CVE-2018-8024 in Spark
Summary
by MITRE
In Apache Spark 1.0.0 to 2.1.2, 2.2.0 to 2.2.1, and 2.3.0, it's possible for a malicious user to construct a URL pointing to a Spark cluster's UI's job and stage info pages, and if a user can be tricked into accessing the URL, can be used to cause script to execute and expose information from the user's view of the Spark UI.
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Analysis
by VulDB Data Team • 03/04/2020
Apache Spark versions 1.0.0 through 2.1.2, 2.2.0 through 2.2.1, and 2.3.0 contain a critical cross-site scripting vulnerability that enables malicious actors to construct specially crafted URLs that can execute arbitrary scripts within the context of a user's browser session when accessing Spark cluster UI pages. This vulnerability specifically affects the job and stage information pages of the Spark web interface, creating a pathway for attackers to exploit user trust and execute malicious code in the victim's browser environment.
The technical flaw stems from insufficient input validation and output encoding within the Spark UI's handling of URL parameters and user-provided data. When users navigate to job or stage information pages, the application fails to properly sanitize or escape user-controllable input, allowing malicious payloads to be injected directly into the web page content. This creates a classic cross-site scripting condition where attacker-controlled JavaScript code can execute with the privileges of the authenticated user, potentially leading to complete session compromise and unauthorized access to cluster resources.
The operational impact of this vulnerability extends beyond simple information disclosure, as it enables a range of malicious activities including session hijacking, data exfiltration, and privilege escalation within the Spark cluster environment. An attacker who successfully tricks a user into accessing a maliciously crafted URL can potentially access sensitive cluster information, monitor user activities, and even execute unauthorized operations against the Spark cluster. The vulnerability is particularly dangerous because it leverages the trust relationship between users and the Spark UI, making it difficult to detect and prevent through traditional network monitoring approaches.
This vulnerability aligns with CWE-79 Cross-site Scripting and maps to several ATT&CK techniques including T1566 Initial Access through malicious links and T1071.004 Application Layer Protocol: Web Protocols. The attack surface is significant given that Spark clusters are commonly deployed in enterprise environments where users frequently access cluster UIs for monitoring and management purposes. Organizations should prioritize immediate patching of affected versions and implement additional security controls such as web application firewalls, content security policies, and user education programs to mitigate the risk of exploitation.
Mitigation strategies include upgrading to Apache Spark versions 2.3.1 or later where this vulnerability has been addressed, implementing strict input validation on all user-provided parameters, and deploying content security policies that prevent execution of unauthorized scripts within the Spark UI context. Network administrators should also consider restricting direct access to Spark cluster UIs from untrusted networks and implementing additional authentication layers to reduce the attack surface. The vulnerability demonstrates the critical importance of input validation and output encoding in web applications, particularly in distributed computing environments where cluster management interfaces are frequently accessed by multiple users with varying privilege levels.