guillaume
759fd33acf
Rename remove-claude-marks to remove-ai-marks, add container metadata support (SVG/PDF/DOCX/ODT/HTML/MD), Layer B rewrite hook, unified file CLI, and multi-vendor documentation for the first public release.
1.8 KiB
Mark classes
1. Edit-based text (Unicode / rules)
Invisible or near-invisible characters, exotic spaces, bidi controls, tag characters, synonym tables.
| Inspect kinds (Layer A) | Examples |
|---|---|
zwj_family |
ZWSP, ZWNJ, ZWJ, WJ, BOM |
bidi |
LRE/RLO/LRI/… |
tag_chars |
U+E0001–U+E007F |
variation_selector |
VS1–VS256 |
space |
NBSP, em space, ideographic space |
confusable |
Cyrillic/fullwidth Latin (aggressive) |
Removal: clean_text.py / Layer A — deterministic, verifiable.
Maps to Nature paper “edit-based watermarking.”
2. Generative / statistical text (token sampling)
Bias next-token sampling toward a pseudo-random green list / score (Kirchenbauer, SynthID-Text / Tournament sampling, etc.). Signal lives in word choice, not metadata.
Removal: Layer B rewrite (paraphrase → back-translate → structural). Best-effort; no gold cert without vendor detector/key.
Maps to Nature paper primary method (SynthID-Text).
3. Data-driven / backdoor
Model trained or fine-tuned so trigger prompts produce marked or identifiable behavior.
Out of scope for this skill (model-side).
4. File provenance metadata (C2PA / EXIF / XMP / props)
Signed Content Credentials and AI generator tags in containers.
| Format | Support |
|---|---|
| PNG / JPEG | Full strip (stdlib + optional exiftool) |
| SVG | Drop metadata/XMP blocks |
| Prefer exiftool; degraded stdlib XMP strip | |
| DOCX / ODT | Scrub zip XML props / customXml |
| HTML | Meta generator / JSON-LD / data-ai* |
| Markdown | YAML frontmatter AI keys |
Removal: clean_file.py / clean_image.py — usually verifiable by re-inspect.
5. Pixel-domain image watermarks
Invisible image marks (e.g. SynthID for images). Out of scope.