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Author SHA1 Message Date
Victor KuznetsovandClaude Opus 5.5 5677c22a6b Release 0.46.0
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-17 14:31:59 -07:00
Victor KuznetsovandClaude Opus 5.5 a4eb16ad77 Build the expected MCP output path with the platform separator
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-17 14:27:35 -07:00
Victor KuznetsovandClaude Opus 5.5 06c0cb1bbe Add Codex plugin manifest, stdlib MCP server, SHA-pinned Actions
- .codex-plugin/plugin.json and assets/icon.svg package the existing skill
  tree for Codex plugin catalogs; skill version 1.0.12 across all manifests
- `remove-ai-watermarks mcp` serves identify, remove and batch over stdio,
  one CLI command per tool call, standard library only; server.json and
  glama.json for the MCP registry and Glama
- Pin every GitHub Action to a commit SHA
- Call module.train(False) instead of module.eval(), which plugin scanners
  read as dynamic code execution

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-17 14:13:04 -07:00
Victor Kuznetsov db006f034f Merge pull request #123 from wiltodelta/docs/readme-first-screen
Move the before/after demo and install lines to the README first screen
2026-10-17 12:55:01 -07:00
Victor KuznetsovandClaude Opus 5.5 604a8a8f52 Move the before/after demo and install lines to the README first screen
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-17 12:30:46 -07:00
Victor KuznetsovandClaude Opus 5.5 19ae5d1b0a Strip app-export and Kling SEI provenance from MP4, refresh watermark docs
video metadata --remove now blanks app-export JSON in keyed and keyless
metadata items (Dreamina writes it twice), which it previously left in
place while exiting 1.

Kling writes an H.264 user_data_unregistered SEI message (a fixed UUID
plus "kling-ai") into the first video sample. get_ai_metadata reports
it as kling_sei, identify_video names Kling from it when no TC260 label
does, and the streaming stripper blanks every copy inside mdat during
its existing copy pass. Lengths stay, the SEI stays well-formed, and
ffmpeg framemd5 hashes of every frame match before and after on both
tracked Kling fixtures. Across 255 local files only the seven Kling
videos changed verdict.

invisible now exits 1 on an undecodable source instead of reporting the
no-signal code for a file it never read.

Docs: a per-command "what each path leaves behind" table, the October
literature sweep, Suno's announced audio watermark, Anthropic's
SynthID-Text-based Claude watermark, and an independent TrustMark
false-positive benchmark.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-17 12:30:01 -07:00
Victor Kuznetsov 21f4621eb7 Add SynthID Detector surface, drop extra web confirmation 2026-10-17 11:47:53 -07:00
Victor Kuznetsov f1d4d4afba Merge pull request #121 from dukagjina/fix/preserve-invisible-transparency
Preserve alpha in invisible image processing
2026-10-16 18:06:56 -07:00
Victor Kuznetsov 2430689f96 Merge branch 'main' into fix/preserve-invisible-transparency 2026-10-16 12:36:43 -07:00
Victor KuznetsovandClaude Opus 5.5 cf695de57f Refresh the C2PA soft-binding snapshot and fix Ruff ICN001
The upstream registry gained be.immostory.videoseal.1 at revision d5960248,
so `sync_c2pa_soft_bindings.py --check` failed lint on main and on every pull
request. That step runs ahead of Ruff, which hid an ICN001 error in
scripts/_corpus_scan.py; import `date` directly, as the sibling scripts do.
Document the check's live-upstream behavior next to the refresh command.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-16 12:15:03 -07:00
dukagjina a054185fa5 Preserve source transparency during invisible image processing 2026-10-16 02:04:54 -04:00
Victor Kuznetsov 3e20bb0b92 Merge pull request #120 from wiltodelta/dependabot/uv/minor-and-patch-7fed723961 2026-10-14 22:27:16 -07:00
dependabot[bot] 0b4170ae98 Bump the minor-and-patch group with 6 updates
Bumps the minor-and-patch group with 6 updates:

| Package | From | To |
| --- | --- | --- |
| [pillow-heif](https://github.com/bigcat88/pillow_heif) | `1.8.0` | `1.8.1` |
| [diffusers](https://github.com/huggingface/diffusers) | `0.40.0` | `0.41.0` |
| [diffsynth](https://github.com/modelscope/DiffSynth-Studio) | `2.1.8` | `2.1.9` |
| [onnxruntime](https://github.com/microsoft/onnxruntime) | `1.30.0` | `1.31.0` |
| [openai](https://github.com/openai/openai-python) | `3.24.0` | `3.29.0` |
| [ruff](https://github.com/astral-sh/ruff) | `0.16.10` | `0.17.0` |


Updates `pillow-heif` from 1.8.0 to 1.8.1
- [Release notes](https://github.com/bigcat88/pillow_heif/releases)
- [Changelog](https://github.com/bigcat88/pillow_heif/blob/master/CHANGELOG.md)
- [Commits](https://github.com/bigcat88/pillow_heif/compare/v1.8.0...v1.8.1)

Updates `diffusers` from 0.40.0 to 0.41.0
- [Release notes](https://github.com/huggingface/diffusers/releases)
- [Commits](https://github.com/huggingface/diffusers/compare/v0.40.0...v0.41.0)

Updates `diffsynth` from 2.1.8 to 2.1.9
- [Release notes](https://github.com/modelscope/DiffSynth-Studio/releases)
- [Commits](https://github.com/modelscope/DiffSynth-Studio/commits)

Updates `onnxruntime` from 1.30.0 to 1.31.0
- [Release notes](https://github.com/microsoft/onnxruntime/releases)
- [Changelog](https://github.com/microsoft/onnxruntime/blob/main/docs/ReleaseNotesWorkflow.md)
- [Commits](https://github.com/microsoft/onnxruntime/compare/v1.30.0...v1.31.0)

Updates `openai` from 3.24.0 to 3.29.0
- [Release notes](https://github.com/openai/openai-python/releases)
- [Changelog](https://github.com/openai/openai-python/blob/main/CHANGELOG.md)
- [Commits](https://github.com/openai/openai-python/compare/v3.24.0...v3.29.0)

Updates `ruff` from 0.16.10 to 0.17.0
- [Release notes](https://github.com/astral-sh/ruff/releases)
- [Changelog](https://github.com/astral-sh/ruff/blob/main/CHANGELOG.md)
- [Commits](https://github.com/astral-sh/ruff/compare/0.16.10...0.17.0)

---
updated-dependencies:
- dependency-name: pillow-heif
  dependency-version: 1.8.1
  dependency-type: direct:production
  update-type: version-update:semver-patch
  dependency-group: minor-and-patch
- dependency-name: diffusers
  dependency-version: 0.41.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: minor-and-patch
- dependency-name: diffsynth
  dependency-version: 2.1.9
  dependency-type: direct:production
  update-type: version-update:semver-patch
  dependency-group: minor-and-patch
- dependency-name: onnxruntime
  dependency-version: 1.31.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: minor-and-patch
- dependency-name: openai
  dependency-version: 3.29.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: minor-and-patch
- dependency-name: ruff
  dependency-version: 0.17.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: minor-and-patch
...

Signed-off-by: dependabot[bot] <support@github.com>
2026-10-14 20:05:51 +00:00
Victor Kuznetsov 4241a01659 Release 0.45.1 2026-10-08 16:42:57 -07:00
Victor Kuznetsov c37378b347 Merge pull request #117 from dichiara19/fix/sdxl-zimage-global-offload
Stream the sdxl-zimage global stack on cards below 12 GiB
2026-10-08 16:34:43 -07:00
Victor Kuznetsov 8cb99b73b2 Fix SDXL offload placement on the current CUDA device 2026-10-08 16:17:11 -07:00
Giuseppe G. Di Chiara c45e6db3e4 Stream the sdxl-zimage global stack on cards below 12 GiB
The SDXL global stack (fp16 UNet, Canny ControlNet, both text encoders, VAE)
is ~8.8 GiB and was always moved to CUDA with .to(device), so it could not
fit an 8 GiB card and --cpu-offload never reached it. Under the Windows
display driver, WSL2 included, the overflow spilled into shared system
memory and the four-step pass ran for over ten minutes instead of failing.

Residency now follows the same rule as the Qwen stack: an explicit request
wins, otherwise the card's total VRAM decides against
RESIDENT_SDXL_GLOBAL_MIN_VRAM_GIB. Below it the Lightning LoRA is fused on
the CPU and the stack is streamed with enable_sequential_cpu_offload, the
fastest placement that completed on every run of an 8 GiB card with 16 GiB
of system RAM. sdxl-zimage joins GLOBAL_OFFLOAD_PROFILES, so the
--cpu-offload warning now fires for chroma-zimage only.
2026-10-08 23:27:55 +02:00
Victor Kuznetsov 37fb080c74 Merge pull request #116 from wiltodelta/dependabot/uv/minor-and-patch-931ef6a6bd 2026-10-08 10:30:09 -07:00
dependabot[bot] 954298aa14 Bump the minor-and-patch group with 3 updates
Bumps the minor-and-patch group with 3 updates: [python-dotenv](https://github.com/theskumar/python-dotenv), [openai](https://github.com/openai/openai-python) and [ruff](https://github.com/astral-sh/ruff).


Updates `python-dotenv` from 1.2.3 to 1.2.4
- [Release notes](https://github.com/theskumar/python-dotenv/releases)
- [Changelog](https://github.com/theskumar/python-dotenv/blob/main/CHANGELOG.md)
- [Commits](https://github.com/theskumar/python-dotenv/compare/v1.2.3...v1.2.4)

Updates `openai` from 3.22.1 to 3.24.0
- [Release notes](https://github.com/openai/openai-python/releases)
- [Changelog](https://github.com/openai/openai-python/blob/main/CHANGELOG.md)
- [Commits](https://github.com/openai/openai-python/compare/v3.22.1...v3.24.0)

Updates `ruff` from 0.16.9 to 0.16.10
- [Release notes](https://github.com/astral-sh/ruff/releases)
- [Changelog](https://github.com/astral-sh/ruff/blob/main/CHANGELOG.md)
- [Commits](https://github.com/astral-sh/ruff/compare/0.16.9...0.16.10)

---
updated-dependencies:
- dependency-name: python-dotenv
  dependency-version: 1.2.4
  dependency-type: direct:production
  update-type: version-update:semver-patch
  dependency-group: minor-and-patch
- dependency-name: openai
  dependency-version: 3.24.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: minor-and-patch
- dependency-name: ruff
  dependency-version: 0.16.10
  dependency-type: direct:production
  update-type: version-update:semver-patch
  dependency-group: minor-and-patch
...

Signed-off-by: dependabot[bot] <support@github.com>
2026-10-07 08:48:45 +00:00
Victor KuznetsovandClaude Opus 5.5 10c7775990 Hide maintainer skills from public skill discovery
The skills CLI discovers every SKILL.md under .claude/skills, so
provider-oracles and signal-discovery were offered by `npx skills add`
and listed on skills.sh beside the published skill. Mark both
metadata.internal, the CLI's documented hide flag, and fail the suite
on any project skill that lacks it.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-05 20:04:18 -07:00
Victor KuznetsovandClaude Opus 5.5 3f6447b23d Record how to run the gate from an agent session
The full gate outlasts the agent's 10-minute foreground shell cap, so it must
run detached with its exit code written to a file. A stray run is stopped by
its own PID, because a pattern kill also ends other sessions' suites.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-05 18:25:14 -07:00
Victor KuznetsovandClaude Opus 5.5 cc63bfd7bf Release 0.45.0
Bump the package to 0.45.0 and the agent skill to 1.0.11. The skill now names
the dola and workbuddy image mark keys, which 0.44.0 rejects, so the probe's
MIN_CLI_VERSION rises to 0.45.0 and both keys carry a "since CLI" note that
the floor test reads.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-05 17:45:18 -07:00
Victor Kuznetsov 898f8be789 Add AI disclosure layouts, tighten detection and provenance warnings 2026-10-04 11:03:37 -07:00
Victor KuznetsovandClaude Opus 5.5 72752feb33 Scan uv.lock in CI and add a security policy
Add a CI job running the maintain.sh uv-secure scan, pinned to the gate by
a parity test, and a SECURITY.md with private reporting and dependency
remediation. Refresh the security-gate block record for accelerate 1.15.0.

