Kafka Authorization

Apache Kafka is a high-performance distributed streaming platform deployed by thousands of companies. In many deployments, administrators require fine-grained access control over Kafka topics to enforce important requirements around confidentiality and integrity.

Goals

This tutorial shows how to enforce fine-grained access control over Kafka topics. In this tutorial you will use OPA to define and enforce an authorization policy stating:

• Consumers of topics containing Personally Identifiable Information (PII) must be whitelisted.
• Producers to topics with high fanout must be whitelisted.

In addition, this tutorial shows how to break up a policy with small helper rules to reuse logic and improve overall readability.

Prerequisites

This tutorial requires Docker Compose to run Kafka, ZooKeeper, and OPA.

Steps

1. Bootstrap the tutorial environment using Docker Compose.

First, create an OPA policy that allows all requests. You will update this policy later in the tutorial.

mkdir -p policies

policies/tutorial.rego:

package kafka.authz
allow = true

Next, create a docker-compose.yaml file that runs OPA, ZooKeeper, and Kafka.

docker-compose.yaml:

version: "2"
services:
  opa:
    hostname: opa
    image: openpolicyagent/opa:0.13.5
    ports:
      - 8181:8181
    # WARNING: OPA is NOT running with an authorization policy configured. This
    # means that clients can read and write policies in OPA. If you are deploying
    # OPA in an insecure environment, you should configure authentication and
    # authorization on the daemon. See the Security page for details:
    # https://www.openpolicyagent.org/docs/security.html.
    command: "run --server --watch /policies"
    volumes:
      - ./policies:/policies
  zookeeper:
    image: confluentinc/cp-zookeeper:4.0.0-3
    environment:
      ZOOKEEPER_CLIENT_PORT: 2181
      zk_id: "1"
  kafka:
    hostname: kafka
    image: openpolicyagent/demo-kafka:1.0
    links:
      - zookeeper
      - opa
    ports:
      - "9092:9092"
    environment:
      KAFKA_OFFSETS_TOPIC_REPLICATION_FACTOR: "1"
      KAFKA_ZOOKEEPER_CONNECT: "zookeeper:2181"
      KAFKA_ADVERTISED_LISTENERS: "SSL://:9093"
      KAFKA_SECURITY_INTER_BROKER_PROTOCOL: SSL
      KAFKA_SSL_CLIENT_AUTH: required
      KAFKA_SSL_KEYSTORE_FILENAME: kafka.broker.keystore.jks
      KAFKA_SSL_KEYSTORE_CREDENTIALS: broker_keystore_creds
      KAFKA_SSL_KEY_CREDENTIALS: broker_sslkey_creds
      KAFKA_SSL_TRUSTSTORE_FILENAME: kafka.broker.truststore.jks
      KAFKA_SSL_TRUSTSTORE_CREDENTIALS: broker_truststore_creds
      KAFKA_AUTHORIZER_CLASS_NAME: com.lbg.kafka.opa.OpaAuthorizer
      KAFKA_OPA_AUTHORIZER_URL: "http://opa:8181/v1/data/kafka/authz/allow"
      KAFKA_OPA_AUTHORIZER_ALLOW_ON_ERROR: "false"
      KAFKA_OPA_AUTHORIZER_CACHE_INITIAL_CAPACITY: 100
      KAFKA_OPA_AUTHORIZER_CACHE_MAXIMUM_SIZE: 100
      KAFKA_OPA_AUTHORIZER_CACHE_EXPIRE_AFTER_MS: 600000

For more information on how to configure the OPA plugin for Kafka, see the github.com/open-policy-agent/contrib repository.

Once you have created the file, launch the containers for this tutorial.

docker-compose --project-name opa-kafka-tutorial up

Now that the tutorial environment is running, we can define an authorization policy using OPA and test it.

Authentication

The Docker Compose file defined above requires SSL client authentication for clients that connect to the broker. Enabling SSL client authentication allows for service identities to be provided as input to your policy. The example below shows the input structure.

