Pydantic-Vault

Python versions

A simple extension to Pydantic BaseSettings that can retrieve secrets stored in Hashicorp Vault

With Pydantic and Pydantic-Vault, you can easily declare your configuration in a type-hinted class, and load configuration from environment variables or Vault secrets. Pydantic-Vault will work the same when developing locally (where you probably login with the Vault CLI and your own user account) and when deploying in production (using a Vault Approle or Kubernetes authentication for example).

Installation
Getting started
Documentation
Logging
Examples
Known limitations
Inspirations
License

Installation

pip install pydantic-vault

# or if you use Poetry or Pipenv
poetry add pydantic-vault
pipenv install pydantic-vault

Getting started

With Pydantic BaseSettings class, you can easily "create a clearly-defined, type-hinted application configuration class" that gets its configuration from environment variables. Starting with Pydantic 1.8, custom settings sources are officially supported. This is where Pydantic-Vault steps in, allowing you to load configuration values from Hashicorp Vault secrets. It will work the same when developing locally (where you probably login with the Vault CLI and your own user account) and when deploying in production (using a Vault Approle or Kubernetes authentication for example).

You can create a normal BaseSettings class, and define the customise_sources() method to load secrets from your Vault instance using the vault_config_settings_source function:

import os

from pydantic import BaseSettings, Field, SecretStr
from pydantic_vault import vault_config_settings_source

class Settings(BaseSettings):
    # The `vault_secret_path` is the full path (with mount point included) to the secret
    # The `vault_secret_key` is the specific key to extract from a secret
    username: str = Field(
        ..., vault_secret_path="secret/data/path/to/secret", vault_secret_key="my_user"
    )
    password: SecretStr = Field(
        ...,
        vault_secret_path="secret/data/path/to/secret",
        vault_secret_key="my_password",
    )

    class Config:
        vault_url: str = "https://vault.tld"
        vault_token: SecretStr = os.environ["VAULT_TOKEN"]
        vault_namespace: str = "your/namespace"  # Optional, Pydantic-Vault supports Vault namespaces (for Vault Enterprise)

        @classmethod
        def customise_sources(
            cls,
            init_settings,
            env_settings,
            file_secret_settings,
        ):
            # This is where you can choose which settings sources to use and their priority
            return (
                init_settings,
                env_settings,
                vault_config_settings_source,
                file_secret_settings,
            )

settings = Settings()
# These variables will come from the Vault secret you configured
settings.username
settings.password.get_secret_value()

# Now let's pretend we have already set the USERNAME in an environment variable
# (see the Pydantic documentation for more information and to know how to configure it)
# With the priority order we defined above, its value will override the Vault secret
os.environ["USERNAME"] = "my user"

settings = Settings()
settings.username  # "my user", defined in the environment variable
settings.password.get_secret_value()  # the value set in Vault

Documentation

`Field` additional parameters

You might have noticed that we import Field directly from Pydantic. Pydantic-Vault doesn't add any custom logic to it, which means you can still use everything you know and love from Pydantic.

The additional parameters Pydantic-Vault uses are:

Parameter name	Required	Description
`vault_secret_path`	Yes	The path to your secret in Vault This needs to be the full path to the secret, including its mount point (see examples below)
`vault_secret_key`	No	The key to use in the secret If it is not specified the whole secret content will be loaded as a dict (see examples below)

For example, if you create a secret database/prod with a key password and a value of a secret password in a KV v2 secret engine mounted at the default secret/ location, you would access it with

password: SecretStr = Field(
    ..., vault_secret_path="secret/data/database/prod", vault_secret_key="password"
)

Configuration

You can configure the behaviour of Pydantic-Vault in your Settings.Config class, or using environment variables:

Settings name	Type	Required	Environment variable	Description
`customise_sources()`		Yes	N/A	You need to implement this function to use Vault as a settings source, and choose the priority order you want
`vault_url`	`str`	Yes	`VAULT_ADDR`	Your Vault URL
`vault_namespace`	`str \\| None`	No	`VAULT_NAMESPACE`	Your Vault namespace (if you use one, requires Vault Enterprise)
`vault_auth_mount_point`	`str \\| None`	No	`VAULT_AUTH_MOUNT_POINT`	The mount point of the authentication method, if different from its default mount point
`vault_certificate_verify`	`str \\| bool \\| None`	No	`VAULT_CA_BUNDLE`	The path to a CA bundle validating your Vault certificate, or `False` to disable verification (see hvac docs)

Environment variables override what has been defined in the Config class.

