!PII Filter Node Module

!CI
!License: MIT

A library for detecting, parsing, and removing personally identifiable information from strings and objects.

!PII replaced with placeholders

Scenarios

We hope that this software can be useful in some of the following scenarios:
- privacy, security, fraud-detection, and data-auditing
- anonymizing data for research, marketing and machine learning
- accessibility and online guidance
- word tagging and word spotting
- designing chatbots

Languages

pii-filter currently supports the following languages and PII:
- Dutch
- First Names
- Family Names
- Pet Names
- Medicine Names
- Phone Numbers
- Email Addresses
- Dates

Installing

You can add the pii-filter npm package to your project by running:
> npm install --save-dev pii-filter

Documentation

The docs can be read here.

Examples

Sanitizing strings:
``TypeScript
import * as pf from 'pii-filter';

const pii_filter = pf.make_pii_classifier(pf.languages.nl.make_lm());
const raw_str = 'Hallo Johan, mijn 06 is 0612345678, tot morgen.';
const sanitized_str = pii_filter.sanitize_str(raw_str, true);

console.log(sanitized_str);

// output:
'Hallo {first_name}, mijn 06 is {phone_number}, tot morgen.'
`
Sanitizing objects:
`TypeScript
import * as pf from 'pii-filter';

const pii_filter = pf.make_pii_classifier(pf.languages.nl.make_lm());
const obj =
{
message: 'Wilma de Vries, 20 november 1964',
detail: 'Werking Paracetamol bij gebruik medicatie'
};
const sanitized_obj = pii_filter.sanitize_obj(obj, true, false);

console.dir(sanitized_obj);

// output:
{
message: '{first_name} {family_name}, {date}',
detail: 'Werking {medicine_name} bij gebruik medicatie'
}
`
Parsing PII:
`TypeScript
import * as pf from 'pii-filter';

const pii_filter = pf.make_pii_classifier(pf.languages.nl.make_lm());
const raw_str = 'Hallo Johan, mijn e-mail is test@test.com en mijn nummer is 0612345678, tot dan.';
const results = pii_filter.classify(raw_str);

for (let pii of results.pii)
console.dir(pii);

// output:
{
value: 'Johan',
type: 'first_name',
confidence: 0.755,
severity: 0.4539742200500001,
start_pos: 6,
end_pos: 11
}
{
value: 'test@test.com',
type: 'email_address',
confidence: 1,
severity: 0.2,
start_pos: 28,
end_pos: 41
}
{
value: '0612345678',
type: 'phone_number',
confidence: 0.8512500000000001,
severity: 0.35,
start_pos: 60,
end_pos: 70
}
``

Main repository

For more information and access to used the datasets check out the main repository.