How to Implement Client-Side Field Level Encryption (CSFLE) in Java with Spring Data MongoDB

Maxime Beugnet, Megha Arora11 min read • Published Nov 06, 2023 • Updated Jan 27, 2024

Spring Java

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GitHub Repository

The source code of this template is available on GitHub:

Code Snippet

To get started, you'll need:

Java 17.
A MongoDB cluster v7.0.2 or higher.
MongoDB Automatic Encryption Shared Library v7.0.2 or higher.

See the README.md file for more information.

Video

This content is also available in video format.

Introduction

This post will explain the key details of the integration of MongoDB Client-Side Field Level Encryption (CSFLE) with Spring Data MongoDB.

However, this post will not explain the basic mechanics of CSFLE or Spring Data MongoDB.

If you feel like you need a refresher on CSFLE before working on this more complicated piece, I can recommend a few resources for CSFLE:

My tutorial: CSFLE with the Java Driver ( without Spring Data)
CSFLE MongoDB documentation
CSFLE encryption schemas
CSFLE quick start

And for Spring Data MongoDB:

This template is significantly larger than other online CSFLE templates you can find online. It tries to provide reusable code for a real production environment using:

Multiple encrypted collections.
Automated JSON Schema generation.
Server-side JSON Schema.
Separated clusters for DEKs and encrypted collections.
Automated data encryption keys generation or retrieval.
SpEL Evaluation Extension.
Auto-implemented repositories.
Open API documentation 3.0.1.

While I was coding, I also tried to respect the SOLID Principles as much as possible to increase the code readability, usability, and reutilization.

High-Level Diagrams

Now that we are all on board, here is a high-level diagram of the different moving parts required to create a correctly-configured CSFLE-enabled MongoClient which can encrypt and decrypt fields automatically.

The arrows can mean different things in the diagram:

"needs to be done before"
"requires"
"direct dependency of"

But hopefully it helps explain the dependencies, the orchestration, and the inner machinery of the CSFLE configuration with Spring Data MongoDB.

Once the connection with MongoDB — capable of encrypting and decrypting the fields — is established, with the correct configuration and library, we are just using a classical three-tier architecture to expose a REST API and manage the communication all the way down to the MongoDB database.

Here, nothing tricky or fascinating to discuss, so we are not going to discuss this in this post.

Let's now focus on all the complicated bits of this template.

Creation of the Key Vault Collection

As this is a tutorial, the code can be started from a blank MongoDB cluster.

So the first point of order is to create the key vault collection and its unique index on the keyAltNames field.

KeyVaultAndDekSetup.java

Code Snippet

/**
 * This class initialize the Key Vault (collection + keyAltNames unique index) using a dedicated standard connection
 * to MongoDB.
 * Then it creates the Data Encryption Keys (DEKs) required to encrypt the documents in each of the
 * encrypted collections.
 */
@Component
public class KeyVaultAndDekSetup {

private static final Logger LOGGER = LoggerFactory.getLogger(KeyVaultAndDekSetup.class);
    private final KeyVaultService keyVaultService;
    private final DataEncryptionKeyService dataEncryptionKeyService;
    @Value("${spring.data.mongodb.vault.uri}")
    private String CONNECTION_STR;

public KeyVaultAndDekSetup(KeyVaultService keyVaultService, DataEncryptionKeyService dataEncryptionKeyService) {
        this.keyVaultService = keyVaultService;
        this.dataEncryptionKeyService = dataEncryptionKeyService;
    }

@PostConstruct
    public void postConstruct() {
        LOGGER.info("=> Start Encryption Setup.");
        LOGGER.debug("=> MongoDB Connection String: {}", CONNECTION_STR);
        MongoClientSettings mcs = MongoClientSettings.builder()
                                                     .applyConnectionString(new ConnectionString(CONNECTION_STR))
                                                     .build();
        try (MongoClient client = MongoClients.create(mcs)) {
            LOGGER.info("=> Created the MongoClient instance for the encryption setup.");
            LOGGER.info("=> Creating the encryption key vault collection.");
            keyVaultService.setupKeyVaultCollection(client);
            LOGGER.info("=> Creating the Data Encryption Keys.");
            EncryptedCollectionsConfiguration.encryptedEntities.forEach(dataEncryptionKeyService::createOrRetrieveDEK);
            LOGGER.info("=> Encryption Setup completed.");
        } catch (Exception e) {
            LOGGER.error("=> Encryption Setup failed: {}", e.getMessage(), e);
        }

}

In production, you could choose to create the key vault collection and its unique index on the keyAltNames field manually once and remove the code as it's never going to be executed again. I guess it only makes sense to keep it if you are running this code in a CI/CD pipeline.

