threat-modeling.md

Threat Model Analysis for apache/kafka

Threat: Unauthorized Access to Kafka Brokers

Description: An attacker attempts to bypass authentication or exploit misconfigurations to gain access to Kafka brokers. They might use brute-force attacks, exploit default credentials, or leverage network vulnerabilities to connect to broker ports. Once inside, they can produce/consume messages, modify configurations, or disrupt the cluster.

Impact:

• Confidentiality breach: Reading sensitive messages.
• Integrity breach: Modifying messages or cluster configurations.
• Availability impact: Disrupting Kafka cluster operations, leading to service downtime.

Affected Kafka Component: Kafka Brokers, Broker Authentication/Authorization Modules

Risk Severity: Critical

Mitigation Strategies:

• Implement strong authentication mechanisms (SASL/PLAIN, SASL/SCRAM, TLS Mutual Authentication).
• Enforce authorization using Kafka ACLs.
• Restrict network access to Kafka broker ports using firewalls and network segmentation.
• Regularly audit and review authentication and authorization configurations.

Threat: Client Impersonation

Description: An attacker steals or compromises credentials of a legitimate Kafka client (producer or consumer). They then use these credentials to impersonate the client and perform actions as if they were authorized. This could involve producing malicious messages or consuming sensitive data they shouldn't access.

Impact:

• Integrity breach: Injecting malicious or incorrect messages into topics.
• Confidentiality breach: Accessing and consuming sensitive messages from topics.
• Availability impact: Disrupting message flow or application logic by injecting faulty data.

Affected Kafka Component: Kafka Clients (Producers, Consumers), Client Authentication Modules

Risk Severity: High

Mitigation Strategies:

• Use strong client authentication methods.
• Implement secure credential storage and management for client applications (avoid hardcoding credentials).
• Regularly rotate client credentials.
• Monitor client activity for anomalous behavior.
• Consider client-side authorization checks in addition to Kafka ACLs.

Threat: Lack of Authorization for Topic Access

Description: Kafka topics are created or configured without proper authorization rules (ACLs). This allows unauthorized producers to write to topics or unauthorized consumers to read from topics, potentially leading to data breaches or data corruption.

Impact:

• Confidentiality breach: Unauthorized access to sensitive data in topics.
• Integrity breach: Unauthorized injection of data into topics, potentially corrupting data streams.

Affected Kafka Component: Kafka Brokers, Authorization Modules (ACLs), Topic Configuration

Risk Severity: High

Mitigation Strategies:

• Implement and enforce Kafka ACLs for all topics, controlling producer and consumer access.
• Define clear roles and permissions for topic access based on application requirements.
• Regularly review and update ACLs as application needs evolve.
• Automate ACL management as part of topic creation and management processes.

Threat: Zookeeper Access Control Vulnerability (If Zookeeper is Used)

Description: If Zookeeper is directly exposed and not properly secured (especially in older Kafka setups), attackers can exploit vulnerabilities in Zookeeper's access control or configuration. Gaining access to Zookeeper allows manipulation of Kafka cluster metadata, potentially leading to complete cluster compromise.

Impact:

• Complete cluster compromise: Full control over the Kafka cluster.
• Availability impact: Disrupting cluster management and stability, leading to service outage.
• Integrity breach: Modifying cluster metadata, leading to data corruption or misdirection.
• Confidentiality breach: Accessing sensitive cluster metadata.

Affected Kafka Component: Zookeeper (if used), Kafka Cluster Management

Risk Severity: Critical

Mitigation Strategies:

• Restrict network access to Zookeeper ports to only authorized Kafka brokers.
• Implement Zookeeper authentication (if applicable and supported by your Zookeeper version).
• Harden Zookeeper configuration according to security best practices.
• Consider migrating to Kafka versions using Kraft mode to eliminate Zookeeper dependency.
• Regularly patch and update Zookeeper to address known vulnerabilities.

Threat: Data Interception in Transit (Man-in-the-Middle)

Description: Communication between Kafka clients and brokers, or between brokers, is not encrypted. An attacker positioned on the network can intercept network traffic and read sensitive message data as it is transmitted.

Impact:

• Confidentiality breach: Exposure of sensitive message content to unauthorized parties.

