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Threat Model Analysis for apache/flink

Threat: Malicious Job Submission

  • Description: An attacker gains unauthorized access to the Flink cluster and submits a crafted Flink job. This job could be designed to exfiltrate data, cause denial of service by exhausting resources, execute arbitrary code on TaskManagers, or corrupt data within Flink.
  • Impact: Data breach, Denial of Service, Remote Code Execution, Data Corruption, Cluster Instability.
  • Affected Flink Component: JobManager (Job Submission API, Web UI), TaskManagers (Job Execution).
  • Risk Severity: Critical
  • Mitigation Strategies:
    • Implement strong authentication and authorization for job submission.
    • Utilize Flink's security features like Kerberos or other authentication mechanisms.
    • Restrict access to the JobManager UI and API.
    • Employ job validation and sandboxing techniques.
    • Implement network segmentation to limit access to the Flink cluster.

Threat: Job Parameter Manipulation

  • Description: An attacker intercepts or manipulates job submission parameters to alter job behavior, bypass security checks, or inject malicious configurations.
  • Impact: Data Manipulation, Unauthorized Actions, Security Bypass, Potential Code Execution.
  • Affected Flink Component: JobManager (Job Submission API), Client (Job Submission Process).
  • Risk Severity: High
  • Mitigation Strategies:
    • Enforce HTTPS for job submission to protect parameters in transit.
    • Implement server-side validation and sanitization of all job parameters.
    • Enforce parameter type checking to prevent unexpected input.
    • Use secure communication channels for job submission.

Threat: Unauthorized Job Cancellation/Modification

  • Description: An attacker gains unauthorized access to the JobManager and cancels or modifies running Flink jobs, disrupting critical data processing pipelines.
  • Impact: Service Disruption, Data Loss, Operational Impact, Data Inconsistency.
  • Affected Flink Component: JobManager (Job Management API, Web UI).
  • Risk Severity: High
  • Mitigation Strategies:
    • Implement strong authentication and authorization for JobManager access, especially for job management operations.
    • Utilize Role-Based Access Control (RBAC) to restrict job management actions.
    • Enable audit logging for job lifecycle events.
    • Apply the principle of least privilege for user permissions.

Threat: Code Injection in User-Defined Functions (UDFs)

  • Description: Vulnerabilities in user-provided code (UDFs, custom connectors) can be exploited to inject malicious code that executes within TaskManagers, leading to data exfiltration, remote code execution, or privilege escalation.
  • Impact: Data Breach, Remote Code Execution, Privilege Escalation, Compromised TaskManagers.
  • Affected Flink Component: TaskManagers (UDF Execution Environment), User-Defined Functions (UDFs), Custom Connectors.
  • Risk Severity: Critical
  • Mitigation Strategies:
    • Enforce secure coding practices for UDF development.
    • Implement thorough code review and testing for all UDFs, including security testing.
    • Utilize static code analysis tools on UDF code.
    • Consider sandboxing or containerization for UDF execution.
    • Carefully manage UDF dependencies and ensure they are from trusted sources.

Threat: Resource Exhaustion on TaskManagers

  • Description: A malicious or poorly designed Flink job can consume excessive resources on TaskManagers, causing denial of service for other jobs and potentially destabilizing the Flink cluster.
  • Impact: Service Disruption, Performance Degradation, Cluster Instability, Denial of Service for other applications.
  • Affected Flink Component: TaskManagers (Resource Management), JobManager (Job Scheduling).
  • Risk Severity: High
  • Mitigation Strategies:
    • Implement resource quotas and limits for Flink jobs.
    • Monitor TaskManager resource utilization and set up alerts.
    • Implement job prioritization and fair scheduling mechanisms.
    • Encourage developers to profile and optimize job resource usage.