One important thing to note here is the dependency to a completely standard (i.e., not CSFLE-enabled) and ephemeral MongoClient (use of a try-with-resources block) as we are already creating a collection and an index in our MongoDB cluster.

KeyVaultServiceImpl.java

Code Snippet

/**
 * Initialization of the Key Vault collection and keyAltNames unique index.
 */
@Service
public class KeyVaultServiceImpl implements KeyVaultService {

private static final Logger LOGGER = LoggerFactory.getLogger(KeyVaultServiceImpl.class);
    private static final String INDEX_NAME = "uniqueKeyAltNames";
    @Value("${mongodb.key.vault.db}")
    private String KEY_VAULT_DB;
    @Value("${mongodb.key.vault.coll}")
    private String KEY_VAULT_COLL;

public void setupKeyVaultCollection(MongoClient mongoClient) {
        LOGGER.info("=> Setup the key vault collection {}.{}", KEY_VAULT_DB, KEY_VAULT_COLL);
        MongoDatabase db = mongoClient.getDatabase(KEY_VAULT_DB);
        MongoCollection<Document> vault = db.getCollection(KEY_VAULT_COLL);
        boolean vaultExists = doesCollectionExist(db, KEY_VAULT_COLL);
        if (vaultExists) {
            LOGGER.info("=> Vault collection already exists.");
            if (!doesIndexExist(vault)) {
                LOGGER.info("=> Unique index created on the keyAltNames");
                createKeyVaultIndex(vault);
            }
        } else {
            LOGGER.info("=> Creating a new vault collection & index on keyAltNames.");
            createKeyVaultIndex(vault);
        }
    }

private void createKeyVaultIndex(MongoCollection<Document> vault) {
        Bson keyAltNamesExists = exists("keyAltNames");
        IndexOptions indexOpts = new IndexOptions().name(INDEX_NAME)
                                                   .partialFilterExpression(keyAltNamesExists)
                                                   .unique(true);
        vault.createIndex(new BsonDocument("keyAltNames", new BsonInt32(1)), indexOpts);
    }

private boolean doesCollectionExist(MongoDatabase db, String coll) {
        return db.listCollectionNames().into(new ArrayList<>()).stream().anyMatch(c -> c.equals(coll));
    }

private boolean doesIndexExist(MongoCollection<Document> coll) {
        return coll.listIndexes()
                   .into(new ArrayList<>())
                   .stream()
                   .map(i -> i.get("name"))
                   .anyMatch(n -> n.equals(INDEX_NAME));
    }
}

When it's done, we can close the standard MongoDB connection.

Creation of the Data Encryption Keys

We can now create the Data Encryption Keys (DEKs) using the ClientEncryption connection.

MongoDBKeyVaultClientConfiguration.java

Code Snippet

/**
 * ClientEncryption used by the DataEncryptionKeyService to create the DEKs.
 */
@Configuration
public class MongoDBKeyVaultClientConfiguration {

private static final Logger LOGGER = LoggerFactory.getLogger(MongoDBKeyVaultClientConfiguration.class);
    private final KmsService kmsService;
    @Value("${spring.data.mongodb.vault.uri}")
    private String CONNECTION_STR;
    @Value("${mongodb.key.vault.db}")
    private String KEY_VAULT_DB;
    @Value("${mongodb.key.vault.coll}")
    private String KEY_VAULT_COLL;
    private MongoNamespace KEY_VAULT_NS;

public MongoDBKeyVaultClientConfiguration(KmsService kmsService) {
        this.kmsService = kmsService;
    }

@PostConstruct
    public void postConstructor() {
        this.KEY_VAULT_NS = new MongoNamespace(KEY_VAULT_DB, KEY_VAULT_COLL);
    }

