There is a significant conceptual gap between legal and mathematical thinking around data privacy. The effect is uncertainty as to which technical offerings meet legal standards. This uncertainty is exacerbated by a litany of successful privacy attacks demonstrating that traditional statistical disclosure limitation techniques often fall short of the privacy envisioned by regulators.
This research paper examines a critical privacy challenge related to LINKABILITY — the ability to connect two pieces of information to the same person.
anonym.plus addresses this through 200+ entity types processed 100% locally via Presidio 2.2.357 sidecar — detection and anonymization that never leaves the device.
The ability to connect two pieces of information to the same person. This is the foundational operation that makes PII dangerous. Nearly every pain point is an expression of linkability being created, exploited, or failing to be broken.
Irreducible truth: You cannot have useful data that is completely unlinkable AND completely useful. The very features that make data informative make it linkable. This is not a bug — it is information theory. The information content of a dataset and its linkability are the same property measured differently.
anonym.plus identifies 200+ entity types including names, email addresses, phone numbers, social media handles, organizational affiliations. The local Presidio 2.2.357 + spaCy 3.8.11 architecture uses Presidio 2.2.357 deterministic recognizers with 121 built-in presets for structured identifiers and spaCy 3.8.11 with 23 language models, all running locally via FastAPI sidecar for contextual references.
Redact is recommended for this pain point: removing contact identifiers from documents prevents construction of social graphs from document collections. Replace provides an alternative — substituting names and identifiers with type labels preserves document structure while breaking the social graph. For scenarios requiring reversibility, Encrypt (AES-256-GCM) enables authorized recovery of original values.
The Tauri 2.x desktop application (Rust + React) processes 7 document formats (PDF, DOCX, XLSX, TXT, CSV, JSON, XML) plus images (Tesseract OCR). AES-256-GCM vault with Argon2id protects all stored data.
This pain point intersects with GDPR Article 5(1)(c) data minimization, Article 25 data protection by design.
anonym.plus’s GDPR (data never leaves device), HIPAA (local processing) compliance coverage, combined with 100% local — data never leaves device hosting, provides documented technical measures organizations can reference in their compliance documentation and regulatory submissions.
| Specification | Value |
|---|---|
| App Version | v8.10.5 |
| Entity Types | 200+ built-in, up to 50 custom |
| Detection Engine | Presidio 2.2.357 + spaCy 3.8.11 (23 models) |
| Languages | 48 UI, 23 NLP models |
| Document Formats | PDF, DOCX, XLSX, TXT, CSV, JSON, XML + Image OCR |
| Anonymization Methods | Replace, Redact, Mask, Hash (SHA-256/512/MD5), Encrypt (AES-256-GCM) |
| Architecture | Tauri 2.x (Rust + React) + FastAPI sidecar (~370 MB) |
| Platforms | Win/Mac/Linux |
| Licensing | Ed25519 signed, machine-fingerprinted, max 5 machines |
| Processing | 100% local — data never leaves device |
| Compliance | GDPR, HIPAA (data residency guaranteed by local processing) |