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Threat Model Analysis for apache/hadoop

Threat: Unauthorized HDFS Data Access

  • Description: An attacker gains unauthorized access to sensitive data stored in HDFS. This could be achieved by exploiting misconfigured HDFS permissions, compromised user accounts, or vulnerabilities in HDFS access control mechanisms. The attacker might read, copy, or exfiltrate sensitive data.
  • Impact: Confidentiality breach, data leakage, regulatory non-compliance, reputational damage.
  • Affected Hadoop Component: HDFS (NameNode, DataNodes, HDFS Client)
  • Risk Severity: High
  • Mitigation Strategies:
    • Implement strong authentication and authorization using Kerberos and Hadoop authorization frameworks (Ranger, Sentry).
    • Enforce the principle of least privilege when granting HDFS permissions.
    • Regularly review and audit HDFS permissions.
    • Utilize HDFS encryption features (Transparent Encryption) for data at rest and in transit.

Threat: HDFS Data Tampering

  • Description: An attacker modifies or deletes data stored in HDFS without authorization. This could be done by exploiting compromised DataNodes, manipulating HDFS client interactions, or leveraging vulnerabilities in HDFS data integrity mechanisms. The attacker might corrupt data, inject malicious data, or cause data loss.
  • Impact: Data integrity compromise, incorrect application results, business disruption, data loss, reputational damage.
  • Affected Hadoop Component: HDFS (DataNodes, NameNode, HDFS Client)
  • Risk Severity: High
  • Mitigation Strategies:
    • Implement strong authentication and authorization to control access to HDFS write operations.
    • Harden DataNodes and monitor for unauthorized access or modifications.
    • Enable HDFS audit logging to track data access and modification events.
    • Utilize HDFS snapshots for data recovery and rollback in case of data corruption.

Threat: DataNode Compromise

  • Description: An attacker compromises a DataNode server. This could be achieved by exploiting vulnerabilities in the DataNode operating system, Hadoop services running on it, or through social engineering or physical access. Once compromised, the attacker can access data stored on the DataNode, potentially inject malicious data, or use the DataNode as a launchpad for further attacks within the cluster.
  • Impact: Confidentiality breach, data integrity compromise, availability issues, lateral movement within the cluster, resource abuse, potential cluster-wide compromise.
  • Affected Hadoop Component: HDFS (DataNode)
  • Risk Severity: Critical
  • Mitigation Strategies:
    • Harden DataNode operating systems and apply regular security patches.
    • Implement strong access controls and firewalls to restrict access to DataNodes.
    • Use intrusion detection and prevention systems (IDS/IPS) to monitor DataNode activity.
    • Implement endpoint detection and response (EDR) on DataNodes.
    • Regularly scan DataNodes for vulnerabilities.
    • Isolate DataNodes in a secure network segment.

Threat: NameNode Vulnerability Exploitation

  • Description: An attacker exploits a vulnerability in the NameNode service. This could be a software vulnerability in the NameNode itself or in underlying libraries. Successful exploitation could allow the attacker to gain control of the NameNode, leading to cluster-wide disruption, data corruption, or unauthorized access.
  • Impact: Availability compromise, business disruption, data inaccessibility, potential data integrity compromise, potential cluster-wide compromise.
  • Affected Hadoop Component: HDFS (NameNode)
  • Risk Severity: Critical
  • Mitigation Strategies:
    • Keep the NameNode software and its dependencies up-to-date with the latest security patches.
    • Harden the NameNode operating system and restrict access to the NameNode server.
    • Implement intrusion detection and prevention systems (IDS/IPS) to monitor NameNode activity.
    • Implement endpoint detection and response (EDR) on the NameNode server.
    • Regularly scan the NameNode for vulnerabilities.
    • Deploy a highly available NameNode setup (HA) to mitigate single point of failure risks.

