CVE-2018-9159 in Spark
Summary
by MITRE
In Spark before 2.7.2, a remote attacker can read unintended static files via various representations of absolute or relative pathnames, as demonstrated by file: URLs and directory traversal sequences. NOTE: this product is unrelated to Ignite Realtime Spark.
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Analysis
by VulDB Data Team • 02/26/2023
The vulnerability identified as CVE-2018-9159 affects Apache Spark versions prior to 2.7.2 and represents a critical path traversal flaw that allows remote attackers to access unintended static files through improper handling of absolute or relative pathnames. This vulnerability specifically manifests when Spark processes file: URLs and directory traversal sequences, creating an attack surface where malicious actors can potentially access sensitive system files, configuration data, or other unauthorized resources that should remain protected. The flaw stems from insufficient validation of file paths during resource resolution, enabling attackers to bypass normal access controls and retrieve files outside the intended directory boundaries.
The technical implementation of this vulnerability involves Spark's handling of file system operations where absolute or relative path representations are not properly sanitized or validated before being processed. When a file: URL is constructed with traversal sequences such as ../ or ..\, the system fails to adequately normalize or restrict these paths, allowing access to files in parent directories or other locations outside the expected scope. This behavior aligns with CWE-22, which describes improper limitation of a pathname to a restricted directory, commonly known as path traversal or directory traversal attacks. The vulnerability operates at the file system abstraction layer where Spark's resource resolution logic does not sufficiently validate the integrity of pathname representations, creating a direct pathway for unauthorized file access.
From an operational impact perspective, this vulnerability poses significant risks to organizations utilizing Apache Spark for data processing and analytics. Attackers could exploit this weakness to access sensitive configuration files, credentials, system logs, or other confidential data stored on the same system where Spark is deployed. The implications extend beyond simple file access, as this vulnerability could potentially lead to privilege escalation, data exfiltration, or further compromise of the underlying system infrastructure. The attack vector is particularly concerning because it can be executed remotely without requiring authentication, making it accessible to any attacker who can send requests to the Spark service. This vulnerability also aligns with ATT&CK technique T1083, which covers discovering file and directory permissions, as attackers can use path traversal to identify and access resources that should be restricted.
Organizations should implement immediate mitigations including upgrading to Apache Spark version 2.7.2 or later, which contains the necessary patches to address the path traversal vulnerability. Additional protective measures include implementing strict file access controls, configuring proper firewall rules to restrict access to Spark services, and monitoring system logs for suspicious file access patterns. Security teams should also consider implementing network segmentation to limit exposure of Spark services to untrusted networks and ensure that only authorized users can access the Spark cluster interfaces. The vulnerability demonstrates the critical importance of proper input validation and path normalization in distributed computing environments where file system access is required for data processing operations.