/**
     * MongoDB Encryption Client that can manage Data Encryption Keys (DEKs).
     *
     * @return ClientEncryption MongoDB connection that can create or delete DEKs.
     */
    @Bean
    public ClientEncryption clientEncryption() {
        LOGGER.info("=> Creating the MongoDB Key Vault Client.");
        MongoClientSettings mcs = MongoClientSettings.builder()
                                                     .applyConnectionString(new ConnectionString(CONNECTION_STR))
                                                     .build();
        ClientEncryptionSettings ces = ClientEncryptionSettings.builder()
                                                               .keyVaultMongoClientSettings(mcs)
                                                               .keyVaultNamespace(KEY_VAULT_NS.getFullName())
                                                               .kmsProviders(kmsService.getKmsProviders())
                                                               .build();
        return ClientEncryptions.create(ces);
    }
}

We can instantiate directly a ClientEncryption bean using the KMS and use it to generate our DEKs (one for each encrypted collection).

DataEncryptionKeyServiceImpl.java

Code Snippet

/**
 * Service responsible for creating and remembering the Data Encryption Keys (DEKs).
 * We need to retrieve the DEKs when we evaluate the SpEL expressions in the Entities to create the JSON Schemas.
 */
@Service
public class DataEncryptionKeyServiceImpl implements DataEncryptionKeyService {

private static final Logger LOGGER = LoggerFactory.getLogger(DataEncryptionKeyServiceImpl.class);
    private final ClientEncryption clientEncryption;
    private final Map<String, String> dataEncryptionKeysB64 = new HashMap<>();
    @Value("${mongodb.kms.provider}")
    private String KMS_PROVIDER;

public DataEncryptionKeyServiceImpl(ClientEncryption clientEncryption) {
        this.clientEncryption = clientEncryption;
    }

public Map<String, String> getDataEncryptionKeysB64() {
        LOGGER.info("=> Getting Data Encryption Keys Base64 Map.");
        LOGGER.info("=> Keys in DEK Map: {}", dataEncryptionKeysB64.entrySet());
        return dataEncryptionKeysB64;
    }

public String createOrRetrieveDEK(EncryptedEntity encryptedEntity) {
        Base64.Encoder b64Encoder = Base64.getEncoder();
        String dekName = encryptedEntity.getDekName();
        BsonDocument dek = clientEncryption.getKeyByAltName(dekName);
        BsonBinary dataKeyId;
        if (dek == null) {
            LOGGER.info("=> Creating Data Encryption Key: {}", dekName);
            DataKeyOptions dko = new DataKeyOptions().keyAltNames(of(dekName));
            dataKeyId = clientEncryption.createDataKey(KMS_PROVIDER, dko);
            LOGGER.debug("=> DEK ID: {}", dataKeyId);
        } else {
            LOGGER.info("=> Existing Data Encryption Key: {}", dekName);
            dataKeyId = dek.get("_id").asBinary();
            LOGGER.debug("=> DEK ID: {}", dataKeyId);
        }
        String dek64 = b64Encoder.encodeToString(dataKeyId.getData());
        LOGGER.debug("=> Base64 DEK ID: {}", dek64);
        LOGGER.info("=> Adding Data Encryption Key to the Map with key: {}",
                    encryptedEntity.getEntityClass().getSimpleName());
        dataEncryptionKeysB64.put(encryptedEntity.getEntityClass().getSimpleName(), dek64);
        return dek64;
    }

}

One thing to note here is that we are storing the DEKs in a map, so we don't have to retrieve them again later when we need them for the JSON Schemas.

Entities

One of the key functional areas of Spring Data MongoDB is the POJO-centric model it relies on to implement the repositories and map the documents to the MongoDB collections.

PersonEntity.java

Code Snippet

As you can see above, this entity contains all the information we need to fully automate CSFLE. We have the information we need to generate the JSON Schema:

Using the SpEL expression #{mongocrypt.keyId(#target)}, we can populate dynamically the DEK that was generated or retrieved earlier.
ssn is a String that requires a deterministic algorithm.
bloodType is a String that requires a random algorithm.

