Apache Spark Unauthorized Admin Access Scanner

Spark WebUI is a web-based interface used to monitor the performance and status of Apache Spark applications. It is primarily used by data scientists and developers who need to ensure their Spark jobs are running efficiently across cluster nodes. The Spark WebUI provides detailed insights and metrics about Spark applications, including executors, jobs, and stages. It can also reveal resource usage data, which aids in performance tuning and debugging. Typically, it's deployed in environments where Spark clusters are actively in use for large-scale data processing tasks. Protecting this interface from unauthorized access is crucial to maintain the security of cluster data and operations.

The Unauthorized Admin Access vulnerability occurs when the Spark WebUI is exposed to the internet without requiring user authentication. This vulnerability allows anyone with network access to view detailed Spark applications data without restrictions. Such access could potentially disclose sensitive information about the infrastructure and the data being processed. The lack of authentication measures grants an external actor the ability to access internal resources inadvertently. This oversight usually happens due to default configurations that prioritize ease of access over security. Exploiting this vulnerability may provide attackers with crucial insights to plan further attacks on the system.

Technically, the vulnerability is due to missing authentication steps in the Spark WebUI setup. Common endpoints that realize this vulnerability are often directly accessible, typically at default ports. The vulnerability manifests in setups where access restrictions haven't been placed on network or application level. Key parameters like IP address filtering or authentication mechanisms are neglected, leaving the Spark WebUI open to anyone scanning for these services. The exposed service could be particularly represented by the HTTP GET requests returning an HTTP status of 200 with the recognizable HTML titles and URL indicators within the page body.

Exploiting this vulnerability can lead to unauthorized access to sensitive Spark application data. Attackers could monitor job execution details and resource allocation, potentially identifying weak spots in job configurations. They could launch denial-of-service attacks by overloading resources with additional job submissions or interact with current jobs to disrupt performance. Additionally, insight into the cluster operations could lead to data theft, as actors could identify and target specific datasets. The privacy and integrity of the data processed on the Spark platform could thus be severely compromised if this vulnerability is exploited.

REFERENCES

• https://github.com/vulhub/vulhub/tree/master/spark/unacc