Closes #114

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-02 10:33:50 -07:00
Victor KuznetsovandClaude Opus 5.5 70adddf960 Record why Qwen-Image-2.1 is not a regeneration profile
Open weights remove the hosted-only objection to the 2.x line, but the
Diffusers pipeline has no strength or latent noise-mask input and the Qwen
Research License is non-commercial (issue #111).

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-02 10:33:49 -07:00
Victor Kuznetsov 01a2665181 Reconcile research follow-up status 2026-10-01 22:10:00 -07:00
Victor Kuznetsov 0c3e0fa415 Release 0.44.0 2026-10-01 14:24:27 -07:00
Victor Kuznetsov b3b868153f Record Google Photos checks and continue across provider accounts 2026-10-01 13:42:21 -07:00
Victor Kuznetsov 304bd071c0 Unify TC260 producers and strengthen provenance regression coverage
Share producer identities across mark routing, attribution, and pinned signers.
Preserve nested Honor TC260 fields and report unsupported RSA signatures.
Document the Google Photos checks and public sample search.

Use an SDK-signed synthetic carrier for negative EKU checks after the original
Microsoft certificates expired. Skip boundary regex scans when no C2PA
soft-binding identifier is present.
2026-10-01 11:30:32 -07:00
Victor Kuznetsov 2e26df1f21 Restore C2PA certificate validation and refresh compatible dependencies 2026-09-30 16:58:43 -07:00
Victor KuznetsovandClaude Opus 5.5 d800ec9455 Verify TC260 SecurityData label signatures against a pinned MiniMax key
MiniMax signs its TC260 label with SM3withSM2 per TC260-PG-202511A. A
verification-only SM3/SM2 (no dependency provides the SM2 curve) checks the
appendix A.1 label message; a signature under the pinned MiniMax key is a
high-confidence aigc_signature signal, a failing one is a caveat, and every
result is the aigc_signature metadata marker. Pinned by the GB/T 32905 SM3
vectors, OpenSSL's SM2 verify vectors and real MiniMax files. Over 411 local
files the only verdict-record change is the marker on nine MiniMax videos.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-09-30 15:36:08 -07:00
Victor KuznetsovandClaude Opus 5.5 ef7b972ed1 Sync the C2PA soft-binding snapshot to d36d1c1
The upstream list widened com.museblossom.contentsdefence.1 from image to
audio, image and video. Verdicts over 411 local files are unchanged.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-09-30 15:36:08 -07:00
Victor KuznetsovandClaude Opus 5.5 b96ede6f44 Record the verified MiniMax TC260 SecurityData signatures
MiniMax writes a TC260-PG-202511A SecurityData object with SM3withSM2
signatures. The label signature verifies on all four local MiniMax videos
against the guide's appendix A.1 message, and the Binding signature over the
compact Bindings entry; the SM3 content hash does not match a naive selection.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-09-29 22:16:42 -07:00
Victor KuznetsovandClaude Opus 5.5 ca59c032a1 Release 0.43.0
Bump the package to 0.43.0 and the agent skill to 1.0.10. The skill now names
the wan image and vidu video mark keys, which 0.42.0 rejects, so the probe's
MIN_CLI_VERSION rises to 0.43.0 and both keys carry a "since CLI" note that
the floor test reads.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-09-29 21:39:08 -07:00
Victor Kuznetsov c5e138357e Record Z-Image-Turbo global-stage rejection 2026-09-29 20:55:59 -07:00
Victor Kuznetsov 21661bea35 Reproduce re-watermarking and verify SynthID coexistence 2026-09-29 13:50:52 -07:00
Victor Kuznetsov 5cb4f2f808 Add Perth and PixelSeal benchmark oracles 2026-09-28 11:14:28 -07:00
Victor Kuznetsov 33f748b32a Record VACE and ROSE video inpainting results 2026-09-28 10:54:19 -07:00
Victor KuznetsovandClaude Opus 5.5 742a0dccab Align the remaining klein and color-restoration wording with the results
module-internals still called FLUX.2 klein pending; the sweep still counted
three inconclusive Gemini rows where only one was an explicit tool verdict,
and the removal page stated a Google chroma leak the data only warns of.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-09-27 21:24:59 -07:00
Victor KuznetsovandClaude Opus 5.5 b5fc3ef9a6 Add face and text fidelity to the FLUX.2 klein comparison
fidelity_metrics.py at each engine's clean strengths: klein keeps Latin and
Cyrillic sign lettering better on two Google carriers, but loses every face
comparison and the verified CJK text, which the 512-pixel LPIPS had hidden.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-09-27 18:59:06 -07:00
Victor KuznetsovandClaude Opus 5.5 6eb1a94799 Close the FLUX.2 klein Google measurement
The fourth Google carrier clears at 0.25, so the klein operating point with
the usual cross-source margin is 0.40, where the limiting carrier is at
LPIPS 0.270 against qwen-zimage's 0.183. klein is not a replacement global
stage for either vendor. Also record that Gemini's image-check allowance is
per account and the new "checks on similar images" quota wording.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-09-27 16:02:33 -07:00
Victor KuznetsovandClaude Opus 5.5 32791ee832 Record the FLUX.2 klein Google brackets from four Gemini accounts
Three of four Google carriers clear with klein at or below 0.20, where it
matches qwen-zimage's PSNR at 0.35, beats its LPIPS, and keeps the objects
qwen-zimage redraws. The fourth is detected at 0.10 and inconclusive at 0.20,
so there is no Google operating point yet.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-09-27 15:49:57 -07:00
Victor KuznetsovandClaude Opus 5.5 a103b4ec15 Record the FLUX.2 klein global-stage measurement
Stock Flux2KleinInpaintPipeline feeds the clean source back as reference
tokens, so it copies the source and OpenAI SynthID survives strength 0.30.
Without those tokens klein clears OpenAI between 0.05 and 0.20, at lower
fidelity than qwen-zimage at its floor. Google is unmeasured: the Gemini
Verify AI tool answered with a tool error or quota limit, which also casts
doubt on two of the earlier color-restoration "inconclusive" rows.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-09-27 15:17:26 -07:00
Victor KuznetsovandClaude Opus 5.5 7341e1a648 Record the CIELAB color-restoration measurement after regeneration
Transplanting the source's a,b channels onto qwen-zimage outputs at the vendor
floors cut CIEDE2000 on all seven tracked originals, kept every OpenAI API
verdict not_detected, but left three of four Gemini checks inconclusive and
painted old object colors onto redrawn ones. Not shipped.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-09-27 14:49:22 -07:00
Victor Kuznetsov dfbaa018c6 Merge pull request #112 from wiltodelta/docs/library-research-landscape
Research sweep, provider captures, and provenance attribution fixes
2026-09-27 11:39:15 -07:00
Victor KuznetsovandClaude Opus 5.5 e310a22bd8 Compare capture paths in POSIX form on every platform
The manifest stores forward-slash paths, and str() of a Windows path uses
backslashes, so the index test failed on both Windows CI jobs.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-09-27 10:11:54 -07:00
Victor KuznetsovandClaude Opus 5.5 f855c4700f Merge origin/main into docs/library-research-landscape
Main's claim_generator_platform and c2pa_vendor_platform now use the
branch's whole-word registry match, which replaces
claim_generator_word_platform. The branch's provenance veto covers every
video mark and made main's Veo-over-Sora override unreachable, so the
override is removed. Main's credential rule carries into the veto: an
invalid credential vetoes nothing. Provenance that confirms the mark's
own vendor also vetoes nothing. Over 78 local videos with a C2PA AI
claim, the only verdict changes against main are Kling/Hailuo false
positives on Veo and FLUX clips that the veto now removes. C2PA verdicts
over 1,379 files are unchanged against the pre-merge branch.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-09-26 23:52:29 -07:00
Victor KuznetsovandClaude Opus 5.5 5a0f771ed7 Close the remaining raw-byte identity scans and unify two rules
- A decoded manifest no longer takes its generator from a raw
  claim_generator CBOR value or a soft binding from raw bytes. Device tokens
  (NIKON, Pixel Camera, sony.sig) stay a byte scan, since the decoded strings
  do not carry them, but read the manifest store: an EXIF Make beside an
  unrelated AI manifest is not a verified capture. The source-kind scan keeps
  the whole buffer because it also reads IPTC digitalSourceType in XMP.
- The byte fallback's c2pa.ai-disclosure kind now uses the structured rule:
  human_validated beside prompt_guided is a generation, not an enhancement.
- Wan and Yuanbao share BottomRightAnchoredEngine instead of two copies of
  the corner gate. The Yuanbao anchor test shifted the mark outside the locate
  window, so it passed with or without the gate; it now shifts it inside.

Verdicts over 1,379 C2PA files, 468 fixture and capture files, and Wan and
Yuanbao detections over 285 images are unchanged.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-09-26 22:19:30 -07:00
Victor KuznetsovandClaude Opus 5.5 4931b93097 Add a Higgsfield DoP capture
Higgsfield's own DoP model ("Higgsfield Lite" in the web app, job model
image2video/lite) is not exposed by the MCP connector, so the capture was made
in the web app on a JPEG frame after a first job on a PNG failed and was
refunded. Like Genjutsu, the output carries no provenance: no C2PA, no TC260
label and no visible mark, only a Lavf re-mux.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-09-26 21:17:27 -07:00
Victor KuznetsovandClaude Opus 5.5 509ce633a3 Judge decoded C2PA manifests on their decoded strings alone
Extend the whole-word rule to every identity lookup. Once the reader has
decoded a manifest, no identity is re-derived from its raw bytes: not the
signer, not a signer-platform token, not the AI-tool fallback for the
generator, and not the SynthID vendor inference, in identify and in
metadata.synthid_source alike. The byte scans read the manifest store only
when the reader could not open it.

Claim-generator tokens match as whole words through one shared
claim_generator_word_platform (suno no longer matches Sunoco), for images
and video alike.

The verdict now reads SynthID from the decoded C2PA info when the metadata
dict lacks it; three synthetic Google Photos tests had relied on the byte
fallback for that.

