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medium·Product Based Web Vulnerabilities·Updated Jun 10, 2025

Apache Spark Security Misconfiguration Scanner

This scanner detects the use of Apache Spark UI exposed on the internet in digital assets. The exposure of the UI can lead to the leakage of sensitive job and cluster information, making it a critical security risk.

Est. Time~10 seconds
Scan TypeGroup Scan
Targetsurl
CostFree
3.5k
Times Used
continuous scan runs
0
Continuously Checked
assets under CS
2
Vulnerabilities Found
confirmed findings
References
Detail

Apache Spark is an open-source unified analytics engine used for large-scale data processing. It is widely used across various industries, including finance, healthcare, and technology, to process and analyze large datasets quickly and efficiently. Companies and data analysts utilize Apache Spark for its speed, ease of use, and ability to handle big data workloads across distributed computing clusters. The Spark Application UI is critical for monitoring and managing these jobs, providing insights into job execution and cluster status. When securely configured, it is only accessible internally to prevent leakage of sensitive information.

The vulnerability detected involves the exposure of the Apache Spark Application UI to the internet. This exposure occurs when the UI, usually intended for internal access, is incorrectly configured to be accessible externally. As a result, external users may gain unauthorized visibility into Spark job executions and clusters. This security misconfiguration can lead to unauthorized data access and potential manipulation if not corrected. Securing the Application UI access to within trusted networks is crucial to mitigate the associated risks.

The technical details of the vulnerability include the exposure of the Apache Spark UI, which typically runs on port 4040, without proper authentication. The endpoint that is vulnerable is the URL path containing job information, potentially leaking sensitive data about active Spark jobs and application states. Proper configuration and access control can mitigate this exposure. Ensuring that the UI listens only on internal interfaces or is secured via authentication can help prevent unwanted access.

When exploited, this vulnerability can lead to significant security risks such as unauthorized data access, exposure of sensitive job information, and even manipulation of computational tasks. Malicious actors gaining access to this information could analyze job structures, gain insights into data processing workflows, or disrupt scheduled jobs. Organizations risk data breaches and loss of confidentiality if the UI is left exposed.

REFERENCES

Solution Advice
  • Restrict access to the Spark Application UI to internal networks only.
  • Implement authentication mechanisms to secure the UI.
  • Regularly review firewall and access control settings to ensure compliance.
  • Monitor and log access to the UI for unauthorized access attempts.

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Apache Spark Security Misconfiguration Scanner | S4E