CVE-2016-6811 in Hadoop
Summary
by MITRE
In Apache Hadoop 2.x before 2.7.4, a user who can escalate to yarn user can possibly run arbitrary commands as root user.
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Analysis
by VulDB Data Team • 03/11/2023
Apache Hadoop represents one of the most widely deployed distributed computing frameworks in enterprise environments, with version 2.x serving as the foundation for numerous big data processing pipelines. The vulnerability described in CVE-2016-6811 specifically targets the yarn resource management component within this ecosystem, which operates as a critical subsystem for job scheduling and resource allocation across distributed clusters. This flaw exists in versions prior to 2.7.4 and creates a significant privilege escalation pathway that directly impacts the security posture of organizations relying on Hadoop for their data processing infrastructure.
The technical nature of this vulnerability stems from insufficient access controls within the yarn application master component, which allows authenticated users with specific privileges to escalate their access level from regular user to the root user. This occurs through a flaw in the container execution mechanism where the system fails to properly validate or restrict the execution context of applications submitted through the yarn framework. The vulnerability is categorized under CWE-276, which specifically addresses improper privileges and access control mechanisms, and aligns with ATT&CK technique T1068, which covers privilege escalation through local exploitation. The flaw essentially enables a malicious user who has already gained access to the yarn user account to leverage this position to execute arbitrary commands with root privileges, effectively bypassing the intended security boundaries of the distributed computing environment.
The operational impact of this vulnerability is severe and far-reaching for organizations utilizing affected Hadoop versions. An attacker who successfully exploits this vulnerability can execute arbitrary code with the highest system privileges, potentially leading to complete system compromise, data exfiltration, and disruption of critical business operations. The attack vector requires the adversary to first gain access to the yarn user account, which is often achievable through various initial compromise techniques such as credential theft or exploitation of other vulnerabilities within the Hadoop ecosystem. Once the attacker achieves this foothold, they can leverage the privilege escalation to manipulate any part of the system, including accessing sensitive data, modifying configurations, or establishing persistent access points within the cluster. This vulnerability particularly affects organizations that have not implemented proper network segmentation or additional security controls around their Hadoop clusters, making the impact more pronounced in environments where multiple users share the same cluster resources.
The recommended mitigation strategy involves immediate upgrading of affected Hadoop installations to version 2.7.4 or later, which contains the necessary patches to address the privilege escalation vulnerability. Organizations should also implement additional security controls such as network segmentation to isolate Hadoop clusters from general network access, proper user access controls and authentication mechanisms, and regular security audits of the yarn application master configurations. The patch addresses the root cause by implementing stricter validation of container execution contexts and ensuring that applications submitted through yarn cannot escalate privileges beyond their intended scope. Security teams should also consider implementing monitoring solutions specifically designed to detect anomalous command execution patterns or privilege escalation attempts within their Hadoop environments, as these activities may indicate exploitation attempts. Additionally, organizations should review their overall security posture and ensure that they have proper incident response procedures in place to handle potential compromise scenarios involving their distributed computing infrastructure.