{
  "operation": {
    "name": "Write",
  },
  "resource": {
    "resourceType": {
      "name": "Topic",
    },
    "name": "credit-scores"
  },
  "session": {
    "principal": {
      "principalType": "User",
    },
    "clientAddress": "172.21.0.5",
    "sanitizedUser": "CN%3Danon_producer.tutorial.openpolicyagent.org%2COU%3DTUTORIAL%2CO%3DOPA%2CL%3DSF%2CST%3DCA%2CC%3DUS"
  }
}

The client identity is extracted from the SSL certificates that clients present when they connect to the broker. The client identity information is encoded in the input.session.sanitizedUser field. This field can be decoded inside the policy.

Generating SSL certificates and JKS files required for SSL client authentication is outside the scope of this tutorial. To simplify the steps below, the Docker Compose file uses an extended version of the confluentinc/cp-kafka image from Docker Hub. The extended image includes pre-generated SSL certificates that the broker and clients use to identify themselves.

Do not rely on these pre-generated SSL certificates in real-world scenarios. They are only provided for convenience/test purposes.

Kafka Authorizer JAR File

The Kafka image used in this tutorial includes a pre-installed JAR file that implements the Kafka Authorizer interface. For more information on the authorizer see open-policy-agent/contrib/kafka_authorizer.

2. Define a policy to restrict consumer access to topics containing Personally Identifiable Information (PII).

Update the policies/tutorial.rego with the following content.

#-----------------------------------------------------------------------------
# High level policy for controlling access to Kafka.
#
# * Deny operations by default.
# * Allow operations if no explicit denial.
#
# The kafka-authorizer-opa plugin will query OPA for decisions at
# /kafka/authz/allow. If the policy decision is _true_ the request is allowed.
# If the policy decision is _false_ the request is denied.
#-----------------------------------------------------------------------------
package kafka.authz
default allow = false
allow {
    not deny
}
deny {
    is_read_operation
    topic_contains_pii
    not consumer_is_whitelisted_for_pii
}
#-----------------------------------------------------------------------------
# Data structures for controlling access to topics. In real-world deployments,
# these data structures could be loaded into OPA as raw JSON data. The JSON
# data could be pulled from external sources like AD, Git, etc.
#-----------------------------------------------------------------------------
consumer_whitelist = {"pii": {"pii_consumer"}}
topic_metadata = {"credit-scores": {"tags": ["pii"]}}
#-----------------------------------
# Helpers for checking topic access.
#-----------------------------------
topic_contains_pii {
    topic_metadata[topic_name].tags[_] == "pii"
}
consumer_is_whitelisted_for_pii {
    consumer_whitelist.pii[_] == principal.name
}
#-----------------------------------------------------------------------------
# Helpers for processing Kafka operation input. This logic could be split out
# into a separate file and shared. For conciseness, we have kept it all in one
# place.
#-----------------------------------------------------------------------------
is_write_operation {
    input.operation.name == "Write"
}
is_read_operation {
    input.operation.name == "Read"
}
is_topic_resource {
    input.resource.resourceType.name == "Topic"
}
topic_name = input.resource.name {
    is_topic_resource
}
principal = {"fqn": parsed.CN, "name": cn_parts[0]} {
    parsed := parse_user(urlquery.decode(input.session.sanitizedUser))
    cn_parts := split(parsed.CN, ".")
}
parse_user(user) = {key: value |
    parts := split(user, ",")
    [key, value] := split(parts[_], "=")
}

The ./policies directory is mounted into the Docker container running OPA. When the files under this directory change, OPA is notified and the policies are automatically reloaded.

At this point, you can exercise the policy.

3. Exercise the policy that restricts consumer access to topics containing PII.

This step shows how you can grant fine-grained access to services using Kafka. In this scenario, some services are allowed to read PII data while others are not.

First, run kafka-console-producer to generate some data on the credit-scores topic.

This tutorial uses the kafka-console-producer and kafka-console-consumer scripts to generate and display Kafka messages. These scripts read from STDIN and write to STDOUT and are frequently used to send and receive data via Kafka over the command line. If you are not familiar with these scripts you can learn more in Kafka’s Quick Start documentation.

docker run --rm --network opakafkatutorial_default \
    openpolicyagent/demo-kafka:1.0 \
    bash -c 'for i in {1..10}; do echo "{\"user\": \"bob\", \"score\": $i}"; done | kafka-console-producer --topic credit-scores --broker-list kafka:9093 -producer.config /etc/kafka/secrets/anon_producer.ssl.config'

This command will send 10 messages to the credit-scores topic. Bob’s credit score seems to be improving.

