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aissemble-extensions-encryption-vault-python
Advanced tools
This module provides a package for encrypting Python based pipeline data. There are multiple encryption algorithms available. Each with their own strengths and weaknesses as outlined below.
| Strategy | Description |
|---|---|
| VaultRemoteEncryptionStrategy | Leverages the Hashicorp Vault secrets as a service capabilities. This is a highly recommended strategy given it follows best practices and has the advantage of a large developer base working to secure the service. |
| VaultLocalEncryptionStrategy | Leverages the Vault service to provide encryption keys (key rotation and secure storage) but allows for local encryption. This is a good option if you have to encrypt large data objects. It can also provide a performance boost over remote Vault encryption given there is no need for a roundtrip to the server for each data element. |
| AesCbcEncryptionStrategy | A good basic 128 bit encryption strategy. To use this you only need to supply a single encryption key in the encrypt.properties file (128 bit or 16 character). This algorithm works well, but is less efficient than the AES GCM algorithm. |
| AesGcm96EncryptionStrategy | This is a good strategy for most encryption needs. It is efficient and strong against most attacks. You can optionally use an encryption key retrieved from the Vault service with this strategy. |
The following example illustrates how to perform encryption.
Example usage
# Uses remote Vault encryption
from aissemble_encrypt.vault_remote_encryption_strategy import VaultRemoteEncryptionStrategy
vault_remote = VaultRemoteEncryptionStrategy()
# encrypt plain text data using Vault
encrypted_value = vault_remote.encrypt('SOME PLAIN TEXT')
# decrypt cipher text data using Vault
decrypted_value = vault_remote.decrypt(encrypted_value)
NOTE: If you are encrypting your data through a User Defined Function (udf) in PySpark you need to use the VaultLocalEncryptionStrategy (see below). Currently the remote version causes threading issues. This issue will likely be resolved in a future update to the Hashicorp Vault client
# Uses an encryption key retrieved from the Vault server, but performs the encryption locally.
from aissemble_encrypt.vault_local_encryption_strategy import VaultLocalEncryptionStrategy
vault_local = VaultLocalEncryptionStrategy()
# encrypt plain text data using local Vault
encrypted_value = vault_local.encrypt('SOME PLAIN TEXT')
# decrypt cipher text data using local Vault
decrypted_value = vault_local.decrypt(encrypted_value)
# Uses the AES CBC encryption
from aissemble_encrypt.aes_cbc_encryption_strategy import AesCbcEncryptionStrategy
aes_cbc = AesCbcEncryptionStrategy()
# encrypt plain text data using AES CBC
encrypted_value = aes_cbc.encrypt('SOME PLAIN TEXT')
# decrypt cipher text data using AES CBC
decrypted_value = aes_cbc.decrypt(encrypted_value)
# AES GCM encryption with a 96 bit initialization vector (same algorithm as Vault)
from aissemble_encrypt.aes_gcm_96_encryption_strategy import AesGcm96EncryptionStrategy
aes_gcm_96 = AesGcm96EncryptionStrategy()
# encrypt plain text data using AES GCM
encrypted_value = aes_gcm_96.encrypt('SOME PLAIN TEXT')
# decrypt cipher text data using AES CBC
decrypted_value = aes_gcm_96.decrypt(encrypted_value)
This package includes one security client for calling the "Secrets as a Service" encryption service.
See the extensions-encryption README for more information on how to configure Vault encryption.
FAQs
Vault data encryption classes (python)
We found that aissemble-extensions-encryption-vault-python demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 4 open source maintainers collaborating on the project.
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