Affected Kafka Component: Network Communication Channels (Client-Broker, Broker-Broker), Kafka Networking Modules

Risk Severity: High

Mitigation Strategies:

• Enable TLS encryption for all Kafka communication channels (client-broker, broker-broker).
• Enforce TLS usage by configuring Kafka brokers to require encrypted connections.
• Use strong TLS cipher suites.
• Regularly review and update TLS configurations.

Threat: Data at Rest Exposure on Brokers

Description: Data stored on Kafka brokers' disks (message logs) is not encrypted by default. If an attacker gains physical access to broker machines, compromises the operating system, or exploits storage vulnerabilities, they could directly access and read message data from disk.

Impact:

• Confidentiality breach: Exposure of stored message content to unauthorized parties.

Affected Kafka Component: Kafka Brokers, Disk Storage, Log Management

Risk Severity: High

Mitigation Strategies:

• Implement disk encryption on broker machines (e.g., using LUKS, BitLocker, cloud provider encryption).
• Consider using Kafka's built-in data at rest encryption features if available and suitable for your environment.
• Implement strong physical security for broker machines.
• Regularly monitor and audit access to broker machines and storage.

Threat: Message Content Injection

Description: An attacker, through compromised clients or by exploiting authorization weaknesses, injects malicious, incorrect, or malformed messages into Kafka topics. These messages can then be processed by consumer applications, leading to data corruption, application malfunctions, or propagation of harmful data downstream.

Impact:

• Integrity breach: Data corruption within Kafka topics and downstream systems.
• Availability impact: Application malfunctions, errors, or crashes due to processing malicious data.
• Potential cascading impacts on downstream systems and data consumers.

Affected Kafka Component: Kafka Producers, Kafka Topics, Consumer Applications

Risk Severity: High

Mitigation Strategies:

• Implement strong input validation and sanitization in producer applications to prevent injection of malicious data.
• Enforce schema validation for messages to ensure data conforms to expected formats.
• Implement robust error handling in consumer applications to gracefully handle unexpected or malformed messages.
• Monitor message content for anomalies and suspicious patterns.
• Implement rate limiting on producers to prevent message flooding.

Threat: Broker Resource Exhaustion

Description: An attacker floods Kafka brokers with excessive produce or consume requests, overwhelming broker resources (CPU, memory, network bandwidth, disk I/O). This can lead to broker performance degradation, instability, or complete service disruption, preventing legitimate clients from using Kafka.

Impact:

• Availability impact: Kafka service disruption, preventing message production and consumption.
• Performance degradation for legitimate clients.

Affected Kafka Component: Kafka Brokers, Broker Resource Management, Network Communication

Risk Severity: High

Mitigation Strategies:

• Implement rate limiting and request quotas at the application level or using Kafka's built-in quota mechanisms.
• Monitor broker resource utilization (CPU, memory, network, disk I/O) and set up alerts for high usage.
• Implement proper capacity planning and scaling for the Kafka cluster to handle expected load and potential spikes.
• Use load balancing techniques to distribute load across brokers.
• Implement network-level DoS protection mechanisms (e.g., firewalls, intrusion detection/prevention systems).

Threat: Zookeeper DoS (If Zookeeper is Used)

Description: An attacker targets Zookeeper with DoS attacks, flooding it with requests or exploiting vulnerabilities. Disrupting Zookeeper's availability impacts its ability to manage the Kafka cluster, leading to cluster instability, loss of coordination, and potentially complete Kafka service outage.

Impact:

• Availability impact: Kafka cluster disruption, potentially leading to complete service outage.
• Loss of cluster coordination and management.

Affected Kafka Component: Zookeeper (if used), Kafka Cluster Management, Coordination Modules

Risk Severity: Critical

Mitigation Strategies:

• Restrict network access to Zookeeper to only authorized Kafka brokers.
• Implement rate limiting on Zookeeper requests (if possible and applicable to your Zookeeper setup).
• Monitor Zookeeper performance and set up alerts for performance degradation.
• Harden Zookeeper configuration and follow security best practices.
• Consider migrating to Kafka versions using Kraft mode to eliminate Zookeeper dependency.
• Implement network-level DoS protection for Zookeeper.