You can also configure everything available in the original Pydantic BaseSettings class.

Authentication

Pydantic-Vault supports the following authentication method (in descending order of priority):

Pydantic-Vault tries to be transparent and help you work, both during local development and in production. It will try to find the required information for the first authentication method, if it can't it goes on to the next method, until it has exhausted all authentication methods. In this case it gives up and logs the failure.

You only need to know this order of priority if you specify the authentication parameters for multiple methods.

Support is planned for GKE authentication methods (contributions welcome! :wink:).

Approle

To authenticate using the Approle auth method, you need to pass a role ID and a secret ID to your Settings class.

Pydantic-Vault reads this information from the following sources (in descending order of priority):

the VAULT_ROLE_ID and VAULT_SECRET_ID environment variables
the vault_role_id and vault_secret_id configuration fields in your Settings.Config class (vault_secret_id can be a str or a SecretStr)

You can also mix-and-match, e.g. write the role ID in your Settings.Config class and retrieve the secret ID from the environment at runtime.

Example:

from pydantic import BaseSettings, Field, SecretStr
from pydantic_vault import vault_config_settings_source

class Settings(BaseSettings):
    username: str = Field(
        ..., vault_secret_path="path/to/secret", vault_secret_key="my_user"
    )
    password: SecretStr = Field(
        ..., vault_secret_path="path/to/secret", vault_secret_key="my_password"
    )

    class Config:
        vault_url: str = "https://vault.tld"
        vault_role_id: str = "my-role-id"
        vault_secret_id: SecretStr = SecretStr("my-secret-id")

        @classmethod
        def customise_sources(
            cls,
            init_settings,
            env_settings,
            file_secret_settings,
        ):
            return (
                init_settings,
                env_settings,
                vault_config_settings_source,
                file_secret_settings,
            )

Kubernetes

To authenticate using the Kubernetes auth method, you need to pass a role to your Settings class.

Pydantic-Vault reads this information from the following sources (in descending order of priority):

the VAULT_KUBERNETES_ROLE environment variable
the vault_kubernetes_role configuration field in your Settings.Config class, which must be a str

The Kubernetes service account token will be read from the file at /var/run/secrets/kubernetes.io/serviceaccount/token.

Example:

from pydantic import BaseSettings, Field, SecretStr
from pydantic_vault import vault_config_settings_source

class Settings(BaseSettings):
    username: str = Field(
        ..., vault_secret_path="path/to/secret", vault_secret_key="my_user"
    )
    password: SecretStr = Field(
        ..., vault_secret_path="path/to/secret", vault_secret_key="my_password"
    )

    class Config:
        vault_url: str = "https://vault.tld"
        vault_kubernetes_role: str = "my-role"

        @classmethod
        def customise_sources(
            cls,
            init_settings,
            env_settings,
            file_secret_settings,
        ):
            return (
                init_settings,
                env_settings,
                vault_config_settings_source,
                file_secret_settings,
            )

Vault token

To authenticate using the Token auth method, you need to pass a Vault token to your Settings class.