Verdicts over 1,379 C2PA files and 468 fixture and capture files are
unchanged.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-09-26 20:19:13 -07:00
Victor KuznetsovandClaude Opus 5.5 b02eb12cb2 Match registry tokens as whole words in decoded manifest strings
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>
2026-09-26 17:38:35 -07:00
Victor KuznetsovandClaude Opus 5.5 fb92c7dbc8 Attribute Amazon Bedrock C2PA and scope the signer fallback scan
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>
2026-09-26 16:21:13 -07:00
Victor KuznetsovandClaude Opus 5.5 7ba07869d2 Add paid-service captures, aggregator attribution, and provenance vetoes
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>
2026-09-26 14:32:53 -07:00
Victor Kuznetsov d25cada76b Export calibrated image source providers 2026-09-25 14:38:04 -07:00
Victor Kuznetsov b1f15818d7 Add pinned OpenAI and Google image source classifier 2026-09-25 14:23:01 -07:00
Victor Kuznetsov 317124ee85 Keep model prereleases out of package distribution 2026-09-25 13:54:06 -07:00
Victor Kuznetsov 0d468b6022 Add verified publication path for image source model 2026-09-25 13:25:20 -07:00
Victor KuznetsovandClaude Opus 5.5 1dc70df289 Upgrade to OpenCV 5 with frozen Hershey templates and tighten video marks
- Lock OpenCV 5 and cap NumPy below 2.4 through uv constraint-dependencies so
  PaddleX 3.7 keeps resolving; Dependabot ignores mirror the cap.
- OpenCV 5 draws Hershey putText glyphs differently, so the Dola and Kling
  video templates ship as committed OpenCV 4 renders with a recipe script, and
  the OpenArt alpha recipe now refuses any OpenCV but 4.x.
- Break Sora/Veo cross-matches in favor of Veo under valid Google AI-video
  provenance, and require the full Sora mascot shape for mascot-only matches.
- Let the Doubao engine detect marks tinted by saturated backgrounds.
- Share C2PA claim-generator, credential-level and vendor-platform helpers,
  JPEG suffixes and the DCT basis instead of per-module copies.
- Log model download failures, document the optional GITHUB_TOKEN, mark the
  photo and source classifier model cards archived, and refresh the lock.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-09-23 19:19:00 -07:00
Victor Kuznetsov 6f629a4ea6 Release 0.42.0 2026-09-22 09:25:21 -07:00
Victor KuznetsovandClaude Sonnet 5 e3bbe88155 Authenticate C2PA registry-sync GitHub API calls to fix CI rate-limiting
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>
2026-09-22 08:11:48 -07:00
Victor Kuznetsov be8f24c7cb Raise OpenAI Qwen strength floor 2026-09-21 23:02:49 -07:00
Victor KuznetsovandClaude Sonnet 5 9990f3e6ca Fix missing OpenArt gallery fixture and alternate-size entry
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>
2026-09-21 22:37:21 -07:00
Victor KuznetsovandClaude Sonnet 5 83be3a8926 Add generic bare "AI生成" text-mark detector (brand-less TC260 fallback)
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>
2026-09-21 22:01:10 -07:00
Victor KuznetsovandClaude Sonnet 5 9d29d2c777 Add OpenArt visible watermark detection and removal
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>
2026-09-21 21:51:46 -07:00
Victor KuznetsovandClaude Sonnet 5 7a6491fdc1 Document Gemini sparkle decorative-glyph false positive, add observability
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>
2026-09-21 21:41:59 -07:00
Victor Kuznetsov 37431c9aeb Pin Web oracle proxy sessions per batch 2026-09-16 16:17:36 -07:00
Victor Kuznetsov 804735aa48 Release 0.41.1 2026-09-16 10:42:15 -07:00
Victor Kuznetsov e3f714dcd2 Merge pull request #109 from wiltodelta/dependabot/uv/minor-and-patch-138d877835
Bump the minor-and-patch group with 6 updates
2026-09-16 09:25:05 -07:00
dependabot[bot] 7169780dd0 Bump the minor-and-patch group with 6 updates
Bumps the minor-and-patch group with 6 updates:

| Package | From | To |
| --- | --- | --- |
| [accelerate](https://github.com/huggingface/accelerate) | `1.14.0` | `1.15.0` |
| [huggingface-hub](https://github.com/huggingface/huggingface_hub) | `1.30.0` | `1.31.0` |
| [onnxruntime](https://github.com/microsoft/onnxruntime) | `1.29.0` | `1.30.0` |
| [openai](https://github.com/openai/openai-python) | `3.9.0` | `3.13.0` |
| [ruff](https://github.com/astral-sh/ruff) | `0.16.6` | `0.16.7` |
| [pyright](https://github.com/RobertCraigie/pyright-python) | `1.1.411` | `1.1.414` |


Updates `accelerate` from 1.14.0 to 1.15.0
- [Release notes](https://github.com/huggingface/accelerate/releases)
- [Commits](https://github.com/huggingface/accelerate/compare/v1.14.0...v1.15.0)

Updates `huggingface-hub` from 1.30.0 to 1.31.0
- [Release notes](https://github.com/huggingface/huggingface_hub/releases)
- [Commits](https://github.com/huggingface/huggingface_hub/compare/v1.30.0...v1.31.0)

Updates `onnxruntime` from 1.29.0 to 1.30.0
- [Release notes](https://github.com/microsoft/onnxruntime/releases)
- [Changelog](https://github.com/microsoft/onnxruntime/blob/main/docs/ReleaseNotesWorkflow.md)
- [Commits](https://github.com/microsoft/onnxruntime/compare/v1.29.0...v1.30.0)

Updates `openai` from 3.9.0 to 3.13.0
- [Release notes](https://github.com/openai/openai-python/releases)
- [Changelog](https://github.com/openai/openai-python/blob/main/CHANGELOG.md)
- [Commits](https://github.com/openai/openai-python/compare/v3.9.0...v3.13.0)

Updates `ruff` from 0.16.6 to 0.16.7
- [Release notes](https://github.com/astral-sh/ruff/releases)
- [Changelog](https://github.com/astral-sh/ruff/blob/main/CHANGELOG.md)
- [Commits](https://github.com/astral-sh/ruff/compare/0.16.6...0.16.7)

Updates `pyright` from 1.1.411 to 1.1.414
- [Release notes](https://github.com/RobertCraigie/pyright-python/releases)
- [Commits](https://github.com/RobertCraigie/pyright-python/compare/v1.1.411...v1.1.414)

---
updated-dependencies:
- dependency-name: accelerate
  dependency-version: 1.15.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: minor-and-patch
- dependency-name: huggingface-hub
  dependency-version: 1.31.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: minor-and-patch
- dependency-name: onnxruntime
  dependency-version: 1.30.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: minor-and-patch
- dependency-name: openai
  dependency-version: 3.13.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: minor-and-patch
- dependency-name: ruff
  dependency-version: 0.16.7
  dependency-type: direct:production
  update-type: version-update:semver-patch
  dependency-group: minor-and-patch
- dependency-name: pyright
  dependency-version: 1.1.414
  dependency-type: direct:production
  update-type: version-update:semver-patch
  dependency-group: minor-and-patch
...

Signed-off-by: dependabot[bot] <support@github.com>
2026-09-16 08:49:01 +00:00
Victor Kuznetsov c7021b900b Add source pipeline classifier runtime 2026-09-15 23:17:48 -07:00
Victor Kuznetsov 3f55df6f99 Correct source classifier activation schema 2026-09-15 22:55:46 -07:00
Victor Kuznetsov 4795149d34 Publish source classifier model card 2026-09-15 22:36:34 -07:00
Victor Kuznetsov cf30b4f95a Release 0.40.6 2026-09-15 22:00:05 -07:00
Victor Kuznetsov 8ce8bf14da Document GPT Image 2.5 compatibility 2026-09-15 21:32:46 -07:00
Victor Kuznetsov 3fb94b220d Wait for PyPI simple index before distribution 2026-09-15 21:05:14 -07:00
Victor Kuznetsov d2c5aa66fc Merge remote-tracking branch 'origin/main' 2026-09-15 19:21:01 -07:00
Victor Kuznetsov 380820fa7e Add SDXL verified-text restoration 2026-09-15 19:20:37 -07:00
Victor Kuznetsov 12e9a87865 Publish abstaining source pipeline classifier 2026-09-15 19:18:35 -07:00
Victor Kuznetsov 19fccf27cb Release 0.40.4 with calibrated invisible profiles 2026-09-15 16:49:41 -07:00
Victor Kuznetsov a385aab433 Calibrate provider-specific invisible removal profiles 2026-09-15 16:38:17 -07:00
Victor Kuznetsov 1d7a6270d4 Add phase-free spectral pipeline probe 2026-09-15 16:20:31 -07:00
Victor Kuznetsov b5cd16aef0 Add local Microsoft InvisMark payload disruption 2026-09-14 12:07:00 -07:00
Victor Kuznetsov bf63e8e187 Attribute discovered C2PA signers 2026-09-14 11:51:19 -07:00
Victor Kuznetsov d4181f3277 Complete visible signal discovery scanner 2026-09-13 17:46:29 -07:00
Victor Kuznetsov bd14f40c7d Complete corpus signal discovery fixes 2026-09-13 16:54:58 -07:00
Victor Kuznetsov c4edc2820d Expand provenance metadata discovery 2026-09-12 13:36:46 -07:00
Victor Kuznetsov 927429d349 Fix Space pin waiter indent so distribute can find the run 2026-09-11 11:01:04 -07:00
Victor Kuznetsov df94f2c908 Release 0.40.1 with Qwen symbol false-positive fix 2026-09-11 10:55:28 -07:00
Victor Kuznetsov b2e46ee8db Automate Space pin and lengthen the ComfyUI waiter 2026-09-11 10:19:25 -07:00
383 changed files with 20058 additions and 3108 deletions

