Tools

PII entity types Redactly detects

Forty entity types across twelve groups. Each one has its own page with the detection method, a live demo, and a request example. Send text and every type is redacted; pass entities to narrow it down.

Contact details

Ways to reach a person: addresses, email, phone, IP, postal codes.

• Email addressesRedact email addresses from text, JSON, and CSV with one HTTP call. Returns exact character offsets and keeps your structure intact.
• Phone numbersRedact phone numbers in national and international formats from text, JSON, and CSV. Model-gated, so dates and ID numbers are not mistaken for numbers.
• Street addressesRedact postal addresses from free text and structured payloads, including partial street names the model only half-captures.
• Postal codesRedact ZIP and postcode values in US 5-digit, ZIP+4, and UK formats from text and tabular data.
• IP addressesRedact IPv4 addresses from access logs, error traces, and analytics exports with a format check per octet.

Credentials and secrets

Keys and tokens that grant access if they leak.

• API keysRedact AWS, OpenAI, Anthropic, GitHub, Google, Slack, and Hugging Face API keys from logs and pasted text.
• JSON Web TokensRedact JWTs from debug output, HAR files, and support tickets before they leave your environment.
• PasswordsRedact plaintext passwords from configuration dumps, tickets, and transcripts before they are shared.
• Private keysRedact PEM private keys, header and body, from logs and pasted configuration before they are stored or shared.
• Database connection stringsRedact connection strings containing embedded credentials for Postgres, MySQL, MongoDB, Redis, and AMQP.

Developer identifiers

Identifiers tied to a developer account or session.

• Device identifiersRedact device IDs and installation identifiers from analytics payloads and crash reports.
• Login credentialsRedact username and password pairs from pasted transcripts, config files, and support threads.

Device identifiers

Hardware addresses and IMEIs that persist across reinstalls.

• IMEI numbersRedact 15-digit IMEI numbers from warranty claims, device logs, and repair tickets.
• MAC addressesRedact hardware MAC addresses from network logs, DHCP dumps, and device inventories.

Financial data

Cards, accounts, IBANs, wallets, and monetary amounts.

• Credit card numbersRedact card numbers from text and JSON with Luhn validation, so only real card numbers are flagged and order IDs are left alone.
• IBANsRedact International Bank Account Numbers with mod-97 validation across all SEPA countries.
• SWIFT/BIC codesRedact SWIFT and BIC codes from payment instructions without flagging every all-caps word.
• Bank account numbersRedact domestic bank account numbers that carry no checksum and no fixed format.
• Crypto wallet addressesRedact Bitcoin and Ethereum wallet addresses from text, JSON, and support transcripts.
• Monetary amountsRedact prices, salaries, balances, and invoice totals in multiple currencies from text and tabular data.

Health data

Records, plan IDs, conditions, and medications.

• Medical record numbersRedact MRNs and patient record identifiers from clinical notes, referrals, and export files.
• Health plan identifiersRedact health plan and insurance member IDs from claims, eligibility files, and billing exports.
• Medical conditionsRedact diagnoses and medical conditions from clinical notes, claim narratives, and support transcripts.
• MedicationsRedact drug names and prescriptions from clinical text and support transcripts.

Identity and government IDs

Names and the numbers governments issue to identify people.

• Social Security numbersRedact US Social Security numbers in 3-2-4 format from text, JSON, and CSV. Format-matched, with no model dependency.
• Passport numbersRedact passport numbers from travel documents, onboarding packets, and KYC notes.
• National ID numbersRedact national identity numbers such as NIN, DNI, PESEL, and similar government identifiers.
• Driver's licence numbersRedact driver's licence numbers from onboarding forms, insurance claims, and fleet records.
• Tax identification numbersRedact TINs, EINs, and equivalent tax identifiers from invoices, payroll files, and vendor records.
• Dates of birthRedact dates of birth in numeric, ISO, and written month formats from text and tabular data.
• Person namesRedact personal names from free text, including partial names the model only half-captures.

Legal identifiers

Case numbers that link a document to a proceeding.

• Case numbersRedact legal case and docket numbers from filings, correspondence, and legal-ops exports.

Location data

Coordinates precise enough to find a person.

• GPS coordinatesRedact latitude and longitude pairs from delivery records, field-service notes, and mobile telemetry.

Online presence

Profile URLs and usernames.

• Profile URLsRedact URLs that point at a person, such as profile, portfolio, and social links.
• UsernamesRedact handles and account usernames from transcripts, exports, and community data.

Organisations

Employers and counterparties whose identity is commercially sensitive.

• Company namesRedact organisation and employer names where the counterparty itself is confidential.

Special-category data

The Article 9 categories GDPR treats as most sensitive.

• Health statusRedact statements about a person's health, disability, or medical status from free text.
• Religious beliefsRedact references to religious belief or affiliation from HR records, applications, and free text.
• Political opinionsRedact political opinions and affiliations from free text, surveys, and HR records.
• Sexual orientationRedact references to sexual orientation from free text and HR records.