEIC (stored raster, EXIF-only rotation) and a re-encoded one (rotation baked
as irot) both decode with Image.size matching the raster and the tag blanked,
so _read_display_tags dropped the turn for both (issue #105): a camera HEIC
went through erase and came out sideways with nothing on it saying so.
For HEIF the caller's orientation_applied claim is now ignored the way it is
for TIFF, and the container decides: isobmff.heif_transform_applied scans
meta/iprp/ipco for an irot with a non-zero angle or any imir, the orientation
comes from original_orientation, and a transform-bearing file drops the tag.
AVIF keeps the generic path: this plugin build neither blanks its tag nor
applies the transform there, and a camera-style AVIF's orientation stays
unreachable from Pillow (recorded in known-limitations).
Tests build the camera fixture without exiftool: a pillow-heif-written file
with its irot angle neutralized to the identity behaves like the reporter's
exiftool-built camera file. Mutation-checked in both directions: forcing the
detector either way fails exactly the tests whose property broke.
pre-commit: 1) maintain.sh - exit 2 at the uv-secure gate, the three triaged
no-fix advisories in docs/development.md (rechecked 2026-09-09: accelerate
1.15.0 and lightning 2.6.5 still carry no fix); ruff check+format clean,
pyright src/ 0 errors, 2368 passed 3 skipped run separately; 2) /simplify -
single pass, no fan-out available, one duplicate test helper inlined, no
other findings; 3) docs sync - heif_transform_applied, original_orientation,
irot, imir live only in module-internals.md and known-limitations.md, both
updated, no other refs; 4) CLAUDE.md - audited against the structure rule,
no additions; revise-claude-md: no CLAUDE.md changes