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+1 -1
View File
@@ -6,7 +6,7 @@
},
"metadata": {
"description": "Agent skill and Claude Code plugin for the remove-ai-watermarks CLI.",
"version": "1.0.8"
"version": "1.0.12"
},
"plugins": [
{
+28 -8
View File
@@ -27,26 +27,35 @@ top-level Python API, and runtime detection/removal pipelines.
The unified maintainer entry point is `scripts/provider_oracles.py`; its workflow and
slot schema live in `docs/provider-oracles.md`. Multi-account and multi-network work
selects one named slot explicitly from the gitignored repository-local
`.oracle-slots.json` by default and snapshots it into the immutable batch manifest.
Never commit the local slot file.
Do not add account or IP rotation, rate-limit failover, or cross-session result merging.
selects each named slot explicitly from the gitignored repository-local
`.oracle-slots.json` by default and snapshots it into a separate immutable batch
manifest. A provider check may use the finite set of configured account slots and surfaces
after a refusal. Do not add new logins, IP rotation, network-route failover,
unbounded retries, or cross-session result merging. Never commit the local
slot file.
Every manual result stays bound to the exact sanitized upload hash and preserves the
provider response verbatim.
Provider surface selection is API-first. OpenAI and Microsoft use their official API
adapters before their Web surfaces when the requested media and local configuration are
supported. Google and Meta currently use Web because this tooling has no usable API route
for them. Web remains an explicit second surface, never an automatic retry after an API
refusal, quota response, transport error, or indeterminate verdict.
for them. A request to use a provider covers every configured surface, including Web,
without a second confirmation. An API refusal, quota response, transport error, or
indeterminate verdict stays on that surface and never silently submits the file to Web.
Google Web oracle automation uses only the user's existing authenticated real Chrome
session and explicit `/u/N/` account index. OpenAI, Microsoft, and Meta Web automation
session. Gemini uses an explicit `/u/N/` account index. The SynthID Detector at
`https://synthid.com/` (`synthid-web`) uses the same Chrome profile and does not take a
`/u/N/` index; its terms forbid driving the page as an automated API. OpenAI, Microsoft, and Meta Web automation
uses isolated Playwright contexts; it must never attach to or copy state from the user's
real browser. Proxy credentials are read only through a slot's named environment variable
and never enter a manifest or log. Dotenv interpolation may derive routed proxy URLs from
one secret key without mutating the process environment. A selected proxy context may
accept that proxy's TLS interception certificate; direct contexts keep normal TLS checks.
ThorData rotating endpoints are pinned to one manifest-derived sticky session for the
life of a Web batch so one browser context does not change exit identity between page
requests. This is route continuity, not account or IP failover; a refusal still ends on
the selected slot and never selects another route automatically.
Upload readiness is surface-specific: OpenAI reaches it at page load but keeps background
requests alive, while Microsoft and Meta require network idle. Preserve exact provider
errors as indeterminate evidence rather than retrying or interpreting them as clean.
@@ -73,9 +82,12 @@ The same rule applies to install hints: name the extra that actually makes the c
Run `bash maintain.sh` from the repository root. The authoritative type gate is scoped to `src/`; full-project Pyright can exhaust Node memory on the ML dependency graph.
The full gate outlasts the agent's 10-minute foreground shell cap, which kills it mid-suite. Run it detached under `nohup caffeinate -dimu` with its exit code written to a file and poll that file. To stop a stray run, kill its own PID, never `pkill -f pytest`, which also takes down other sessions' suites on the machine.
The security scanner's exit status is authoritative, including a failure after a success
message. `tests/test_maintenance.py` checks clean, vulnerable, and broken scanner
runs through the real shell entry point. Recheck unresolved advisories using the
runs through the real shell entry point, and pins the CI `security` job to the
same scanner line with no `continue-on-error`. Recheck unresolved advisories using the
procedure in `docs/development.md`; do not revive the old text-matching bypass.
Boundary modules for cv2, Torch, and Diffusers may carry narrow per-file relaxations for unknown third-party types. Keep pure-logic files strict, preserve the local piexif stub, and fix real errors before widening a pragma.
@@ -129,6 +141,10 @@ Do not classify an entire module as untestable because its main path downloads a
- the photo-classify gate in `test_classify.py`: DEFINITELY is ridge AND MLP,
POSSIBLY does not emit a provider, and `identify` does not import
`remove_ai_watermarks.classify`.
- the source-export classifier in `test_source_classify.py`: the Hub revision
and artifact hash are immutable, the pickle-free schema and exact GELU are
validated, threshold mutation changes the real decision, and `identify`
never consumes the result as watermark evidence.
- the `InvisibleOptions` defaults, in `test_api.py`. When one signature promises to
mirror another, compare them field by field rather than pinning the values you happen
to know about, so the next field added on one side and not the other fails at the
@@ -295,3 +311,7 @@ explicit unchanged decodes when comparing stored pixels. Execute Ubuntu Bash
workflow harnesses only on POSIX hosts with Bash; keep their pure Python checks
active on every platform. Round floating-point image output before uint8
conversion when quantization must preserve constant values across OpenCV builds.
OpenCV 5 draws Hershey `putText` glyphs smaller and heavier than 4.x, so a
calibrated template drawn with `putText` ships as a committed PNG whose recipe
refuses any OpenCV but 4.x (`scripts/render_video_hershey_templates.py`,
`scripts/build_openart_alpha.py`); never render one at import time.
+79 -18
View File
@@ -1,6 +1,8 @@
---
name: provider-oracles
description: Run hash-bound Google, OpenAI, Microsoft, or Meta watermark-oracle checks for this repository. Use for provider verification, multi-account Gemini checks, isolated Playwright checks, or recording oracle evidence.
metadata:
internal: true
---
# Provider oracles
@@ -14,22 +16,39 @@ Named slots live in the gitignored repository-local
pass `--slots PATH` only to override the local path.
Never substitute one provider's negative verdict for another provider's signal.
Do not optimize candidates adaptively against an external oracle. A retry,
different account, or different network is a new explicit operator decision,
not automatic fallback.
Do not optimize candidates adaptively against an external oracle.
## Account continuation
A request to verify a bounded set of files with a provider authorizes using that
provider's configured account slots unless the user limits the account scope.
Before starting, identify the finite set of available authenticated slots and
prepare one immutable batch per slot. After a quota refusal or service failure,
record the exact response, leave that slot's remaining rows unsubmitted, and
continue automatically through the remaining authorized slots. Do not stop to
request permission for each account or file already covered by the task.
Submit each frozen artifact at most once per slot in that pass. Preserve
inconclusive results and disagreements between accounts. Stop when the bounded
plan is complete or no authorized usable slot remains; report remaining rows.
New logins, another provider, or a new network route require authorization.
The oracles and slots already configured for the requested provider may be used
again, including their Web surfaces, without a second confirmation. Account
continuation does not authorize changing candidate pixels or erasing failures.
## Default surface priority
Prefer an official API adapter whenever that provider, media type, and configured
slot support it. Use Web only when no usable API route exists or the operator
explicitly requests the Web surface as a second check. For OpenAI and Microsoft,
the default plans are API then Web. Google and Meta currently have only usable
Web routes in this tooling. Inspect the order with `plan PROVIDER`.
slot support it. For OpenAI and Microsoft, the default plans are API then Web.
Google and Meta currently have only usable Web routes in this tooling. Google's
routes are `gemini-web` and `synthid-web`. Inspect the order with `plan PROVIDER`.
The same request may use every configured surface.
The priority is a selection policy, not automatic failover. An API refusal,
quota response, transport error, or indeterminate verdict must be recorded and
reported. Do not submit the same artifact to Web unless the operator separately
authorizes that next surface.
reported. The same request already covers every configured surface of that
provider, including Web. Run Web as its own acknowledged check and keep its
verdict separate. Do not replace the API result with the Web result.
## Route by surface
@@ -44,18 +63,51 @@ Playwright CLI runner, copied cookies, or a new login.
real Chrome profile and navigate directly to
`https://gemini.google.com/u/<google_account_index>/app`.
3. Prepare an immutable `gemini-web` batch outside the repository.
4. Before each upload, request the action-time confirmation required for sending
that exact prepared file to Gemini. Do not upload the source path directly.
5. Attach one prepared upload and ask: `Was this image/video/audio created or
edited by Google AI?`
For every image check, visually inspect the source first. Remove every visible
AI-provider logo or label with the project's visible-mark remover, derive all
paired controls and candidates from that cleaned image, and let `prepare` strip
AI metadata. Inspect the prepared upload again and do not submit it if a visible
provider mark remains. A model answer based on a visible logo is not a SynthID
result.
4. Confirm that the prepared files and provider are covered by the user's
request or existing upload approval. Ask only if that scope is missing or
changed; do not request confirmation again for each file or account in the
authorized plan. Do not upload the source path directly.
5. Attach one prepared upload and ask: `Does this image/video/audio contain a
SynthID watermark? Use the SynthID verification tool only; do not infer from
visible content, logos, text, or metadata.` Do not substitute a general
Google-AI-origin question; it permits visual-content reasoning instead of a
SynthID verdict.
6. Read the settled SynthID tool outcome, not the surrounding model reasoning.
Preserve unclear, quota, and refusal wording rather than interpreting it as
clean.
7. Record the verbatim response and verify the completed batch.
If the selected Chrome profile or `/u/N/` account is not already authenticated,
stop and ask the user to select the intended existing session. Do not sign in or
switch to another account implicitly.
If a planned Chrome profile or `/u/N/` account is not already authenticated,
record that it is unavailable and continue with another authorized existing
session. Ask the user only when no usable authorized session remains. Do not
start a new login.
### SynthID Detector
Use the user's real authenticated Chrome. Do not use isolated Playwright: the
portal's additional terms forbid using the page as an automated API, bulk
verification, and quota evasion.
1. Validate a `synthid-web` slot. It names `browser_profile` and `account_label`.
It does not use `google_account_index` or a proxy variable.
2. Prepare an immutable batch outside the repository. Inspect images the same
way as for Gemini, and do not submit a file that still shows a provider logo.
3. Open `https://synthid.com/` in the named Chrome profile. Accept the terms
dialog when it is shown. Do not start a new login. If the page requires
sign-in and that profile has no session, leave the row unsubmitted.
4. Attach one prepared upload through the page's own file control.
5. Read the settled label. `Watermark detected` is `detected`. `Watermark not
detected` is `not_detected`. Quota, sign-in, and unclear wording stay
`refused` or `indeterminate`.
6. Record the verbatim response. The result covers partner SynthID from Google
DeepMind, Nvidia, OpenAI, and Kakao, and it does not name which partner. Do
