CVE-2017-12625 in Hive
Summary
by MITRE
Apache Hive 2.1.x before 2.1.2, 2.2.x before 2.2.1, and 2.3.x before 2.3.1 expose an interface through which masking policies can be defined on tables or views, e.g., using Apache Ranger. When a view is created over a given table, the policy enforcement does not happen correctly on the table for masked columns.
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Analysis
by VulDB Data Team • 01/21/2021
Apache Hive vulnerability CVE-2017-12625 represents a critical data masking and access control flaw that affects multiple versions of the Apache Hive data warehouse system. This vulnerability specifically targets the implementation of masking policies within Hive's security framework, where the system fails to properly enforce access controls when views are created over underlying tables containing sensitive data. The flaw exists in the interaction between Hive's policy enforcement mechanisms and its view creation functionality, creating a scenario where data masking rules defined through external systems like Apache Ranger are bypassed or improperly applied when users query data through views.
The technical implementation of this vulnerability stems from a failure in Hive's authorization model where the system does not correctly validate or enforce masking policies when processing queries against views that reference tables containing masked columns. This occurs because the policy enforcement mechanism operates at the table level but fails to maintain proper enforcement when data is accessed through view abstractions. The vulnerability is particularly concerning as it allows unauthorized access to sensitive data that should be masked according to defined security policies, effectively creating a data leakage scenario where users can bypass access controls through view-based queries. The flaw impacts the fundamental security model of Hive by undermining the principle of least privilege and data protection mechanisms that organizations rely on to maintain compliance with data governance requirements.
The operational impact of CVE-2017-12625 extends beyond simple data exposure to encompass broader security implications for organizations using Hive for data analytics and processing. When this vulnerability is exploited, it allows attackers or unauthorized users to access masked data through view queries, potentially exposing sensitive information that should remain protected according to established security policies. This vulnerability directly violates the security controls implemented through Apache Ranger and other policy management systems, undermining the trust organizations place in their data protection mechanisms. The impact is particularly severe in regulated environments where data masking is required for compliance with standards such as gdpr, hipaa, or pci dss, as this vulnerability can result in unintentional data breaches and compliance violations that may lead to significant regulatory penalties.
Organizations affected by CVE-2017-12625 should implement immediate mitigations including upgrading to patched versions of Hive 2.1.2, 2.2.1, or 2.3.1, depending on their current version. The vulnerability is classified under CWE-284 Access Control Flaws, specifically related to insufficient access control enforcement and improper privilege management within data processing systems. From an ATT&CK framework perspective, this vulnerability maps to privilege escalation and data exposure techniques, as attackers can leverage the flaw to gain unauthorized access to sensitive data through legitimate query interfaces. Additional mitigations include implementing additional monitoring and logging of view creation and access patterns, ensuring proper testing of access control policies, and conducting comprehensive audits of existing views and masking policies to identify potential exposure scenarios. Organizations should also consider implementing network segmentation and additional access controls to limit exposure, as this vulnerability can be exploited both internally and externally depending on system configuration and access controls in place.