Threat: Misconfigured Kafka Brokers

Description: Kafka brokers are deployed with insecure default configurations or misconfigurations. This could include weak authentication settings, disabled encryption, overly permissive access controls, or exposed management interfaces. Misconfigurations create vulnerabilities that attackers can exploit.

Impact:

• Various impacts depending on the specific misconfiguration, including Confidentiality, Integrity, and Availability breaches.
• Potential for complete cluster compromise in severe cases.

Affected Kafka Component: Kafka Brokers, Broker Configuration, Security Settings

Risk Severity: High

Mitigation Strategies:

• Follow security best practices and hardening guides for Kafka configuration.
• Use configuration management tools (e.g., Ansible, Chef, Puppet) to ensure consistent and secure configurations across brokers.
• Regularly review and audit Kafka configurations for security vulnerabilities.
• Disable unnecessary features and components.
• Implement a secure deployment process and environment for Kafka brokers.

Threat: Insecure Client Configurations

Description: Kafka client applications (producers and consumers) are configured insecurely. This includes hardcoding credentials in code or configuration files, using weak authentication methods, not enabling encryption, or using insecure communication protocols. Insecure client configurations can expose credentials, lead to data interception, or allow unauthorized access.

Impact:

• Confidentiality breach: Exposure of credentials, data interception.
• Unauthorized access to Kafka topics and brokers.
• Integrity breach: Potential for malicious message injection if client is compromised.

Affected Kafka Component: Kafka Clients (Producers, Consumers), Client Configuration, Client Libraries

Risk Severity: High

Mitigation Strategies:

• Use secure credential management practices (e.g., environment variables, secrets management systems like HashiCorp Vault, AWS Secrets Manager).
• Avoid hardcoding credentials in code or configuration files.
• Enforce strong client authentication methods.
• Enable TLS encryption in client configurations for secure communication.
• Regularly review and audit client configurations for security vulnerabilities.
• Educate developers on secure Kafka client configuration practices.

Threat: Vulnerable Kafka Components

Description: Using outdated or vulnerable versions of Kafka brokers, clients, or related components (Zookeeper, Kafka Connect, Kafka Streams). Known vulnerabilities in these components can be exploited by attackers to gain unauthorized access, execute arbitrary code, or cause denial of service.

Impact:

• Various impacts depending on the specific vulnerability, including Confidentiality, Integrity, and Availability breaches.
• Potential for remote code execution on Kafka brokers or client machines.
• Service disruption due to exploited vulnerabilities.

Affected Kafka Component: Kafka Brokers, Kafka Clients, Zookeeper (if used), Kafka Connect, Kafka Streams, Kafka Libraries

Risk Severity: Critical

Mitigation Strategies:

• Regularly update Kafka brokers, clients, and related components to the latest stable and patched versions.
• Subscribe to security advisories for Kafka and its dependencies (e.g., Apache Kafka security mailing list, vendor security bulletins).
• Implement vulnerability scanning and patching processes for Kafka infrastructure.
• Establish a process for quickly responding to and mitigating newly discovered vulnerabilities.

Threat: Exposed Kafka Management Interfaces

Description: Kafka management interfaces (JMX, REST APIs exposed by tools like Kafka Manager or Confluent Control Center) are exposed without proper authentication or authorization. Attackers can exploit these interfaces to monitor cluster metrics, modify configurations, or even perform administrative actions on the Kafka cluster, potentially leading to complete cluster compromise.

Impact:

• Cluster compromise: Full control over the Kafka cluster.
• Availability impact: Disrupting cluster management, leading to service outage.
• Integrity breach: Modifying cluster configurations, potentially leading to data corruption or misdirection.
• Confidentiality breach: Accessing sensitive monitoring data and cluster metadata.

Affected Kafka Component: Kafka Brokers, JMX Interface, REST APIs (if exposed by management tools), Management Tools (Kafka Manager, Confluent Control Center)

Risk Severity: Critical

Mitigation Strategies:

• Secure Kafka management interfaces by implementing strong authentication and authorization.
• Restrict network access to management interfaces to only authorized administrators and monitoring systems.
• Use HTTPS for management APIs to encrypt communication.
• Regularly audit access to management interfaces.
• Disable management interfaces if they are not actively used.
• Use dedicated security tools and firewalls to protect management interfaces.