Pydantic-Vault reads this token from the following sources (in descending order of priority):

the VAULT_TOKEN environment variable
the ~/.vault-token file (so you can use the vault CLI to login locally, Pydantic-Vault will transparently reuse its token)
the vault_token configuration field in your Settings.Config class, which can be a str or a SecretStr

Example:

from pydantic import BaseSettings, Field, SecretStr
from pydantic_vault import vault_config_settings_source

class Settings(BaseSettings):
    username: str = Field(
        ..., vault_secret_path="path/to/secret", vault_secret_key="my_user"
    )
    password: SecretStr = Field(
        ..., vault_secret_path="path/to/secret", vault_secret_key="my_password"
    )

    class Config:
        vault_url: str = "https://vault.tld"
        vault_token: SecretStr = SecretStr("my-secret-token")

        @classmethod
        def customise_sources(
            cls,
            init_settings,
            env_settings,
            file_secret_settings,
        ):
            return (
                init_settings,
                env_settings,
                vault_config_settings_source,
                file_secret_settings,
            )

Order of priority

Thanks to the new feature in Pydantic 1.8 that allows you to customize settings sources, you can choose the order of priority you want.

Here are some examples:

from pydantic import BaseSettings
from pydantic_vault import vault_config_settings_source

class Settings(BaseSettings):
    """
    In descending order of priority:
      - arguments passed to the `Settings` class initializer
      - environment variables
      - Vault variables
      - variables loaded from the secrets directory, such as Docker Secrets
      - the default field values for the `Settings` model
    """

    class Config:
        @classmethod
        def customise_sources(
            cls,
            init_settings,
            env_settings,
            file_secret_settings,
        ):
            return (
                init_settings,
                env_settings,
                vault_config_settings_source,
                file_secret_settings,
            )

class Settings(BaseSettings):
    """
    In descending order of priority:
      - Vault variables
      - environment variables
      - variables loaded from the secrets directory, such as Docker Secrets
      - the default field values for the `Settings` model
    Here we chose to remove the "init arguments" source,
    and move the Vault source up before the environment source
    """

    class Config:
        @classmethod
        def customise_sources(
            cls,
            init_settings,
            env_settings,
            file_secret_settings,
        ):
            return (vault_config_settings_source, env_settings, file_secret_settings)

Logging

The library exports a logger called pydantic-vault.

To help debugging you can change the log level. A simple way to do that if you do not have a custom log setup is:

# At the beginning of your main file or entrypoint
import logging

logging.basicConfig()
logging.getLogger("pydantic-vault").setLevel(logging.DEBUG)  # Change the log level here

Examples

All examples use the following structure, so we will omit the imports and the Config inner class:

from pydantic import BaseSettings, Field, SecretStr
from pydantic_vault import vault_config_settings_source

class Settings(BaseSettings):
    ###############################################
    # THIS PART CHANGES IN THE DIFFERENT EXAMPLES #
    username: str = Field(
        ..., vault_secret_path="secret/data/path/to/secret", vault_secret_key="my_user"
    )
    ###############################################

    class Config:
        vault_url: str = "https://vault.tld"

        @classmethod
        def customise_sources(
            cls,
            init_settings,
            env_settings,
            file_secret_settings,
        ):
            return (
                init_settings,
                env_settings,
                vault_config_settings_source,
                file_secret_settings,
            )

Retrieve a secret from a KV v2 secret engine

Suppose your secret is at my-api/prod and looks like this:

Key             Value
---             -----
root_user       root
root_password   a_v3ry_s3cur3_p4ssw0rd

Your settings class would be:

class Settings(BaseSettings):
    # The `vault_secret_path` is the full path (with mount point included) to the secret.
    # For a KV v2 secret engine, there is always a `data/` sub-path between the mount point and
    # the secret actual path, eg. if your mount point is `secret/` (the default) and your secret
    # path is `my-api/prod`, the full path to use is `secret/data/my-api/prod`.
    # The `vault_secret_key` is the specific key to extract from a secret.
    username: str = Field(
        ..., vault_secret_path="secret/data/my-api/prod", vault_secret_key="root_user"
    )
    password: SecretStr = Field(
        ...,
        vault_secret_path="secret/data/my-api/prod",
        vault_secret_key="root_password",
    )

settings = Settings()

settings.username  # "root"
settings.password.get_secret_value()  # "a_v3ry_s3cur3_p4ssw0rd"

Retrieve a whole secret at once

If you omit the vault_secret_key parameter in your Field, Pydantic-Vault will load the whole secret in your class field.