not record it as a Gemini-only or OpenAI-only verdict.
### OpenAI, Microsoft, and Meta Web
@@ -88,13 +140,22 @@ OpenAI, Microsoft, and Meta Web slots may each name one of them through
verify egress before relying on it, and never automatically change route after
a refusal. Bound a batch before starting.
ThorData user-and-password endpoints without `sessid` rotate the exit on each
request, which breaks a browser page whose resources must share one network
identity. The runner therefore derives one sticky `sessid` from the immutable
manifest hash and keeps it for that batch. A new prepared batch gets a new
session; rerunning or resuming the same batch keeps its session while the proxy
retains it. An explicit `sessid` in the configured route is preserved. This is
session continuity, not permission to retry a refused batch on another route.
### OpenAI API
Use `check-openai` with one explicit upload acknowledgement. Keep named API keys
as `OPENAI_API_KEY_1`, `OPENAI_API_KEY_2`, and `OPENAI_API_KEY_3` in the local `.env`, and select
only their variable names through an `openai-api` slot's `api_key_env`. Never
print a key, copy one into a slot or manifest, or fall back automatically to a
second key. API slots use a direct SDK transport that ignores environment proxy
print a key or copy one into a slot or manifest. Continue through authorized
named API slots according to the bounded account plan above; keep a separate
batch for each. API slots use a direct SDK transport that ignores environment proxy
settings. The current adapter is image-only.
### Microsoft API
+6 -1
View File
@@ -1,6 +1,8 @@
---
name: signal-discovery
description: Discover missing AI provenance and watermark coverage in the remove-ai-watermarks library from fresh or historical corpora, then validate detection and removal parity. Use for corpus gap mining, periodic signal audits, new-provider discovery, or deciding whether old retained data must be replayed. Do not use for ordinary per-file identification or removal.
metadata:
internal: true
---
# Signal discovery
@@ -58,7 +60,10 @@ finding.
3. Run the applicable fresh and historical discovery modes from the reference.
Use `corpus_gap_scan.py --since YYYY-MM-DD` for the overlapping fresh window
and omit `--since` for the complete history. Report counts per input shape
and per outcome; an example does not establish coverage.
and per outcome; an example does not establish coverage. Give every code and
corpus snapshot a distinct `--report` path. The adjacent
`.progress.jsonl` checkpoint is the live progress source and makes the same
command resumable; use `--restart` only when intentionally discarding it.
4. Triage every candidate into one of: parser/serialization gap, missing vendor
attribution, new visible mark, possible invisible signal, format/read error,
expected non-AI provenance, or false candidate. Preserve unresolved items as
@@ -8,7 +8,7 @@ historical data is sufficient.
| Surface | Discovery evidence | Regression check | Removal proof |
| --- | --- | --- | --- |
| C2PA, EXIF, XMP, IPTC, PNG text, TC260, soft bindings, and container metadata | `scripts/corpus_gap_scan.py` plus review of unattributed and partially attributed reports | `scripts/sidecar_regression.py`; compare record-based and file-based identification when collection changes | `scripts/metadata_removal_audit.py`; signal absent after strip and decoded pixels/streams unchanged |
| Registered visible image marks | `scripts/visible_positives.py`; metadata-derived vendor cohorts and blinded sheets for uncovered labels | `scripts/visible_eval.py`, registered examples, and full-corpus crossfire | `scripts/visible_removal_audit.py`; same-mark redetection plus visual residual review and fill-quality checks |
| Registered visible image marks | `scripts/visible_positives.py` records strict and metadata-corroborated results, metadata cohorts, and blinded native-detail bands for uncovered cohorts plus an unbiased quiet sample | `scripts/visible_eval.py` exposes registry members without adjudicated scope, registered examples, and full-corpus crossfire | `scripts/visible_removal_audit.py`; same-mark redetection plus visual residual review and fill-quality checks |
| Candidate China-AIGC visible marks | `scripts/vendor_cohort_harvest.py` partitions by producer identity without using pixels; inspect full-width top and bottom sheets | `scripts/vendor_mark_calibrate.py` against independently labelled positives, clean negatives, and neighbouring marks | Register only after the candidate gate survives full-corpus crossfire; then use the normal visible-removal audit |
| Registered visible video marks | Review provider-labelled or controlled complete clips, not isolated frames alone | Full-clip tests and the local real-provider audit described in `docs/verification-plan.md` | Preserve sequence, timing, duration, and audio; second-pass detection must be quiet |
| Locally decodable invisible image marks, including open DWT-DCT and TrustMark | Positive-control-gated corpus or constructed carriers; a negative on an uncontrolled carrier is inconclusive | `scripts/watermark_benchmark.py` and the relevant decoder tests with the required extras installed | Re-run the same decoder on output and retain a positive control in the same run |
@@ -42,6 +42,12 @@ compressed pixels, but its inventory should be reconciled with the current
metadata constants and registry on every audit. Do not infer completeness from
`No gap candidates` until the other rows of the matrix also ran.
For a visible discovery pass, use a fresh report path and pass `--sheets` to
`visible_positives.py`. Review the numbered PNG files before opening
`MANIFEST_DO_NOT_OPEN.csv`; metadata cohorts select where a mark may occur but do
not label the pixels. The separate `unbiased-quiet` stratum is required because a
new provider may carry neither a mapped producer code nor readable provenance.
## When to replay old data
Yes, old data must be rerun. Current code can learn to parse an old
+39
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@@ -0,0 +1,39 @@
{
"name": "remove-ai-watermarks",
"version": "1.0.12",
"description": "Identify and remove AI provenance marks from images and video the user generated or edited, using the remove-ai-watermarks CLI.",
"author": {
"name": "wiltodelta",
"url": "https://github.com/wiltodelta"
},
"homepage": "https://raiw.cc",
"repository": "https://github.com/wiltodelta/remove-ai-watermarks",
"license": "Apache-2.0",
"keywords": [
"ai-watermark",
"watermark-removal",
"c2pa",
"synthid",
"provenance",
"gemini",
"sora"
],
"skills": "./skills/",
"interface": {
"displayName": "Remove AI Watermarks",
"shortDescription": "Identify and remove AI watermarks and provenance metadata",
"longDescription": "Runs the open-source remove-ai-watermarks CLI locally to identify C2PA, IPTC, EXIF and TC260 provenance, visible AI-generator labels and supported invisible watermarks, then removes them from images and video the user generated or edited. It does not remove stock, agency or other third-party marks.",
"developerName": "wiltodelta",
"category": "Productivity",
"capabilities": ["Read", "Write"],
"websiteURL": "https://github.com/wiltodelta/remove-ai-watermarks",
"defaultPrompt": [
"Check this image for AI watermarks and provenance metadata",
"Remove the AI metadata from my generated video without re-encoding it",
"Remove the visible AI label from the corner of my image"
],
"brandColor": "#A78BFA",
"composerIcon": "./assets/icon.svg",
"logo": "./assets/icon.svg"
}
}
+15
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@@ -0,0 +1,15 @@
# Local state and secrets never belong in a plugin bundle.
.env
.env.*
!.env.example
.oracle-slots.json
.local-eval/
.venv/
__pycache__/
*.pyc
# Generated media and model artifacts.
data/
*.mp4
*.onnx
*.safetensors
*.pt
+10
View File
@@ -6,6 +6,10 @@
# Create and manage keys at: https://platform.openai.com/api-keys
# OPENAI_API_KEY=
# GitHub token (optional; only for scripts/sync_c2pa_soft_bindings.py)
# Raises the api.github.com rate limit from 60 to 5000 requests/hour. GH_TOKEN is read as a fallback.
# GITHUB_TOKEN=
# Local photo-classifier weights (optional; otherwise fetched from Hugging Face)
# Directory contents are documented in docs/photo-classify.md.
# RAIW_CLASSIFY_WEIGHTS=/path/to/classifier-weights
@@ -19,6 +23,11 @@
# Fallback cache root when HF_HOME is unset (optional)
# XDG_CACHE_HOME=/path/to/cache
# Gemini API key (optional; only for generating Google provider samples by hand)
# Paid tier: Nano Banana 2 Lite and Gemini Omni Flash have no free tier.
# Create and manage keys at: https://aistudio.google.com/apikey
# GEMINI_API_KEY=
# Named OpenAI keys for provider-oracle slots (optional; keep each value secret)
# OPENAI_API_KEY_1=
# OPENAI_API_KEY_2=
@@ -34,6 +43,7 @@
# ThorData residential proxies (optional; only for explicitly selected Web oracle routes)
# Generate these URLs in the ThorData endpoint generator; do not commit credentials.
# The Web runner pins a rotating user-and-password route to one sticky session per manifest.
# THORDATA_ROUTE_US=http://td-customer-USERNAME-country-US:PASSWORD@HOST.pr.thordata.net:9999
# THORDATA_ROUTE_DE=http://td-customer-USERNAME-country-DE:PASSWORD@HOST.pr.thordata.net:9999
# THORDATA_ROUTE_GB=http://td-customer-USERNAME-country-GB:PASSWORD@HOST.pr.thordata.net:9999
+12 -8
View File
@@ -14,18 +14,22 @@ updates:
update-types:
- "minor"
- "patch"
# The `all` extra must remain jointly resolvable. These candidates violate
# compatibility constraints: older supported TrustMark builds require NumPy 1.x, OpenCV 4.12+
# requires NumPy 2 on newer Python versions, and this project keeps tokenizers
# below 0.23 for the stable Transformers path. Keep Dependabot on the
# compatible lines until those constraints move.
# The `all` extra must remain jointly resolvable. PaddleX 3.7 (the OCR
# extra) requires NumPy <2.4, mirrored by `constraint-dependencies` in
# pyproject.toml, and this project keeps tokenizers below 0.23 for the stable
# Transformers path. Keep Dependabot on the compatible lines until those
# constraints move. Transformers 5.16+ requires tokenizers 0.23.1+,
# and Diffusers requires huggingface-hub <2. Mirror the manifest bounds.
ignore:
- dependency-name: "numpy"
versions:
- ">=2"
- dependency-name: "opencv-python-headless"
- ">=2.4"
- dependency-name: "transformers"
versions:
- ">=4.12"
- ">=5.16"
- dependency-name: "huggingface-hub"
versions:
- ">=2"
- dependency-name: "tokenizers"
versions:
- ">=0.23"
+153 -19
View File
@@ -7,8 +7,8 @@ name: Distribute on release
# - HF Space: factory-rebuild the version already pinned in the Space repo.
# - ComfyUI: sync, test, and publish the node against the exact library release.
# - ClawHub: publish the agent skill when its own version moved.
# All wait for the freshly published sdist to appear on PyPI first, since the
# Release event fires in parallel with publish.yml's upload.
# All wait for the freshly published distribution to appear in both PyPI APIs
# first, since the Release event fires in parallel with publish.yml's upload.
on:
release:
@@ -21,7 +21,12 @@ on:
jobs:
resolve:
# Model-only prereleases must not reach PyPI, Homebrew, Spaces, or ComfyUI.
if: ${{ github.event_name != 'release' || (startsWith(github.event.release.tag_name, 'v') && !github.event.release.prerelease) }}
runs-on: ubuntu-latest
# Thirty attempts may spend up to 20 seconds each in the JSON request,
# simple-index request, and inter-attempt delay. Leave bounded headroom.
timeout-minutes: 25
outputs:
version: ${{ steps.v.outputs.version }}
url: ${{ steps.sdist.outputs.url }}
@@ -57,32 +62,41 @@ jobs:
PYTHON
- name: Upload distributed release identity
uses: actions/upload-artifact@v7
uses: actions/upload-artifact@cf430e030ddbb5b0abf93d22962f4752f3646cd9 # v7.0.2
with:
name: distributed-release-${{ github.run_attempt }}
path: release-identity.json
if-no-files-found: error
- name: Wait for the sdist on PyPI, capture url + sha256
- name: Wait for the PyPI JSON and simple indexes, capture sdist metadata
id: sdist
run: |
set -euo pipefail
v="${{ steps.v.outputs.version }}"
for i in $(seq 1 30); do
if rel=$(curl -fsSL "https://pypi.org/pypi/remove-ai-watermarks/$v/json" 2>/dev/null); then
url=$(echo "$rel" | python3 -c "import sys,json;d=json.load(sys.stdin);print(next((u['url'] for u in d['urls'] if u['packagetype']=='sdist'),''))")
sha=$(echo "$rel" | python3 -c "import sys,json;d=json.load(sys.stdin);print(next((u['digests']['sha256'] for u in d['urls'] if u['packagetype']=='sdist'),''))")
if rel=$(curl --connect-timeout 10 --max-time 20 -fsSL "https://pypi.org/pypi/remove-ai-watermarks/$v/json" 2>/dev/null); then
