Format-preserving tokenization

Databunker Pro provides two distinct tokenization engines, each designed for a different job:

PII tokenization (UserCreate / UserGet) — stores a complete user profile (JSON, N fields) as one encrypted record and returns a single UUID token representing the whole profile. Builds secure hashed search indexes over email, phone, login, and a custom field for efficient lookups. This is the user-table replacement pattern; see the PII Vault page for full detail.
Format-preserving tokenization (TokenCreate / TokenGet) — tokenizes individual sensitive values such as credit-card numbers (Luhn-valid) and Unix timestamps. Returns both a UUID and a format-preserving token in the same response. This is the PCI / single-value pattern, covered in the rest of this page.

Both engines share the same vault, encryption, multi-tenancy, and access-control layers — so the same auditability, key management, and CRBAC policies apply to either flow. Databunker Pro was built with the latest data privacy requirements in mind, such as data minimization, and is engineered to handle millions of data tokenization requests. The API supports bulk tokenization for efficient batch operations.

Supported data types

Original Record Type	Format Preservation	Generated Token Format
Credit Card Number	✅ (with Luhn check)	Format-preserving or UUID token
Unix timestamp record	✅	Format-preserving or UUID token
Text string	❌	UUID token

Key features

Automatic Expiration

In Databunker Pro, expiration allows you to set a lifespan for sensitive data tokens, ensuring they automatically expire after a defined period. Use slidingtime for a relative window (e.g. 30d, 1h) or finaltime for an absolute Unix-timestamp expiry.

// Set a 30-day sliding expiration for a tokenized record
{
  "tokentype": "creditcard",
  "record": "4532015112830366",
  "slidingtime": "30d"
}

Unique Record Support

This unique flag is used for data deduplication. It ensures that each record is saved only once, and the same token value is returned for identical records. If the original record has an expiration flag set, its expiration countdown will be reset from the beginning.

// Same input generates same token when enabled
{
  "tokentype": "creditcard",
  "record": "4532015112830366",
  "unique": true
}

Dual Token Generation

By default, Databunker Pro generates two tokens: one in UUID format and another in a format-preserving manner.

// Example response for credit card tokenization
{
  "status": "ok",
  "tokenuuid": "550e8400-e29b-41d4-a716-446655440000",
  "tokenbase": "4111111111111111" // Format-preserving token (Luhn-valid, same length)
}

Getting started

# Example API call for tokenization
curl -X POST https://databunker.pro/v2/TokenCreate \
  -H "X-Bunker-Token: <access-token>" \
  -H "X-Bunker-Tenant: <tenant-name>" \
  -H "Content-Type: application/json" \
  -d '{
    "tokentype": "creditcard",
    "record": "4532015112830366",
    "slidingtime": "30d",
    "unique": true
  }'

Output:

{
  "status": "ok",
  "tokenuuid": "550e8400-e29b-41d4-a716-446655440000",
  "tokenbase": "4111111111111111" // Format-preserving token (Luhn-valid, same length)
}

Bulk tokenization

For batch workloads — migrations, nightly imports, mass detokenization — Databunker Pro creates, reads, and deletes many tokens in a single call.

Create tokens in bulk

TokenCreateBulk takes an array of records and returns a token pair for each. slidingtime / finaltime and unique apply to the whole batch.

curl -X POST https://databunker.pro/v2/TokenCreateBulk \
  -H "X-Bunker-Token: <access-token>" \
  -H "X-Bunker-Tenant: <tenant-name>" \
  -H "Content-Type: application/json" \
  -d '{
    "records": [
      { "tokentype": "creditcard", "record": "4532015112830366" },
      { "tokentype": "creditcard", "record": "5467047429390590" }
    ],
    "unique": true
  }'

Output:

{
  "status": "ok",
  "created": [
    { "tokenuuid": "550e8400-e29b-41d4-a716-446655440000", "tokenbase": "4111111111111111", "record": "4532015112830366", "tokentype": "creditcard" },
    { "tokenuuid": "6ba7b810-9dad-11d1-80b4-00c04fd430c8", "tokenbase": "5500005555555559", "record": "5467047429390590", "tokentype": "creditcard" }
  ]
}

Read and delete in bulk

Bulk read and delete return or destroy plaintext for many records at once, so they require a short-lived unlock UUID as an extra authorization step. Call BulkListUnlock first, then pass the returned unlockuuid to BulkListTokens or BulkDeleteTokens along with the token UUIDs.

# 1. Obtain an unlock UUID
curl -X POST https://databunker.pro/v2/BulkListUnlock \
  -H "X-Bunker-Token: <access-token>" \
  -H "X-Bunker-Tenant: <tenant-name>"
# -> { "status": "ok", "unlockuuid": "e1f2a3b4-..." }

# 2. Retrieve the original values
curl -X POST https://databunker.pro/v2/BulkListTokens \
  -H "X-Bunker-Token: <access-token>" \
  -H "X-Bunker-Tenant: <tenant-name>" \
  -H "Content-Type: application/json" \
  -d '{
    "unlockuuid": "e1f2a3b4-...",
    "tokens": ["550e8400-e29b-41d4-a716-446655440000", "6ba7b810-9dad-11d1-80b4-00c04fd430c8"]
  }'
# -> { "status": "ok", "rows": [ { "tokenuuid": "...", "tokenbase": "...", "record": "...", "tokentype": "creditcard" }, ... ] }

# 3. Delete tokens
curl -X POST https://databunker.pro/v2/BulkDeleteTokens \
  -H "X-Bunker-Token: <access-token>" \
  -H "X-Bunker-Tenant: <tenant-name>" \
  -H "Content-Type: application/json" \
  -d '{
    "unlockuuid": "e1f2a3b4-...",
    "tokens": ["550e8400-e29b-41d4-a716-446655440000", "6ba7b810-9dad-11d1-80b4-00c04fd430c8"]
  }'
# -> { "status": "ok", "deleted": 2 }

Compliance and scale

Format-preserving tokenization addresses three concerns at once:

Concern	What tokenization gives you
Privacy & compliance	Supports GDPR data minimization and reduces PCI DSS scope — real card numbers never reach your application databases, logs, or analytics systems.
Legacy compatibility	Tokens keep the original format and validation rules (e.g. the Luhn check for cards), so they drop into existing schemas, validators, and downstream systems without changes.
Scale	Data partitioning and bulk endpoints handle millions of records at high throughput.

Get started

Installation

Administration

Concepts

Comparisons

How-tos

Developer tools

Format-preserving tokenization

Supported data types

Key features

Automatic Expiration

Unique Record Support

Dual Token Generation

Getting started

Bulk tokenization

Create tokens in bulk

Read and delete in bulk

Compliance and scale

​Supported data types

​Key features

​Automatic Expiration

​Unique Record Support

​Dual Token Generation

​Getting started

​Bulk tokenization

​Create tokens in bulk

​Read and delete in bulk

​Compliance and scale

Supported data types

Key features

Automatic Expiration

Unique Record Support

Dual Token Generation

Getting started

Bulk tokenization

Create tokens in bulk

Read and delete in bulk

Compliance and scale