Threat: Data Deserialization Vulnerabilities

  • Description: Vulnerabilities in deserialization libraries used by Flink or custom serializers can be exploited by providing malicious serialized data, potentially leading to remote code execution or denial of service.
  • Impact: Remote Code Execution, Denial of Service, Cluster Compromise.
  • Affected Flink Component: TaskManagers, JobManager, Serialization Frameworks.
  • Risk Severity: Critical
  • Mitigation Strategies:
    • Minimize or avoid Java Serialization, preferring safer alternatives like Kryo or Avro.
    • Keep serialization libraries and Flink dependencies up-to-date with security patches.
    • Implement input validation and sanitization to prevent processing malicious serialized data.
    • Restrict deserialization sources to trusted origins.

Threat: Unauthorized Access to Cluster Management Interfaces

  • Description: Unsecured access to Flink's Web UI or REST API allows attackers to monitor cluster activity, modify configurations, manage jobs, and potentially gain control over the Flink cluster.
  • Impact: Data Breach, Service Disruption, Cluster Compromise, Unauthorized Actions.
  • Affected Flink Component: JobManager (Web UI, REST API).
  • Risk Severity: High
  • Mitigation Strategies:
    • Secure access to management interfaces with strong authentication and authorization.
    • Restrict access to management interfaces to authorized networks and users.
    • Disable unnecessary management interfaces.
    • Regularly audit access controls for management interfaces.

Threat: ZooKeeper Vulnerabilities (for HA clusters)

  • Description: Vulnerabilities in ZooKeeper or misconfigurations can disrupt ZooKeeper service, corrupt data, or allow unauthorized access to cluster metadata, impacting Flink HA clusters.
  • Impact: Service Disruption, Data Corruption, Cluster Compromise, Information Disclosure.
  • Affected Flink Component: ZooKeeper (External Dependency for HA), JobManager (HA Coordination).
  • Risk Severity: High
  • Mitigation Strategies:
    • Deploy ZooKeeper securely according to best practices, including ACLs and network segmentation.
    • Regularly patch ZooKeeper to address vulnerabilities.
    • Monitor ZooKeeper health and security.
    • Restrict access to ZooKeeper to necessary Flink components and administrators.

Threat: Insecure Network Communication

  • Description: Unencrypted communication between Flink components exposes sensitive data in transit to eavesdropping and man-in-the-middle attacks.
  • Impact: Data Breach, Eavesdropping, Man-in-the-Middle Attacks.
  • Affected Flink Component: All Flink Components (Network Communication).
  • Risk Severity: High
  • Mitigation Strategies:
    • Enable TLS/SSL encryption for all network communication within the Flink cluster.
    • Consider mutual TLS (mTLS) for stronger authentication.
    • Secure network configuration and segment the Flink cluster.

Threat: State Backend Vulnerabilities

  • Description: Vulnerabilities in Flink's state backends can be exploited to corrupt state data, gain unauthorized access to state, or cause denial of service.
  • Impact: Data Corruption, Data Breach, Service Disruption, State Manipulation.
  • Affected Flink Component: State Backends (RocksDB, MemoryStateBackend, FsStateBackend, etc.).
  • Risk Severity: High
  • Mitigation Strategies:
    • Use secure and up-to-date state backends.
    • Implement state backend encryption if supported.
    • Implement access control for state backend storage.
    • Regularly audit state backend configurations.

Threat: Misconfiguration of Flink Security Settings

  • Description: Incorrect or incomplete configuration of Flink's security features can leave the application vulnerable to various attacks.
  • Impact: Security Bypass, Unauthorized Access, Data Breach, Service Disruption.
  • Affected Flink Component: Flink Configuration (flink-conf.yaml, etc.), Security Features.
  • Risk Severity: High
  • Mitigation Strategies:
    • Follow Flink security best practices and documentation for configuration.
    • Use security configuration templates for consistency.
    • Regularly audit Flink configurations for misconfigurations.
    • Use configuration management tools to enforce secure settings.
    • Apply the principle of least privilege when configuring security features.