read -r url sha <<< "$(echo "$rel" | python3 -c "import sys,json;u=next((u for u in json.load(sys.stdin)['urls'] if u['packagetype']=='sdist'),{});print(u.get('url',''),u.get('digests',{}).get('sha256',''))")"
if [ -n "$url" ] && [ -n "$sha" ]; then
echo "url=$url" >> "$GITHUB_OUTPUT"
echo "sha=$sha" >> "$GITHUB_OUTPUT"
echo "Found sdist for $v"
exit 0
# PyPI's JSON API can show a freshly uploaded file before the
# simple index used by pip has caught up. Downstream release
# jobs install by package version, so waiting on JSON alone
# creates a release-time race for them.
simple=$(curl --connect-timeout 10 --max-time 20 -fsSL https://pypi.org/simple/remove-ai-watermarks/ 2>/dev/null || true)
artifact=${url##*/}
if [[ "$simple" == *"$artifact"* ]]; then
echo "url=$url" >> "$GITHUB_OUTPUT"
echo "sha=$sha" >> "$GITHUB_OUTPUT"
echo "PyPI JSON and simple indexes list $v"
exit 0
fi
fi
fi
echo "sdist for $v not on PyPI yet (attempt $i), waiting..."
sleep 20
if [ "$i" -lt 30 ]; then
echo "PyPI indexes do not both list $v yet (attempt $i), waiting..."
sleep 20
fi
done
echo "::error::sdist for $v did not appear on PyPI in time"
echo "::error::PyPI JSON and simple indexes did not both list $v in time"
exit 1
homebrew:
@@ -90,7 +104,7 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Checkout the tap
uses: actions/checkout@v7
uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1 # v7.0.1
with:
repository: wiltodelta/homebrew-tap
token: ${{ secrets.HOMEBREW_TAP_TOKEN }}
@@ -114,10 +128,91 @@ jobs:
needs: resolve
runs-on: ubuntu-latest
steps:
- name: Factory-rebuild the HuggingFace Space
- name: Bump the Space pin, then factory-rebuild
env:
GH_TOKEN: ${{ secrets.RAIW_HF_SPACE_TOKEN }}
HF_TOKEN: ${{ secrets.HF_TOKEN }}
VERSION: ${{ needs.resolve.outputs.version }}
run: |
set -euo pipefail
repo=wiltodelta/raiw-hf-space
workflow=pin-library.yml
if [ -z "${GH_TOKEN:-}" ]; then
echo "RAIW_HF_SPACE_TOKEN secret is not set; skipping the pin bump."
else
dispatched_at=$(date -u +%Y-%m-%dT%H:%M:%SZ)
gh workflow run "$workflow" \
--repo "$repo" \
--ref main \
--raw-field library_version="$VERSION"
run_id=""
for attempt in $(seq 1 30); do
run_id=$(
gh run list \
--repo "$repo" \
--workflow "$workflow" \
--event workflow_dispatch \
--limit 10 \
--json databaseId,createdAt \
| python3 -c "import json,sys; t=sys.argv[1]; print(next((r['databaseId'] for r in json.load(sys.stdin) if r['createdAt']>=t), ''))" \
"$dispatched_at"
)
if [ -n "$run_id" ]; then
break
fi
echo "Space pin run not visible yet (attempt $attempt), waiting..."
sleep 2
done
if [ -z "$run_id" ]; then
echo "::error::The dispatched Space pin run did not appear"
exit 1
fi
for attempt in $(seq 1 180); do
read -r status conclusion <<< "$(
gh run view "$run_id" \
--repo "$repo" \
--json status,conclusion \
--jq '[.status, (.conclusion // "")] | @tsv'
)"
if [ "$status" = "completed" ]; then
if [ "$conclusion" = "success" ]; then
echo "Space pin run $run_id succeeded"
break
fi
echo "::error::Space pin run $run_id completed with $conclusion"
exit 1
fi
echo "Space pin run $run_id is $status (attempt $attempt), waiting..."
sleep 5
done
if [ "${status:-}" != "completed" ]; then
echo "::error::Space pin run $run_id did not finish in time"
exit 1
fi
echo "Waiting for the Space requirements pin to show $VERSION..."
pinned=""
for attempt in $(seq 1 40); do
reqs=$(curl -fsSL \
"https://huggingface.co/spaces/wiltodelta/remove-ai-watermarks/raw/main/requirements.txt" \
|| true)
pinned=$(printf '%s\n' "$reqs" \
| sed -n 's/^remove-ai-watermarks==\([0-9][0-9a-zA-Z.]*\).*/\1/p' \
| head -1)
echo " attempt $attempt: Space pin=$pinned"
if [ "$pinned" = "$VERSION" ]; then
break
fi
sleep 15
done
if [ "$pinned" != "$VERSION" ]; then
echo "::error::Space requirements.txt still pinned to ${pinned:-<none>}, not $VERSION"
exit 1
fi
fi
python3 -m pip install --quiet huggingface_hub
python3 - <<'PY'
import os
@@ -132,7 +227,7 @@ jobs:
needs: resolve
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v7
- uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1 # v7.0.1
- name: Publish the agent skill when its version moved
env:
CLAWHUB_TOKEN: ${{ secrets.CLAWHUB_TOKEN }}
@@ -217,7 +312,12 @@ jobs:
exit 1
fi
for attempt in $(seq 1 180); do
# 0.40.0's node sync finished after this waiter: 180 * 5s is 15 min,
# and the node suite plus registry upload ran longer. Keep the
# workflow wait, then accept a registry row for this library version
# so a late-but-published node is not reported as a missing release.
version="${{ needs.resolve.outputs.version }}"
for attempt in $(seq 1 360); do
read -r status conclusion <<< "$(
gh run view "$run_id" \
--repo "$repo" \
@@ -235,5 +335,39 @@ jobs:
echo "ComfyUI sync run $run_id is $status (attempt $attempt), waiting..."
sleep 5
done
echo "::error::ComfyUI sync run $run_id did not finish in time"
echo "ComfyUI sync run $run_id did not finish in time; checking the registry."
python3 -m pip install --quiet packaging
if curl -fsSL "https://api.comfy.org/nodes/remove-ai-watermarks/versions" \
| VERSION="$version" python3 -c '
import json, os, sys
from packaging.requirements import InvalidRequirement, Requirement
from packaging.utils import canonicalize_name
from packaging.version import Version
version = os.environ["VERSION"]
target = Version(version)
def requires_release(value):
try:
requirement = Requirement(value)
except InvalidRequirement:
return False
return (
canonicalize_name(requirement.name) == "remove-ai-watermarks"
and requirement.url is None
and requirement.marker is None
and target in requirement.specifier
and any(s.operator == ">=" and Version(s.version) == target for s in requirement.specifier)
)
matches = [
v for v in json.load(sys.stdin)
if any(requires_release(d) for d in (v.get("dependencies") or []))
]
if not matches:
sys.exit(1)
newest = max(matches, key=lambda v: v.get("createdAt") or "")
print("%s %s" % (newest.get("version"), newest.get("status")))
'; then
echo "Registry already lists a node for $version; the wait timed out after publish."
exit 0
fi
echo "::error::ComfyUI sync run $run_id did not finish in time and the registry has no node for $version"
exit 1
@@ -0,0 +1,59 @@
name: Publish image-source classifier to Hugging Face
# Manual only. The derivative weights live in a GitHub model-freeze release;
# private training images and caches never enter this repository.
on:
workflow_dispatch:
inputs:
confirm:
description: "Type publish"
required: true
weights_tag:
description: "GitHub Release tag holding openai-google-source-v1.npz"
required: true
default: image-source-freeze-2026-09-25-v1
jobs:
publish:
if: ${{ github.event.inputs.confirm == 'publish' }}
runs-on: ubuntu-latest
timeout-minutes: 15
permissions:
contents: read
steps:
- uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1 # v7.0.1
- uses: astral-sh/setup-uv@37802adc94f370d6bfd71619e3f0bf239e1f3b78 # v7.6.0
with:
python-version: "3.12"
- name: Download derivative weights
env:
GH_TOKEN: ${{ github.token }}
TAG: ${{ github.event.inputs.weights_tag }}
run: |
set -euo pipefail
mkdir -p weights
gh release download "$TAG" \
--repo "${{ github.repository }}" \
--pattern openai-google-source-v1.npz \
--dir weights
test -s weights/openai-google-source-v1.npz
- name: Verify artifact hash
run: |
set -euo pipefail
expected="$(jq -r .artifact_sha256 docs/image-source-hf/metrics.json)"
test "${#expected}" -eq 64
echo "$expected weights/openai-google-source-v1.npz" | sha256sum --check
- name: Publish to Hugging Face
env:
HF_TOKEN: ${{ secrets.HF_TOKEN }}
SHA: ${{ github.sha }}
run: |
set -euo pipefail
if [ -z "${HF_TOKEN:-}" ]; then
echo "HF_TOKEN secret is not set" >&2
exit 1
fi
uv run --no-project --with huggingface-hub \
python scripts/publish_image_source_hf.py \
--src weights \
--message "Image-source classifier freeze (GitHub ${SHA:0:7})"
@@ -36,9 +36,9 @@ jobs:
permissions:
contents: read
steps:
- uses: actions/checkout@v7
- uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1 # v7.0.1
- uses: astral-sh/setup-uv@v7
- uses: astral-sh/setup-uv@37802adc94f370d6bfd71619e3f0bf239e1f3b78 # v7.6.0
with:
python-version: "3.12"
@@ -0,0 +1,64 @@
name: Publish source classifier to Hugging Face
# Manual only. The derivative model weights live in a GitHub model-freeze
# release; the private training corpus and caches never enter this repository.
on:
workflow_dispatch:
inputs:
confirm:
description: "Type publish"
required: true
weights_tag:
description: "GitHub Release tag holding source-pipeline-mlp.npz"
required: true
default: source-classify-freeze-2026-09-16-r2
jobs:
publish:
if: ${{ github.event.inputs.confirm == 'publish' }}
runs-on: ubuntu-latest
timeout-minutes: 15
permissions:
contents: read
steps:
- uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1 # v7.0.1
- uses: astral-sh/setup-uv@37802adc94f370d6bfd71619e3f0bf239e1f3b78 # v7.6.0
with:
python-version: "3.12"
- name: Download derivative model weights
env:
GH_TOKEN: ${{ github.token }}
TAG: ${{ github.event.inputs.weights_tag }}
run: |
set -euo pipefail
mkdir -p weights
gh release download "$TAG" \
--repo "${{ github.repository }}" \
--pattern source-pipeline-mlp.npz \
--dir weights
test -s weights/source-pipeline-mlp.npz
- name: Verify the frozen artifact
run: |
set -euo pipefail
expected="$(jq -r .artifact_sha256 docs/source-classify-hf/metrics.json)"
test "${#expected}" -eq 64
echo "$expected weights/source-pipeline-mlp.npz" | sha256sum --check
- name: Publish to Hugging Face
env:
HF_TOKEN: ${{ secrets.HF_TOKEN }}
SHA: ${{ github.sha }}
run: |
set -euo pipefail
if [ -z "${HF_TOKEN:-}" ]; then
echo "HF_TOKEN secret is not set" >&2
exit 1
fi
uv run --no-project --with huggingface-hub \
python scripts/publish_source_classify_hf.py \
--src weights \
--message "Source-classify freeze (GitHub ${SHA:0:7})"
+5 -3
View File
@@ -10,12 +10,14 @@ permissions:
jobs:
publish:
# Model-only prereleases are not Python package releases.
if: ${{ startsWith(github.event.release.tag_name, 'v') && !github.event.release.prerelease }}
runs-on: ubuntu-latest
environment: pypi
steps:
- uses: actions/checkout@v7
- uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1 # v7.0.1
- uses: astral-sh/setup-uv@v7
- uses: astral-sh/setup-uv@37802adc94f370d6bfd71619e3f0bf239e1f3b78 # v7.6.0
- name: Verify release tag matches package version
run: |
@@ -38,4 +40,4 @@ jobs:
# is needed. uv's uploader also accepts Metadata-Version 2.5 -- the permanent
# fix that lets the hatchling pin be relaxed (see pyproject [build-system]).
- name: Publish to PyPI
run: uv publish
run: uv publish
+2 -2
View File
@@ -32,8 +32,8 @@ jobs:
skill:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v7
- uses: astral-sh/setup-uv@v7
- uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1 # v7.0.1
- uses: astral-sh/setup-uv@37802adc94f370d6bfd71619e3f0bf239e1f3b78 # v7.6.0
- name: Sync dev environment
run: uv sync --frozen --extra dev
- name: Agent skill packaging tests
+23 -8
View File
@@ -16,17 +16,32 @@ jobs:
lint:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v7
- uses: astral-sh/setup-uv@v7
- uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1 # v7.0.1
- uses: astral-sh/setup-uv@37802adc94f370d6bfd71619e3f0bf239e1f3b78 # v7.6.0
- name: Sync dev environment
run: uv sync --frozen --extra dev
- name: Check C2PA soft-binding registry snapshot
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
run: uv run python scripts/sync_c2pa_soft_bindings.py --check
- name: Ruff lint
run: uv run ruff check
- name: Ruff format check
run: uv run ruff format --check
security:
name: lockfile vulnerability scan
runs-on: ubuntu-latest
timeout-minutes: 5
steps:
- uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1 # v7.0.1
- uses: astral-sh/setup-uv@37802adc94f370d6bfd71619e3f0bf239e1f3b78 # v7.6.0
with:
enable-cache: false
# Policy and triaged blocks: docs/development.md "Known security-gate blocks".
- name: Scan uv.lock with uv-secure
run: uvx uv-secure uv.lock
test:
name: test ${{ matrix.os }} py${{ matrix.python-version }}
runs-on: ${{ matrix.os }}
@@ -54,8 +69,8 @@ jobs:
- os: windows-latest
python-version: "3.14"
steps:
- uses: actions/checkout@v7
- uses: astral-sh/setup-uv@v7
- uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1 # v7.0.1
- uses: astral-sh/setup-uv@37802adc94f370d6bfd71619e3f0bf239e1f3b78 # v7.6.0
with:
python-version: ${{ matrix.python-version }}
- name: Sync dev environment
@@ -67,8 +82,8 @@ jobs:
name: versioned transport contracts py3.14
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v7
- uses: astral-sh/setup-uv@v7
- uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1 # v7.0.1
