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LexGuard
PII Detection and Correlation Engine for Automated Data Audits
Python 3.11+Typerpydanticpython-magicregex
The Problem It Solves
- Slow manual data audits and generic tools with high false-positive rates.
- Fragmented risk view: evaluates real exposure, not just regex matches.
- Identification of aggregated risks through cross-PII correlation (multiple sensitive data types coexisting).
Key Features
- CLI-first: Designed to run in pipelines, automation scripts, and unattended environments.
- Rules first, AI as support: Deterministic rules and algorithmic validations (Luhn, prefixes, entropy). AI as a secondary layer to reduce false positives.
- Explainable risk: Every finding includes a clear breakdown of why it’s considered risky and its confidence level.
- Fail-safe by default: When ambiguous, classifies as UNCERTAIN rather than generating critical false positives.
- Current detection: Colombian ID (Cédula de Ciudadanía), Colombian mobile phone, email, credit cards, and cross-PII correlation.
- Modular architecture: Extensible deterministic pipeline: ingestion → detection → validation → scoring → correlation → report.
Technical Decision
- Architecture based on deterministic pipeline to ensure reproducibility and traceability.
- Not a DLP or SIEM: it’s an audit and scanning tool that identifies exposure, doesn’t remediate it.
- Region-specific algorithmic validations (Colombia) with extensibility options.
- Apache-2.0 license for enterprise and collaborative use.
- Designed for compliance with Ley 1581 de Colombia.