The generated JSON Schema looks like this:

Code Snippet

SpEL Evaluation Extension

The evaluation of the SpEL expression is only possible because of this class we added in the configuration:

Code Snippet

/**
 * Will evaluate the SePL expressions in the Entity classes like this: #{mongocrypt.keyId(#target)} and insert
 * the right encryption key for the right collection.
 */
@Component
public class EntitySpelEvaluationExtension implements EvaluationContextExtension {

private static final Logger LOGGER = LoggerFactory.getLogger(EntitySpelEvaluationExtension.class);
    private final DataEncryptionKeyService dataEncryptionKeyService;

public EntitySpelEvaluationExtension(DataEncryptionKeyService dataEncryptionKeyService) {
        this.dataEncryptionKeyService = dataEncryptionKeyService;
    }

@Override
    @NonNull
    public String getExtensionId() {
        return "mongocrypt";
    }

@Override
    @NonNull
    public Map<String, Function> getFunctions() {
        try {
            return Collections.singletonMap("keyId", new Function(
                    EntitySpelEvaluationExtension.class.getMethod("computeKeyId", String.class), this));
        } catch (NoSuchMethodException e) {
            throw new RuntimeException(e);
        }
    }

public String computeKeyId(String target) {
        String dek = dataEncryptionKeyService.getDataEncryptionKeysB64().get(target);
        LOGGER.info("=> Computing dek for target {} => {}", target, dek);
        return dek;
    }
}

Note that it's the place where we are retrieving the DEKs and matching them with the target: "PersonEntity", in this case.

JSON Schemas and the MongoClient Connection

JSON Schemas are actually not trivial to generate in a Spring Data MongoDB project.

As a matter of fact, to generate the JSON Schemas, we need the MappingContext (the entities, etc.) which is created by the automatic configuration of Spring Data which creates the MongoClient connection and the MongoTemplate...

But to create the MongoClient — with the automatic encryption enabled — you need JSON Schemas!

It took me a significant amount of time to find a solution to this deadlock, and you can just enjoy the solution now!

The solution is to inject the JSON Schema creation in the autoconfiguration process by instantiating the MongoClientSettingsBuilderCustomizer bean.

MongoDBSecureClientConfiguration.java

Code Snippet

/**
 * Spring Data MongoDB Configuration for the encrypted MongoClient with all the required configuration (jsonSchemas).
 * The big trick in this file is the creation of the JSON Schemas before the creation of the entire configuration as
 * we need the MappingContext to resolve the SpEL expressions in the entities.
 *
 * @see com.mongodb.quickstart.javaspringbootcsfle.components.EntitySpelEvaluationExtension
 */
@Configuration
@DependsOn("keyVaultAndDekSetup")
public class MongoDBSecureClientConfiguration {

private static final Logger LOGGER = LoggerFactory.getLogger(MongoDBSecureClientConfiguration.class);
    private final KmsService kmsService;
    private final SchemaService schemaService;
    @Value("${crypt.shared.lib.path}")
    private String CRYPT_SHARED_LIB_PATH;
    @Value("${spring.data.mongodb.storage.uri}")
    private String CONNECTION_STR_DATA;
    @Value("${spring.data.mongodb.vault.uri}")
    private String CONNECTION_STR_VAULT;
    @Value("${mongodb.key.vault.db}")
    private String KEY_VAULT_DB;
    @Value("${mongodb.key.vault.coll}")
    private String KEY_VAULT_COLL;
    private MongoNamespace KEY_VAULT_NS;

public MongoDBSecureClientConfiguration(KmsService kmsService, SchemaService schemaService) {
        this.kmsService = kmsService;
        this.schemaService = schemaService;
    }

@PostConstruct
    public void postConstruct() {
        this.KEY_VAULT_NS = new MongoNamespace(KEY_VAULT_DB, KEY_VAULT_COLL);
    }

@Bean
    public MongoClientSettings mongoClientSettings() {
        LOGGER.info("=> Creating the MongoClientSettings for the encrypted collections.");
        return MongoClientSettings.builder().applyConnectionString(new ConnectionString(CONNECTION_STR_DATA)).build();
    }