Next, run kafka-console-consumer and try to read data off the topic. Use the pii_consumer credentials to simulate a service that is allowed to read PII data.

docker run --rm --network opakafkatutorial_default \
    openpolicyagent/demo-kafka:1.0 \
    kafka-console-consumer --bootstrap-server kafka:9093 --topic credit-scores --from-beginning --consumer.config /etc/kafka/secrets/pii_consumer.ssl.config

This command will output the 10 messages sent to the topic in the first part of this step. Once the 10 messages have been printed, exit out of the script (^C).

Finally, run kafka-console-consumer again but this time try to use the anon_consumer credentials. The anon_consumer credentials simulate a service that has not been explicitly granted access to PII data.

docker run --rm --network opakafkatutorial_default \
    openpolicyagent/demo-kafka:1.0 \
    kafka-console-consumer --bootstrap-server kafka:9093 --topic credit-scores --from-beginning --consumer.config /etc/kafka/secrets/anon_consumer.ssl.config

Because the anon_consumer is not allowed to read PII data, the request will be denied and the consumer will output an error message.

Not authorized to read from topic credit-scores.
...
Processed a total of 0 messages

4. Extend the policy to prevent services from accidentally writing to topics with large fanout.

First, add the following content to the policy file (./policies/tutorial.rego):

deny {
  is_write_operation
  topic_has_large_fanout
  not producer_is_whitelisted_for_large_fanout
}
producer_whitelist = {
  "large-fanout": {
    "fanout_producer",
  }
}
topic_has_large_fanout {
  topic_metadata[topic_name].tags[_] == "large-fanout"
}
producer_is_whitelisted_for_large_fanout {
  producer_whitelist["large-fanout"][_] == principal.name
}

Next, update the topic_metadata data structure in the same file to indicate that the click-stream topic has a high fanout.

topic_metadata = {
  "click-stream": {
    "tags": ["large-fanout"],
  },
  "credit-scores": {
    "tags": ["pii"],
  }
}

5. Exercise the policy that restricts producer access to topics with high fanout.

First, run kafka-console-producer and simulate a service with access to the click-stream topic.

docker run --rm --network opakafkatutorial_default \
    openpolicyagent/demo-kafka:1.0 \
    bash -c 'for i in {1..10}; do echo "{\"user\": \"alice\", \"button\": $i}"; done | kafka-console-producer --topic click-stream --broker-list kafka:9093 -producer.config /etc/kafka/secrets/fanout_producer.ssl.config'

Next, run the kafka-console-consumer to confirm that the messages were published.

docker run --rm --network opakafkatutorial_default \
    openpolicyagent/demo-kafka:1.0 \
    kafka-console-consumer --bootstrap-server kafka:9093 --topic click-stream --from-beginning --consumer.config /etc/kafka/secrets/anon_consumer.ssl.config

Once you see the 10 messages produced by the first part of this step, exit the console consumer (^C).

Lastly, run kafka-console-producer to simulate a service that should not have access to high fanout topics.

docker run --rm --network opakafkatutorial_default \
    openpolicyagent/demo-kafka:1.0 \
    bash -c 'echo "{\"user\": \"alice\", \"button\": \"bogus\"}" | kafka-console-producer --topic click-stream --broker-list kafka:9093 -producer.config /etc/kafka/secrets/anon_producer.ssl.config'

Because anon_producer is not authorized to write to high fanout topics, the request will be denied and the producer will output an error message.

Not authorized to access topics: [click-stream]

Wrap Up

Congratulations for finishing the tutorial!

At this point you have learned how to enforce fine-grained access control over Kafka topics. In addition, you have seen how to break down policies into smaller rules that can be reused and improve the overall readability over the policy.

If you want to use the Kafka Authorizer plugin that integrates Kafka with OPA, see the build and install instructions in the github.com/open-policy-agent/contrib repository.