With the same secret as before, located at my-api/prod and with this data:

Key             Value
---             -----
root_user       root
root_password   a_v3ry_s3cur3_p4ssw0rd

You could use a settings class like this to retrieve everything in the secret:

class Settings(BaseSettings):
    # The `vault_secret_path` is the full path (with mount point included) to the secret.
    # For a KV v2 secret engine, there is always a `data/` sub-path between the mount point and
    # the secret actual path, eg. if your mount point is `secret/` (the default) and your secret
    # path is `my-api/prod`, the full path to use is `secret/data/my-api/prod`.
    # We don't pass a `vault_secret_key` here so that Pydantic-Vault fetches all fields at once.
    credentials: dict = Field(..., vault_secret_path="secret/data/my-api/prod")

settings = Settings()
settings.credentials  # { "root_user": "root", "root_password": "a_v3ry_s3cur3_p4ssw0rd" }

You can also use a Pydantic BaseModel class to parse and validate the incoming secret:

class Credentials(BaseModel):
    root_user: str
    root_password: SecretStr

class Settings(BaseSettings):
    # The `vault_secret_path` is the full path (with mount point included) to the secret.
    # For a KV v2 secret engine, there is always a `data/` sub-path between the mount point and
    # the secret actual path, eg. if your mount point is `secret/` (the default) and your secret
    # path is `my-api/prod`, the full path to use is `secret/data/my-api/prod`.
    # We don't pass a `vault_secret_key` here so that Pydantic-Vault fetches all fields at once.
    credentials: Credentials = Field(..., vault_secret_path="secret/data/my-api/prod")

settings = Settings()
settings.credentials.root_user  # "root"
settings.credentials.root_password.get_secret_value()  # "a_v3ry_s3cur3_p4ssw0rd"

Retrieve a secret from a KV v1 secret engine

Suppose your secret is at my-api/prod and looks like this:

Key             Value
---             -----
root_user       root
root_password   a_v3ry_s3cur3_p4ssw0rd

Your settings class would be:

class Settings(BaseSettings):
    # The `vault_secret_path` is the full path (with mount point included) to the secret.
    # For a KV v1 secret engine, the secret path is directly appended to the mount point,
    # eg. if your mount point is `kv/` (the default) and your secret path is `my-api/prod`,
    # the full path to use is `kv/my-api/prod` (unlike with KV v2 secret engines).
    # The `vault_secret_key` is the specific key to extract from a secret.
    username: str = Field(
        ..., vault_secret_path="kv/my-api/prod", vault_secret_key="root_user"
    )
    password: SecretStr = Field(
        ..., vault_secret_path="kv/my-api/prod", vault_secret_key="root_password"
    )

settings = Settings()

settings.username  # "root"
settings.password.get_secret_value()  # "a_v3ry_s3cur3_p4ssw0rd"

⚠ Beware of the known limitations on KV v1 secrets!

Retrieve a secret from a database secret engine

Database secrets can be "dynamic", generated by Vault every time you request access. Because every call to Vault will create a new database account, you cannot store the username and password in two different fields in your settings class, or you would get the username of the first generated account and the password of the second account. This means that you must not pass a vault_secret_key, so that Pydantic-Vault retrieves the whole secret at once.