@Bean
    public MongoClientSettingsBuilderCustomizer customizer(MappingContext mappingContext) {
        LOGGER.info("=> Creating the MongoClientSettingsBuilderCustomizer.");
        return builder -> {
            MongoJsonSchemaCreator schemaCreator = MongoJsonSchemaCreator.create(mappingContext);
            Map<String, BsonDocument> schemaMap = schemaService.generateSchemasMap(schemaCreator)
                                                               .entrySet()
                                                               .stream()
                                                               .collect(toMap(e -> e.getKey().getFullName(),
                                                                              Map.Entry::getValue));
            Map<String, Object> extraOptions = Map.of("cryptSharedLibPath", CRYPT_SHARED_LIB_PATH,
                                                      "cryptSharedLibRequired", true);
            MongoClientSettings mcs = MongoClientSettings.builder()
                                                         .applyConnectionString(
                                                                 new ConnectionString(CONNECTION_STR_VAULT))
                                                         .build();
            AutoEncryptionSettings oes = AutoEncryptionSettings.builder()
                                                               .keyVaultMongoClientSettings(mcs)
                                                               .keyVaultNamespace(KEY_VAULT_NS.getFullName())
                                                               .kmsProviders(kmsService.getKmsProviders())
                                                               .schemaMap(schemaMap)
                                                               .extraOptions(extraOptions)
                                                               .build();
            builder.autoEncryptionSettings(oes);
        };
    }
}

One thing to note here is the option to separate the DEKs from the encrypted collections in two completely separated MongoDB clusters. This isn't mandatory, but it can be a handy trick if you choose to have a different backup retention policy for your two clusters. This can be interesting for the GDPR Article 17 "Right to erasure," for instance, as you can then guarantee that a DEK can completely disappear from your systems (backup included). I talk more about this approach in my Java CSFLE post.

Here is the JSON Schema service which stores the generated JSON Schemas in a map:

SchemaServiceImpl.java

Code Snippet

@Service
public class SchemaServiceImpl implements SchemaService {

private static final Logger LOGGER = LoggerFactory.getLogger(SchemaServiceImpl.class);
    private Map<MongoNamespace, BsonDocument> schemasMap;

@Override
    public Map<MongoNamespace, BsonDocument> generateSchemasMap(MongoJsonSchemaCreator schemaCreator) {
        LOGGER.info("=> Generating schema map.");
        List<EncryptedEntity> encryptedEntities = EncryptedCollectionsConfiguration.encryptedEntities;
        return schemasMap = encryptedEntities.stream()
                                             .collect(toMap(EncryptedEntity::getNamespace,
                                                            e -> generateSchema(schemaCreator, e.getEntityClass())));
    }

@Override
    public Map<MongoNamespace, BsonDocument> getSchemasMap() {
        return schemasMap;
    }

private BsonDocument generateSchema(MongoJsonSchemaCreator schemaCreator, Class<?> entityClass) {
        BsonDocument schema = schemaCreator.filter(MongoJsonSchemaCreator.encryptedOnly())
                                           .createSchemaFor(entityClass)
                                           .schemaDocument()
                                           .toBsonDocument();
        LOGGER.info("=> JSON Schema for {}:\n{}", entityClass.getSimpleName(),
                    schema.toJson(JsonWriterSettings.builder().indent(true).build()));
        return schema;
    }

}

We are storing the JSON Schemas because this template also implements one of the good practices of CSFLE: server-side JSON Schemas.

Create or Update the Encrypted Collections

Indeed, to make the automatic encryption and decryption of CSFLE work, you do not require the server-side JSON Schemas.

Only the client-side ones are required for the Automatic Encryption Shared Library. But then nothing would prevent another misconfigured client or an admin connected directly to the cluster to insert or update some documents without encrypting the fields.

To enforce this you can use the server-side JSON Schema as you would to enforce a field type in a document, for instance.

But given that the JSON Schema will evolve with the different versions of your application, the JSON Schemas need to be updated accordingly each time you restart your application.

