There is a known tension between the need to analyze personal data to drive business and privacy concerns. Many data protection regulations, including the EU General Data Protection Regulation (GDPR) and the California Consumer Protection Act (CCPA), set out strict restrictions and obligations on the collection and processing of personal data.
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 phone numbers, IMSI numbers, SIM identifiers, mobile network codes. 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.
Replace is recommended for this pain point: substituting phone numbers with format-valid but non-functional alternatives maintains data structure while removing the PII anchor. Hash provides an alternative — deterministic hashing enables referential integrity across phone-linked records. For scenarios requiring reversibility, Encrypt (AES-256-GCM) enables authorized recovery of original values.
The local sidecar REST API (port 5002-5003) provides programmatic access to Presidio detection for local development workflow integration.
This pain point intersects with GDPR Article 9 special category data in sensitive contexts, ePrivacy Directive.
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) |