You can store the credentials in a dict or in a custom BaseModel class:

class DbCredentials(BaseModel):
    username: str
    password: SecretStr

class Settings(BaseSettings):
    # The `vault_secret_path` is the full path (with mount point included) to the secret.
    # For a database secret engine, the secret path is `<mount point>/creds/<role name>`.
    # For example if your mount point is `database/` (the default) and your role name is
    # `my-db-prod`, the full path to use is `database/creds/my-db-prod`. You will receive
    # `username` and `password` fields in response.
    # You must *not* pass a `vault_secret_key` so that Pydantic-Vault fetches both fields at once.
    db_creds: DbCredentials = Field(..., vault_secret_path="database/creds/my-db-prod")
    db_creds_in_dict: dict = Field(..., vault_secret_path="database/creds/my-db-prod")

settings = Settings()

settings.db_creds.username  # "generated-username-1"
settings.db_creds.password.get_secret_value()  # "generated-password-for-username-1"
settings.db_creds_in_dict["username"]  # "generated-username-2"
settings.db_creds_in_dict["password"]  # "generated-password-for-username-2"

Use a dynamic path to retrieve secrets

If you have different paths for your secrets (for example if you have different environments) you can use string formatting to dynamically generate the paths depending on an environment variable.

import os

# You will need to specify the environment in an environment variable, but by
# default it falls back to "dev"
ENV = os.getenv("ENV", "dev")

class Settings(BaseSettings):
    # This will load different secrets depending on the value of the ENV environment variable
    username: str = Field(
        ..., vault_secret_path=f"kv/my-api/{ENV}", vault_secret_key="root_user"
    )
    password: SecretStr = Field(
        ..., vault_secret_path=f"kv/my-api/{ENV}", vault_secret_key="root_password"
    )

settings = Settings()

settings.username  # "root"
settings.password.get_secret_value()  # "a_v3ry_s3cur3_p4ssw0rd"

Known limitations

On KV v1 secret engines, if your secret has a data key and you do not specify a vault_secret_key to load the whole secret at once, Pydantic-Vault will only load the content of the data key. For example, with a secret kv/my-secret
```
Key             Value
---             -----
user            root
password        a_v3ry_s3cur3_p4ssw0rd
data            a very important piece of data
```
and the settings class
```
class Settings(BaseSettings):
  my_secret: dict = Field(..., vault_secret_path="kv/my-secret")
```
Pydantic-Vault will try to load only the data value (a very important piece of data) in my_secret, which will fail validation from Pydantic because it is not a dict.

Workaround: Rename the data key in your secret 😅

Workaround: Migrate to KV v2
On Pydantic version before 1.10.3, Pydantic by default takes up ~50-80 MB, because it is compiled to a native extension and optimized for speed instead of file size. If you don't rely much on Pydantic (you only use it for your app configuration with Pydantic-Vault, you parse/serialize a low volume of JSON, your code is generally slow and Pydantic wouldn't be the bottleneck) you can use the flag --no-binary pydantic when running pip install to install the pure-Python version instead of the compiled one (which comes at less than 1 MB). You can also add the flag on its own line in your requirements.txt. See this discussion https://github.com/samuelcolvin/pydantic/issues/2276 for more information.

This has been fixed in Pydantic 1.10.3, and a default install with a precompiled wheel now takes ~8 MB.

Inspirations

Ansible hashi_vault lookup plugin for the API and some code
Hashicorp's Vault GitHub Action for the API

License

Pydantic-Vault is available under the MIT license.

nymous / pydantic-vault

readme

Pydantic-Vault

Installation

Getting started

Documentation

`Field` additional parameters

Configuration

Authentication

Approle

Kubernetes

Vault token

Order of priority

Logging

Examples

Retrieve a secret from a KV v2 secret engine

Retrieve a whole secret at once

Retrieve a secret from a KV v1 secret engine

Retrieve a secret from a database secret engine

Use a dynamic path to retrieve secrets

Known limitations

Inspirations

License

nymous / pydantic-vault

readme

Pydantic-Vault

Installation

Getting started

Documentation

Field additional parameters

Configuration

Authentication

Approle

Kubernetes

Vault token

Order of priority

Logging

Examples

Retrieve a secret from a KV v2 secret engine

Retrieve a whole secret at once

Retrieve a secret from a KV v1 secret engine

Retrieve a secret from a database secret engine

Use a dynamic path to retrieve secrets

Known limitations

Inspirations

License

`Field` additional parameters