Code Snippet

/**
 * Create or update the encrypted collections with a server side JSON Schema to secure the encrypted field in the MongoDB database.
 * This prevents any other client from inserting or editing the fields without encrypting the fields correctly.
 */
@Component
public class EncryptedCollectionsSetup {

private static final Logger LOGGER = LoggerFactory.getLogger(EncryptedCollectionsSetup.class);
    private final MongoClient mongoClient;
    private final SchemaService schemaService;

public EncryptedCollectionsSetup(MongoClient mongoClient, SchemaService schemaService) {
        this.mongoClient = mongoClient;
        this.schemaService = schemaService;
    }

@PostConstruct
    public void postConstruct() {
        LOGGER.info("=> Setup the encrypted collections.");
        schemaService.getSchemasMap()
                     .forEach((namespace, schema) -> createOrUpdateCollection(mongoClient, namespace, schema));
    }

private void createOrUpdateCollection(MongoClient mongoClient, MongoNamespace ns, BsonDocument schema) {
        MongoDatabase db = mongoClient.getDatabase(ns.getDatabaseName());
        String collStr = ns.getCollectionName();
        if (doesCollectionExist(db, ns)) {
            LOGGER.info("=> Updating {} collection's server side JSON Schema.", ns.getFullName());
            db.runCommand(new Document("collMod", collStr).append("validator", jsonSchemaWrapper(schema)));
        } else {
            LOGGER.info("=> Creating encrypted collection {} with server side JSON Schema.", ns.getFullName());
            db.createCollection(collStr, new CreateCollectionOptions().validationOptions(
                    new ValidationOptions().validator(jsonSchemaWrapper(schema))));
        }
    }

public BsonDocument jsonSchemaWrapper(BsonDocument schema) {
        return new BsonDocument("$jsonSchema", schema);
    }

private boolean doesCollectionExist(MongoDatabase db, MongoNamespace ns) {
        return db.listCollectionNames()
                 .into(new ArrayList<>())
                 .stream()
                 .anyMatch(c -> c.equals(ns.getCollectionName()));
    }

}

Multi-Entities Support

One big feature of this template as well is the support of multiple entities. As you probably noticed already, there is a CompanyEntity and all its related components but the code is generic enough to handle any amount of entities which isn't usually the case in all the other online tutorials.

In this template, if you want to support a third type of entity, you just have to create the components of the three-tier architecture as usual and add your entry in the EncryptedCollectionsConfiguration class.

EncryptedCollectionsConfiguration.java

Code Snippet

Everything else from the DEK generation to the encrypted collection creation with the server-side JSON Schema is fully automated and taken care of transparently. All you have to do is specify the @Encrypted(algorithm = "AEAD_AES_256_CBC_HMAC_SHA_512-Deterministic") annotation in the entity class and the field will be encrypted and decrypted automatically for you when you are using the auto-implemented repositories (courtesy of Spring Data MongoDB, of course!).

Query by an Encrypted Field

Maybe you noticed but this template implements the findFirstBySsn(ssn) method which means that it's possible to retrieve a person document by its SSN number, even if this field is encrypted.

Note that it only works because we are using a deterministic encryption algorithm.

PersonRepository.java

Code Snippet

Wrapping Up

Thanks for reading my post!

If you have any questions about it, please feel free to open a question in the GitHub repository or ask a question in the MongoDB Community Forum.

Feel free to ping me directly in your post: @MaBeuLux88.

Pull requests and improvement ideas are very welcome!

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Technologies Used

Languages

Java

Technologies

Spring

GitHub Repository
Video
Introduction
High-Level Diagrams
Creation of the Key Vault Collection
Creation of the Data Encryption Keys
Entities
SpEL Evaluation Extension
JSON Schemas and the MongoClient Connection
Create or Update the Encrypted Collections
Multi-Entities Support
Query by an Encrypted Field
Wrapping Up

Java

How to Implement Client-Side Field Level Encryption (CSFLE) in Java with Spring Data MongoDB

GitHub Repository

Video

Introduction

High-Level Diagrams

Creation of the Key Vault Collection

Creation of the Data Encryption Keys

Entities

SpEL Evaluation Extension

JSON Schemas and the MongoClient Connection

Create or Update the Encrypted Collections

Multi-Entities Support

Query by an Encrypted Field

Wrapping Up

Related

Creating a REST API for CRUD Operations With Quarkus and MongoDB

Integrating MongoDB with Amazon Managed Streaming for Apache Kafka (MSK)

Seamless Media Storage: Integrating Azure Blob Storage and MongoDB with Spring Boot

Microservices Architecture With Java, Spring, and MongoDB

Technologies Used

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