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Co-authored-by: Calvin Leung Huang <cleung2010@gmail.com>

Co-authored-by: Calvin Leung Huang <cleung2010@gmail.com>
2020-11-17 16:56:30 -08:00

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---
layout: docs
page_title: Transform - Secrets Engines - Tokenization
sidebar_title: Tokenization Transform <sup>ENTERPRISE</sup>
description: >-
More information on the Tokenization transform.
---
# Tokenization Transform
Not to be confused with Vault tokens, [Tokenization](transform/tokenization) exchanges a
sensitive value for an unrelated value called a *token*. The original sensitive
value cannot be recovered from a token alone, they are irreversible. Instead, unlike format preserving encryption, tokenization is stateful. To
decode the original value, the token must be submitted to Vault where it is
retrieved from a cryptographic mapping in storage.
## Operation
On encode, Vault generates a random, signed token and stores a mapping of a
version of that token to encrypted versions of the plaintext and metadata, as
well as a fingerprint of the original plaintext which facilitates the `tokenized`
endpoint that lets one query whether a plaintext exists in the system.
Depending on the mapping mode, the plaintext may be decoded only with posession
of the distributed token, or may be recoverable in the export operation. See
[Security Considerations](#security-considerations) for more.
## Performance Considerations
### Builtin (Internal) Store
As tokenization is stateful, the encode operation necessarily writes values to
storage. By default, that storage is the Vault backend store itself. This
differs from some secret engines in that the encode and decode operations require
an access of storage per operation. Other engines use storage for configuration
but can process operations largely without accessing any storage.
Since these operations involve writes to storage, and therefore must be performed
on primary nodes, the scalability of the encode operation is limited by the
primary's storage performance.
Additionally, using internal storage, since writes must be performed on primary
nodes, the scalability of the encode operation will be limited by the performance
of the primary and its storage subsystem. All other operations can be performed
on secondaries.
Finally, due to replication, writes to the primary may take some time to reach
secondaries, so other read operations like decode or metadata may not succeed on
the secondaries until this happens. In other words, tokenization is eventually
consistent.
### External Storage
All nodes (except DRs) can participate in all operations using external storage, but one must take care
to monitor and scale the external storage for the level of traffic experienced.
The storage schema is simple however and well known approaches should be effective.
## Security Considerations
The goal of Tokenization is to let end users' devices store the token rather than
their sensitive values (such as credit card numbers) and still participate in
transations where the token is a standin for the sensitive value. For this reason
the token Vault generates is completely unrelated (e.g. irreversible) to the
sensitive value.
Furthermore, the Tokenization transform is designed to resist a number of attacks
on the values produced during encode. In particular it is designed so that
attackers cannot recover plaintext even if they steal the tokenization values
from Vault itself. In the default mapping mode,
even stealing the underlying transform key does not allow them to recover
the plaintext without also posessing the encoded token. An attacker must have
gotten access to all values in the construct.
In the `exportable` mapping mode however, the plaintext values are encrypted
in a way that can be decrypted within Vault. If the attacker posesses the
transform key and the tokenization mapping values, the plaintext can be
recovered. This mode is available for the case where operators prioritize the
ability to export all of the plaintext values in an emergency, via the export
operation.
### Metadata
Since tokenization isn't format preserving and requires storage, one can associate
arbitrary metadata with a token. Metadata is considered less sensitive than the
original plaintext value. As it has it's own retrieval endpoint, operators can
configure policies that may allow access to the metadata of a token but not
its decoded value to enable workflows that operate just on the metadata.
## TTLs and Tidying
By default, tokens are long lived, and the storage for them will be maintained
indefinitely. Where there is a concept of time-to-live, it is strongely encouraged
that the tokens be generated with a TTL. For example, as credit cards
have an expiration date, it is recommended that tokenizing a credit card
primary account number (PAN) be done with a TTL that corresponds to the time
after which the PAN is invalid.
This allows such values to be *tidied* and removed from storage once expired.
Tokens themselves encode the expiration time, so decode and other operations
can immediately reject the operation when presented with an expired token.
## External Storage
### SQL Stores
Currently only PostgreSQL is supported as an external storage backend for tokenization.
The [Schema Endpoint](../../../api-docs/secret/transform#create-update-store-schema) may be used to initialize and upgrade the necessary
database tables. Vault uses a schema versioning table to determine if it needs
to create or modify the tables when using that endpoint. If you make changes to
those tables yourself, the automatic schema management may become out of sync
and may fail in the future.
## Learn
Refer to [Tokenize Data with Transform Secrets
Engine](https://learn.hashicorp.com/tutorials/vault/tokenization) for a
step-by-step tutorial.