Threat: ResourceManager Vulnerability Exploitation

  • Description: An attacker exploits a vulnerability in the YARN ResourceManager service. Similar to NameNode vulnerabilities, this could lead to control over the ResourceManager, disrupting resource allocation, application execution, and potentially the entire cluster.
  • Impact: Availability compromise, application failures, business disruption, potential cluster-wide compromise.
  • Affected Hadoop Component: YARN (ResourceManager)
  • Risk Severity: Critical
  • Mitigation Strategies:
    • Keep the ResourceManager software and its dependencies up-to-date with the latest security patches.
    • Harden the ResourceManager operating system and restrict access to the ResourceManager server.
    • Implement intrusion detection and prevention systems (IDS/IPS) to monitor ResourceManager activity.
    • Implement endpoint detection and response (EDR) on the ResourceManager server.
    • Regularly scan the ResourceManager for vulnerabilities.
    • Deploy a highly available ResourceManager setup (HA) to mitigate single point of failure risks.

Threat: NodeManager Compromise

  • Description: An attacker compromises a NodeManager server. Similar to DataNode compromise, this allows the attacker to execute arbitrary code on the node, access application data and resources running on that node, and potentially use the compromised NodeManager for further attacks.
  • Impact: Confidentiality breach, data integrity compromise, availability issues, lateral movement within the cluster, resource abuse, potential application compromise.
  • Affected Hadoop Component: YARN (NodeManager)
  • Risk Severity: High
  • Mitigation Strategies:
    • Harden NodeManager operating systems and apply regular security patches.
    • Implement strong access controls and firewalls to restrict access to NodeManagers.
    • Use intrusion detection and prevention systems (IDS/IPS) to monitor NodeManager activity.
    • Implement endpoint detection and response (EDR) on NodeManagers.
    • Regularly scan NodeManagers for vulnerabilities.
    • Isolate NodeManagers in a secure network segment.

Threat: Default Credentials and Weak Passwords

  • Description: Default credentials for Hadoop services or weak passwords for administrative accounts are used and not changed. Attackers can easily guess or find default credentials, gaining unauthorized access to Hadoop components and administrative functions.
  • Impact: Unauthorized access, compromise of confidentiality, integrity, and availability, potential cluster-wide compromise.
  • Affected Hadoop Component: Hadoop Core (All components with administrative interfaces)
  • Risk Severity: High
  • Mitigation Strategies:
    • Change all default passwords for Hadoop services and administrative accounts immediately after installation.
    • Enforce strong password policies for all Hadoop users and administrators.
    • Implement multi-factor authentication (MFA) for administrative access.
    • Regularly audit user accounts and credentials.

Threat: Lack of Patch Management and Vulnerability Management

  • Description: Hadoop components and underlying operating systems are not regularly patched and updated to address known vulnerabilities. This leaves the cluster vulnerable to exploitation of publicly known vulnerabilities.
  • Impact: Compromise of confidentiality, integrity, and availability through exploitation of known vulnerabilities, potential cluster-wide compromise.
  • Affected Hadoop Component: Hadoop Core (All components)
  • Risk Severity: High
  • Mitigation Strategies:
    • Establish a robust patch management process for Hadoop components and underlying operating systems.
    • Regularly scan Hadoop components and servers for vulnerabilities.
    • Prioritize patching of critical security vulnerabilities.
    • Automate patching processes where possible.
    • Subscribe to security advisories and vulnerability databases related to Hadoop.

Threat: Misconfigured Hadoop Security Features

  • Description: Hadoop security features like Kerberos, Ranger/Sentry, or encryption are misconfigured during setup or operation. This could result in weakened security posture, bypassing intended security controls, or creating vulnerabilities.
  • Impact: Compromise of confidentiality, integrity, and availability, depending on the specific misconfiguration.
  • Affected Hadoop Component: Hadoop Core (Security Configuration, Kerberos, Ranger/Sentry)
  • Risk Severity: High
  • Mitigation Strategies:
    • Follow security best practices and hardening guides when configuring Hadoop security features.
    • Thoroughly test and validate security configurations after implementation.
    • Regularly audit security configurations for misconfigurations and deviations from best practices.
    • Use configuration management tools to enforce consistent and secure configurations.