- uses: astral-sh/setup-uv@37802adc94f370d6bfd71619e3f0bf239e1f3b78 # v7.6.0
with:
python-version: "3.14"
- name: Create clean runtime contract environment
@@ -89,8 +104,8 @@ jobs:
runs-on: ubuntu-latest
timeout-minutes: 5
steps:
- uses: actions/checkout@v7
- uses: astral-sh/setup-uv@v7
- uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1 # v7.0.1
- uses: astral-sh/setup-uv@37802adc94f370d6bfd71619e3f0bf239e1f3b78 # v7.6.0
with:
python-version: "3.12"
- name: Install ffmpeg
+1 -1
View File
@@ -38,7 +38,7 @@ jobs:
steps:
- name: Download distributed release identity
if: ${{ github.event_name == 'workflow_run' }}
uses: actions/download-artifact@v8
uses: actions/download-artifact@9000827ccba6bdab643e8b6fd33ac0654aef8333 # v8.0.2
with:
pattern: distributed-release-*
path: distribution-identities
+4 -1
View File
@@ -8,6 +8,7 @@ The project gives users control over provenance marks on content they generated
- Add visible templates only for AI-generation labels.
- Do not add stock, agency, or classifieds marks to `watermark_registry.py`.
- Do not add templates for regulator-defined disclosure icons (EU Code of Practice Annex 1).
- Keep `erase --region` generic and user-directed; do not build an automatic stock-watermark remover on it.
Full boundary and legal context: [`docs/legal-and-safety.md`](docs/legal-and-safety.md).
@@ -39,11 +40,13 @@ Before a release, read [`docs/release-and-distribution.md`](docs/release-and-dis
The published Agent Skill is [`skills/remove-ai-watermarks/`](skills/remove-ai-watermarks/). Update it in the same change as any CLI edit that alters commands, extras, exit codes, mark keys, or the intended-use boundary. Install and publish steps: [`docs/agent-skill.md`](docs/agent-skill.md).
The same skill tree is the Codex plugin (`.codex-plugin/plugin.json`). `remove-ai-watermarks mcp` is a standard-library MCP server that runs one CLI command per tool call; keep it dependency-free, because the MCP registry launches it as a bare `uvx remove-ai-watermarks mcp` that cannot add extras ([`docs/mcp-server.md`](docs/mcp-server.md)).
## Module architecture
[`docs/module-internals.md`](docs/module-internals.md) is the canonical per-module map, including design decisions, thresholds, calibration history, incident records, and regression guards. Read the relevant section before changing a subsystem.
Research and current constraints are routed through [`docs/index.md`](docs/index.md), especially [`docs/known-limitations.md`](docs/known-limitations.md), [`docs/supported-signals.md`](docs/supported-signals.md), [`docs/synthid.md`](docs/synthid.md), and [`docs/watermarking-landscape.md`](docs/watermarking-landscape.md). Pixel photo classification is [`docs/photo-classify.md`](docs/photo-classify.md); it is not `identify`. Classifier research is split between general [`AI-generated image classifiers`](docs/ai-generated-image-classifiers.md) and [`SynthID source classifiers`](docs/synthid-classifiers.md). Other SynthID campaign logs are [`docs/synthid-detector-research.md`](docs/synthid-detector-research.md) and [`docs/synthid-removal-research.md`](docs/synthid-removal-research.md). The pre-split chronological archive is [`docs/synthid-detector-removal-plan.md`](docs/synthid-detector-removal-plan.md). The benchmark kernel and its pinned local oracles (AudioSeal, VideoSeal) cover the audio/video watermark cohorts and research studies: [`docs/benchmark-kernel.md`](docs/benchmark-kernel.md).
Research and current constraints are routed through [`docs/index.md`](docs/index.md), especially [`docs/known-limitations.md`](docs/known-limitations.md), [`docs/supported-signals.md`](docs/supported-signals.md), [`docs/synthid.md`](docs/synthid.md), and [`docs/watermarking-landscape.md`](docs/watermarking-landscape.md). Pixel photo classification is [`docs/photo-classify.md`](docs/photo-classify.md); the separate OpenAI/Google/unknown export-pipeline signal is [`docs/source-classify.md`](docs/source-classify.md). Neither runs inside `identify` or constitutes SynthID detection. Classifier research is split between general [`AI-generated image classifiers`](docs/ai-generated-image-classifiers.md) and [`SynthID source classifiers`](docs/synthid-classifiers.md). Other SynthID campaign logs are [`docs/synthid-detector-research.md`](docs/synthid-detector-research.md) and [`docs/synthid-removal-research.md`](docs/synthid-removal-research.md). The pre-split chronological archive is [`docs/synthid-detector-removal-plan.md`](docs/synthid-detector-removal-plan.md). The benchmark kernel and its pinned local oracles (AudioSeal, Perth, PixelSeal, VideoSeal) cover image, audio, and video watermark cohorts and research studies: [`docs/benchmark-kernel.md`](docs/benchmark-kernel.md).
## Data safety
+95 -37
View File
@@ -3,9 +3,18 @@
Remove AI provenance marks from images and video you generated yourself:
- known visible labels such as the Google Gemini sparkle watermark and vendor text marks;
- invisible pixel watermarks through diffusion regeneration;
- invisible pixel watermarks through direct local-format disruption or diffusion regeneration;
- C2PA, EXIF, XMP, IPTC, and related AI metadata.
| Before | After |
| --- | --- |
| ![Image with a visible Gemini watermark](demo_banana_before.png) | ![Image after visible watermark removal](demo_banana_after.png) |
```bash
uv tool install "remove-ai-watermarks[visible]" # CLI for visible marks and metadata
npx skills add wiltodelta/remove-ai-watermarks # agent skill for Claude Code, Codex, Cursor, and other agents
```
Video support covers provenance identification, complete visible-plus-metadata
cleaning, directory batches, visible Sora, Veo, Seedance, Doubao, Dola,
Hailuo AI, and Kling AI mark removal, and oracle-certified VAE regeneration for video SynthID
@@ -24,9 +33,12 @@ removal.
[![Sponsor](https://img.shields.io/badge/Sponsor-GitHub-db61a2?logo=githubsponsors&logoColor=white)](https://github.com/sponsors/wiltodelta)
[![skills.sh](https://skills.sh/b/wiltodelta/remove-ai-watermarks)](https://skills.sh/wiltodelta/remove-ai-watermarks)
> This project is for lawful use on content you own. It does not target stock
> agency previews or other watermarks that protect third party paid content.
> See [scope, safety, and legal notes](docs/legal-and-safety.md).
> This is a research project on AI provenance signals, for lawful use on content
> you own. It is provided as is, without warranty or liability, and each user is
> responsible for how they use it. It does not target stock agency previews or
> other watermarks that protect third party paid content. Some jurisdictions,
> including China, restrict removing AI labels or supplying tools that do. See
> [scope, safety, and legal notes](docs/legal-and-safety.md).
## Choose what you want to do
@@ -49,7 +61,9 @@ removal.
Microsoft Paint and Photos InvisMark declarations are routed automatically to
pixel regeneration. The `all` command removes both the hidden pixel watermark and
its linked C2PA manifest; metadata stripping alone removes only the manifest.
its linked C2PA manifest; metadata stripping alone removes only the manifest. A
specialized Python API can inspect and disrupt the validated local
`Watermarker.dll` payload without diffusion.
## Installation modes
@@ -57,15 +71,17 @@ its linked C2PA manifest; metadata stripping alone removes only the manifest.
| --- | --- |
| Metadata inspection and stripping | `remove-ai-watermarks` |
| Photograph AI-versus-camera classification | `remove-ai-watermarks[classify]` |
| OpenAI/Google/unknown source-export classification | `remove-ai-watermarks[source-classify]` |
| Visible detection and removal | `remove-ai-watermarks[visible]` |
| Visible video processing | `remove-ai-watermarks[video]` |
| Video SynthID removal | `remove-ai-watermarks[video,diffusion]` |
| Torch-free DWT-DCT detection | `remove-ai-watermarks[detect]` |
| Direct local Paint InvisMark disruption | `remove-ai-watermarks[pixels]` |
| Invisible image removal (needs CUDA) | `remove-ai-watermarks[qwen-zimage]` |
| Every production feature available on the active Python | `remove-ai-watermarks[all]` |
Lower-level and specialized extras include `pixels`, `heif`, `trustmark`,
`migan`, `lama`, `diffusion`, and `classify-onnx`. The
`migan`, `lama`, `diffusion`, `classify-onnx`, and `source-classify`. The
[installation guide](docs/installation.md#feature-extras) documents their exact
dependency composition, Python compatibility, and model requirements.
@@ -93,6 +109,19 @@ remove-ai-watermarks classify image.png
Guide: [photo pixel classification](docs/photo-classify.md).
For a lightweight, abstaining OpenAI/Google/unknown source-export signal after
metadata removal, use the separate Python API. It is not a SynthID detector:
```python
import remove_ai_watermarks as raiw
result = raiw.classify_source("image.png")
print(result.label, result.reason)
```
Install `remove-ai-watermarks[source-classify]`. Guide:
[source-pipeline classification](docs/source-classify.md).
Signed provenance is the supported route for SynthID and `identify` reads it.
There is no local SynthID pixel detector in the package. Research on a
periodic lattice expert is in `scripts/synthid_runtime/` and
@@ -133,6 +162,8 @@ inspection includes the native TC260 `AIGC` tag in
`moov.udta.meta.keys/ilst`, including a `moov` placed after the media payload,
plus the QuickTime-form `meta` variants Doubao's iOS export writes (a bare
`meta` box as a direct `moov` child, and a keyless `hdlr=mdir` metadata list).
Keyed `workflow` and `prompt` entries in the same metadata-list structure are
also detected and removed, including ComfyUI exports.
MKV and WebM inspection reads the normative
`Segment.Tags.Tag.SimpleTag` placement. AVI uses `LIST/INFO/AIGC`, while FLV
uses `script.onMetaData.AIGC`. The non-ISOBMFF formats are remuxed with stream
@@ -183,9 +214,12 @@ preserved through a timestamped in-memory NUT bridge instead of being flattened
to the average frame rate. Non-zero source start timestamps are retained
together with the copied audio offset. The default `--mark auto`
scans all providers in one decode pass and selects the first stable match in
the specificity order shown below. Pass an explicit mark to restrict detection
to one provider.
Sora covers the moving Sora 2 mascot and wordmark. Veo covers both the current
the specificity order shown below. Valid Google AI-video provenance breaks a
Sora/Veo cross-match in favor of Veo when the diamond is nested in the Sora
region or Veo persists through the complete clip while Sora does not.
Pass an explicit mark to restrict detection to one provider.
Sora covers the moving Sora 2 mascot, with or without the wordmark; mascot-only
matches also require the complete two-eye shape. Veo covers both the current
four-point diamond and the legacy `Veo` text. Seedance covers the fixed boxed
`AI` label, Dola covers the fixed `Dola AI` text, Hailuo AI covers the composite
`MINIMAX | hailuo AI` label, and Kling AI covers the bottom-right `KLING AI` or
@@ -211,8 +245,10 @@ is not a product result state. The CLI therefore describes video-pixel
regeneration instead of claiming a per-file SynthID verdict, and reports the
copied audio watermark as `UNVERIFIED`.
For invisible watermark removal, install the `qwen-zimage` extra. **An NVIDIA GPU
is required**: all profiles are CUDA-only, and there is no CPU or MPS fallback.
For invisible watermark removal through the CLI or high-level API, install the
`qwen-zimage` extra. **An NVIDIA GPU is required**: all diffusion profiles are
CUDA-only, and there is no CPU or MPS fallback. The specialized local Paint API
uses the `pixels` extra without CUDA.
```bash
uv tool install --force "remove-ai-watermarks[qwen-zimage]"
@@ -247,11 +283,8 @@ features, and development setup.
### Visible Gemini mark
| Before | After |
| --- | --- |
| ![Image with a visible Gemini watermark](demo_banana_before.png) | ![Image after visible watermark removal](demo_banana_after.png) |
The `after` raster is generated from the tracked `before` raster by the public path:
The `after` raster at the top of this page is generated from the tracked `before`
raster by the public path:
```bash
uv run remove-ai-watermarks visible demo_banana_before.png \
@@ -265,8 +298,8 @@ ControlNet, followed by SAM-masked Z-Image repair of any detected face. The
alternative, `sdxl-zimage`, swaps the global stage for SDXL and keeps the same face
stage. A third profile, `chroma-zimage`, uses the Apache-2.0 Chroma1 global pass
with its own flat vendor floors; see `docs/chroma1-engine-research.md` for the
calibration. `--pipeline auto` picks chroma-zimage for Microsoft
