I Built an Open-Source Toolkit for AI Watermark & Provenance Forensics
I Built an Open-Source Toolkit for AI Watermark & Provenance Forensics AI-generated content is becoming increasingly common. But when you receive an AI-generated image, document, or other digital artifact, an interesting question remains: What can we actually learn from the file itself? There may be metadata, provenance information, invisible Unicode characters, statistical signals, or other…
ClaudeMark is an open-source toolkit designed for AI watermark and provenance forensics. It helps analyze digital artifacts like images, documents, and other files to uncover hidden metadata, statistical signals, invisible Unicode characters, and other potential AI-generated markers. The goal isn't to definitively prove AI involvement, but rather to provide forensic evidence to support or refute such claims.
ClaudeMark analyzes various signals, including statistical AI patterns, invisible Unicode analysis, and metadata/provenance information. Statistical AI signals look for unusual patterns that may indicate AI generation, but these are treated as indicators rather than definitive proof. Invisible Unicode analysis examines text for characters that aren't immediately visible, which can help uncover hidden text.
Metadata and provenance layers, such as EXIF data, XMP, and C2PA, are also inspected to understand the file's origins and history.
The toolkit includes security auditing checks to ensure files aren't carrying dangerous structures, and it offers sanitization features to remove selected metadata and provenance artifacts where supported. ClaudeMark emphasizes a local-first approach, meaning files remain on the user's machine throughout the analysis process, with no external data transmission.
The project is designed as modular components rather than a single monolithic detector. It provides a CLI and API for developers to integrate and extend with additional detectors and integrations. Open-source contributions are encouraged, allowing users to audit detection logic, reproduce results, add new detectors, and report edge cases.
ClaudeMark is not meant to be a foolproof AI authorship detector, as AI detection is inherently challenging. It serves as a forensic and analysis toolkit to help users understand what's present in their files before deciding on any cleaning or removal actions. The author invites contributions and feedback from developers working on AI content, provenance, digital forensics, privacy, and developer security tooling.
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