aes_encrypt

Returns an encrypted value of input using AES in given mode with the specified padding. Key lengths of 16, 24 and 32 bits are supported. Supported combinations of (mode, padding) are (ECB, PKCS), (GCM, NONE) and (CBC, PKCS). Optional initialization vectors (IVs) are only supported for CBC and GCM modes. These must be 16 bytes for CBC and 12 bytes for GCM. If not provided, a random vector will be generated and prepended to the output. Optional additional authenticated data (AAD) is only supported for GCM. If provided for encryption, the identical AAD value must be provided for decryption. The default mode is GCM.

Syntax

from pyspark.sql import functions as sf

sf.aes_encrypt(input, key, mode=None, padding=None, iv=None, aad=None)

Parameters

Parameter	Type	Description
input	pyspark.sql.Column or str	The binary value to encrypt.
key	pyspark.sql.Column or str	The passphrase to use to encrypt the data.
mode	pyspark.sql.Column or str, optional	Specifies which block cipher mode should be used to encrypt messages. Valid modes: ECB, GCM, CBC.
padding	pyspark.sql.Column or str, optional	Specifies how to pad messages whose length is not a multiple of the block size. Valid values: PKCS, NONE, DEFAULT. The DEFAULT padding means PKCS for ECB, NONE for GCM and PKCS for CBC.
iv	pyspark.sql.Column or str, optional	Optional initialization vector. Only supported for CBC and GCM modes. Valid values: None or "". 16-byte array for CBC mode. 12-byte array for GCM mode.
aad	pyspark.sql.Column or str, optional	Optional additional authenticated data. Only supported for GCM mode. This can be any free-form input and must be provided for both encryption and decryption.

Returns

pyspark.sql.Column: A new column that contains an encrypted value.

Examples

Example 1: Encrypt data with key, mode, padding, iv and aad

from pyspark.sql import functions as sf
df = spark.createDataFrame([(
    "Spark", "abcdefghijklmnop12345678ABCDEFGH", "GCM", "DEFAULT",
    "000000000000000000000000", "This is an AAD mixed into the input",)],
    ["input", "key", "mode", "padding", "iv", "aad"]
)
df.select(sf.base64(sf.aes_encrypt(
    df.input, df.key, "mode", df.padding, sf.to_binary(df.iv, sf.lit("hex")), df.aad)
)).show(truncate=False)

+-----------------------------------------------------------------------+
|base64(aes_encrypt(input, key, mode, padding, to_binary(iv, hex), aad))|
+-----------------------------------------------------------------------+
|AAAAAAAAAAAAAAAAQiYi+sTLm7KD9UcZ2nlRdYDe/PX4                           |
+-----------------------------------------------------------------------+

Example 2: Encrypt data with key, mode, padding and iv

from pyspark.sql import functions as sf
df = spark.createDataFrame([(
    "Spark", "abcdefghijklmnop12345678ABCDEFGH", "GCM", "DEFAULT",
    "000000000000000000000000", "This is an AAD mixed into the input",)],
    ["input", "key", "mode", "padding", "iv", "aad"]
)
df.select(sf.base64(sf.aes_encrypt(
    df.input, df.key, "mode", df.padding, sf.to_binary(df.iv, sf.lit("hex")))
)).show(truncate=False)

+--------------------------------------------------------------------+
|base64(aes_encrypt(input, key, mode, padding, to_binary(iv, hex), ))|
+--------------------------------------------------------------------+
|AAAAAAAAAAAAAAAAQiYi+sRNYDAOTjdSEcYBFsAWPL1f                        |
+--------------------------------------------------------------------+

Example 3: Encrypt data with key, mode and padding

from pyspark.sql import functions as sf
df = spark.createDataFrame([(
    "Spark SQL", "1234567890abcdef", "ECB", "PKCS",)],
    ["input", "key", "mode", "padding"]
)
df.select(sf.aes_decrypt(sf.aes_encrypt(df.input, df.key, "mode", df.padding),
    df.key, df.mode, df.padding
).cast("STRING")).show(truncate=False)

+---------------------------------------------------------------------------------------------+
|CAST(aes_decrypt(aes_encrypt(input, key, mode, padding, , ), key, mode, padding, ) AS STRING)|
+---------------------------------------------------------------------------------------------+
|Spark SQL                                                                                    |
+---------------------------------------------------------------------------------------------+

Example 4: Encrypt data with key and mode

from pyspark.sql import functions as sf
df = spark.createDataFrame([(
    "Spark SQL", "0000111122223333", "ECB",)],
    ["input", "key", "mode"]
)
df.select(sf.aes_decrypt(sf.aes_encrypt(df.input, df.key, "mode"),
    df.key, df.mode
).cast("STRING")).show(truncate=False)

+---------------------------------------------------------------------------------------------+
|CAST(aes_decrypt(aes_encrypt(input, key, mode, DEFAULT, , ), key, mode, DEFAULT, ) AS STRING)|
+---------------------------------------------------------------------------------------------+
|Spark SQL                                                                                    |
+---------------------------------------------------------------------------------------------+

Example 5: Encrypt data with key

from pyspark.sql import functions as sf
df = spark.createDataFrame([(
    "Spark SQL", "abcdefghijklmnop",)],
    ["input", "key"]
)
df.select(sf.aes_decrypt(
    sf.unbase64(sf.base64(sf.aes_encrypt(df.input, df.key))), df.key
).cast("STRING")).show(truncate=False)

+-------------------------------------------------------------------------------------------------------------+
|CAST(aes_decrypt(unbase64(base64(aes_encrypt(input, key, GCM, DEFAULT, , ))), key, GCM, DEFAULT, ) AS STRING)|
+-------------------------------------------------------------------------------------------------------------+
|Spark SQL                                                                                                    |
+-------------------------------------------------------------------------------------------------------------+