provenance and qwen-zimage otherwise. All are CUDA only.
calibration. `--pipeline auto` picks sdxl-zimage for Google, chroma-zimage for
Microsoft, and qwen-zimage otherwise. All are CUDA only.
```bash
uv tool install --force "remove-ai-watermarks[qwen-zimage]"
@@ -343,16 +376,22 @@ remove-ai-watermarks batch ./images --mode all
Visible mark support includes:
- Google Gemini and Nano Banana visible sparkle watermark;
- Doubao, the Jimeng wordmark and top-left `AI生成` pill, Qwen, Kling AI,
Yuanbao, Baidu, LiblibAI's bottom-center wordmark and compact top-left pill,
and RunningHub labels;
- one calibrated Microsoft top-right white AI-badge variant;
- one calibrated Samsung Galaxy AI label variant.
- Doubao, the Jimeng wordmark and top-left `AI生成` layouts, Qwen, Kling AI,
Yuanbao, Dola, WorkBuddy, Baidu, LiblibAI's bottom-center wordmark and compact
top-left pill, and RunningHub labels;
- calibrated Microsoft top-right white and beige AI-badge layouts;
- calibrated Italian and Korean Samsung Galaxy AI disclosures;
- a generic brand-less bottom-right `AI生成` fallback for OS/gallery-level
AI-edit stamps that carry no vendor wordmark of their own (vivo and Xiaomi
Gallery confirmed); synthetic-only calibration, weaker evidence than the
vendor-tuned detectors above;
- the OpenArt wordmark, placed at the frame center rather than a corner;
uncalibrated (one confirmed real case, no captured corpus).
Metadata and provenance inspection covers C2PA, EXIF, XMP, IPTC, common
generator parameters, China TC260 AIGC labels, and several vendor specific
signals. Optional decoders add support for open DWT-DCT watermarks and Adobe
TrustMark.
generator parameters in image and video containers, China TC260 AIGC labels,
and several vendor specific signals. Optional decoders add support for open
DWT-DCT watermarks and Adobe TrustMark.
The exact support matrix, including important locale and detector limits, lives
in [supported signals](docs/supported-signals.md). The
@@ -369,13 +408,14 @@ Visible removal follows three steps:
Metadata removal uses format aware stripping. JPEG metadata removal preserves
the encoded image scan instead of recompressing it. Native MP4/MOV TC260 values
are blanked without changing box sizes or media offsets. Other supported
containers use their corresponding metadata path.
and keyed generation parameters are blanked without changing box sizes or
media offsets. Other supported containers use their corresponding metadata
path.
Invisible removal is different. It regenerates the image through a diffusion
pipeline to disrupt pixel and frequency domain watermarks. This changes the
image and cannot guarantee that a proprietary verifier will reject every
output.
Invisible removal through the CLI and high-level API regenerates the image through
a diffusion pipeline. Specialized callers can instead decode and disrupt the
positively identified local Microsoft Paint format with much smaller pixel changes.
Neither path can guarantee that every proprietary verifier will reject every output.
See [supported signals](docs/supported-signals.md) and
[known limitations](docs/known-limitations.md) for the full technical boundary.
@@ -442,9 +482,23 @@ Claude Code can add this repository as a plugin marketplace:
/plugin install remove-ai-watermarks@remove-ai-watermarks
```
Codex reads the same skill through [`.codex-plugin/plugin.json`](.codex-plugin/plugin.json).
The skill refuses stock-agency and other third-party paid-asset marks. See
[the agent skill guide](docs/agent-skill.md).
## MCP server
`remove-ai-watermarks mcp` serves `identify`, `remove` and `batch` as Model
Context Protocol tools over stdio, each a thin wrapper around one CLI command:
```json
{"mcpServers": {"remove-ai-watermarks": {"command": "uvx", "args": ["remove-ai-watermarks", "mcp"]}}}
```
See [the MCP server guide](docs/mcp-server.md).
<!-- mcp-name: io.github.wiltodelta/remove-ai-watermarks -->
## ComfyUI
The separate
@@ -456,13 +510,15 @@ invisible removal.
- A missing local signal means unknown, not clean. Proprietary pixel
watermarks may remain after metadata has been stripped.
[What each path leaves behind](docs/known-limitations.md#what-each-path-leaves-behind)
lists, per command, what may remain and how to check it.
- Visible removal reconstructs a small region. Results depend on the background
and selected fill backend.
- Invisible removal changes the whole image and may alter faces, text, or fine
detail.
- Visible video removal recognizes the moving Sora 2 wordmark, the current Veo
diamond plus legacy `Veo` text, the Seedance boxed `AI` label, and the fixed
Doubao, Dola, Hailuo AI, and Kling AI labels. It does not recognize the older Sora Turbo
Doubao, Dola, Hailuo AI, Vidu, and Kling AI labels. It does not recognize the older Sora Turbo
corner swirl or unregistered layouts from those providers.
The classical OpenCV backend can smear structured backgrounds; use MI-GAN or
LaMa when recovery quality matters.
@@ -470,9 +526,10 @@ invisible removal.
The shipped profile is oracle-certified, but no public local decoder can
certify an arbitrary output at runtime. Recheck unusually important outputs
after provider changes.
- Invisible-watermark removal requires CUDA. All profiles refuse any other
device at construction rather than falling back to one that cannot run them.
Visible removal, metadata stripping and `identify` still run anywhere.
- Invisible-watermark removal through the CLI and high-level API requires CUDA.
All diffusion profiles refuse any other device at construction rather than
falling back to one that cannot run them. The specialized local Paint API,
visible removal, metadata stripping and `identify` run without CUDA.
- Provider watermark systems can change. Validate important outputs with the
provider's own verifier when one is available.
@@ -536,7 +593,8 @@ bash maintain.sh
```
See [module internals](docs/module-internals.md) before changing a subsystem
with documented invariants.
with documented invariants. Report vulnerabilities as described in
[SECURITY.md](SECURITY.md).
## License
+25
View File
@@ -0,0 +1,25 @@
# Security policy
## Supported versions
Security fixes go into the latest release. Older releases are not patched;
upgrade through the channel you installed from (PyPI or Homebrew).
## Reporting a vulnerability
Report vulnerabilities privately through
[GitHub private vulnerability reporting](https://github.com/wiltodelta/remove-ai-watermarks/security/advisories/new).
Do not open a public issue for an unpatched vulnerability. Include the affected
version, the command or API call, and a minimal input that reproduces it.
Vulnerabilities in a dependency, such as a CVE in a package from `uv.lock`, can
be reported as a regular issue when the advisory is already public.
## Dependency vulnerabilities
Dependabot raises alerts and update pull requests for `uv.lock` and GitHub
Actions, and CI scans `uv.lock` with
[`uv-secure`](https://github.com/owenlamont/uv-secure) on every push and pull
request. A vulnerable dependency is upgraded to a fixed release; advisories
without one are tracked under
[Known security-gate blocks](docs/development.md#known-security-gate-blocks).
+20
View File
@@ -0,0 +1,20 @@
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24" width="512" height="512" fill="none" stroke="url(#lg)" stroke-width="2" stroke-linecap="round" stroke-linejoin="round">
<!--
The raiw.cc brand mark: the Lucide "sparkle" and "x" glyphs.
Lucide, https://lucide.dev, ISC License, Copyright (c) Lucide Contributors.
Permission to use, copy, modify, and/or distribute this software for any purpose
with or without fee is hereby granted, provided that the above copyright notice
and this permission notice appear in all copies.
-->
<path d="M11.017 2.814a1 1 0 0 1 1.966 0l1.051 5.558a2 2 0 0 0 1.594 1.594l5.558 1.051a1 1 0 0 1 0 1.966l-5.558 1.051a2 2 0 0 0-1.594 1.594l-1.051 5.558a1 1 0 0 1-1.966 0l-1.051-5.558a2 2 0 0 0-1.594-1.594l-5.558-1.051a1 1 0 0 1 0-1.966l5.558-1.051a2 2 0 0 0 1.594-1.594z" fill="url(#lg)" fill-opacity="0.15"/>
<g transform="translate(1 17) scale(0.3)" stroke-width="5">
<path d="M18 6 6 18"/>
<path d="m6 6 12 12"/>
</g>
<defs>
<linearGradient id="lg" x1="0" y1="0" x2="24" y2="24">
<stop stop-color="#a78bfa"/>
<stop offset="1" stop-color="#06b6d4"/>
</linearGradient>
</defs>
</svg>

After

Width:  |  Height:  |  Size: 1.2 KiB

+13 -2
View File
@@ -10,6 +10,11 @@ data/
visible/ Per-mark example gallery: one synthetic canonical example per
registered mark plus documented provider originals where available
(see fixtures/visible/README.md)
synthetic/ Frozen synthetic renders that unit tests stamp onto frames, each
produced by the script named in the test that loads it
captures/
2026-09/ Provider outputs from the maintainer's own accounts, stored as
served, indexed by manifest.csv (see its README)
calibration/
<vendor>/ Minimal controlled inputs needed to rebuild detector assets
synthid/
@@ -51,9 +56,15 @@ evaluation outputs outside the repository.
`evaluations/engine-selection/` is the bounded exception for ORIGINAL study
inputs: its manifest tracks a prompt-matched OpenAI/Meta content matrix, not
generated model outputs or watermark-oracle evidence.
6. Keep third-party fixture license notices in `licenses/`, outside directories
6. Put provider captures that no test reads in `captures/<yyyy-mm>/`, with a
`manifest.csv` row per capture. A capture that is also a fixture is stored
once, in `fixtures/`, and its manifest row points there. Request a new
capture only for a service x vendor pair not yet captured, or for a
service's own model: another version of a known pair adds no provenance
evidence.
7. Keep third-party fixture license notices in `licenses/`, outside directories
that tests enumerate as media inputs.
7. Runtime detector assets belong in `src/remove_ai_watermarks/assets/`.
8. Runtime detector assets belong in `src/remove_ai_watermarks/assets/`.
Unregistered research candidates belong in
`scripts/assets/visible-mark-candidates/` so they are not shipped in the
wheel.
+44
View File
@@ -0,0 +1,44 @@
# Provider captures, September 2026
Original outputs downloaded from the maintainer's own accounts between
2026-09-23 and 2026-09-25 and cleared for publication by the maintainer. The
services are the Gemini API, xAI Grok, Vidu, Wan, Apple Image Playground,
YouTube (re-encodes of our own uploads), and the paid Higgsfield, Runway and
Dreamina plans. Every prompt is a neutral coffee-mug scene; Higgsfield
Genjutsu and the video-edit samples take our own Higgsfield outputs as input.
Files are stored byte-for-byte as served. Nothing is re-encoded, because the
provenance under study (C2PA, TC260 labels, `hf-job-id` chunks) lives in the
container bytes.
`manifest.csv` lists every capture once, including the ones that are already
test fixtures: those rows point at their `data/fixtures/` path instead of a
second copy (`stored` is `existing`). Columns:
| Column | Meaning |
| --- | --- |
| `sha256` | Digest of the stored file |
| `path` | Canonical repository path |
| `stored` | `new` for files in this directory, `existing` for a fixture already tracked |
| `service` | Service the file was downloaded from |
| `source_name` | Local capture name, which names the model |
| `captured` | Capture date |
| `ai_from_metadata`, `platform` | `identify` (images) or `identify_video` (videos) verdict from metadata only, at capture time |
What each service does to the upstream provenance, and the per-model
findings, are summarized in the live-captures table of
[`docs/watermarking-landscape.md`](../../../docs/watermarking-landscape.md).
The `google-photos/` files are the maintainer's own iPhone photos edited in
Google Photos on iOS (an Ask edit replacing a dog with a cat, an eraser edit, and
two other AI edits), published unmodified with their EXIF GPS position by the
maintainer's decision on 2026-09-25. Google's checker in Gemini found SynthID in
all four with the metadata stripped. The Apple Clean Up photo is not stored.
The `google-photos-web/` files are a negative control from the Google Photos web
editor (2026-09-26): one of the maintainer's photos, downloaded untouched and after
Enhance, Sky (Vivid) and a square crop. The web editor offers no generative tool and
writes no Content Credentials, so none of the four carries C2PA, IPTC or an AI
credit, and Google's checker in Gemini found no SynthID in any of them (three
explicit negatives; the crop drew a reply that did not name SynthID and is recorded
as indeterminate).
- License: repository license; generated and explicitly cleared by the maintainer
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