CVE-2023-32007

Apache Spark: Shell command injection via Spark UI

Description

** UNSUPPORTED WHEN ASSIGNED ** The Apache Spark UI offers the possibility to enable ACLs via the configuration option spark.acls.enable. With an authentication filter, this checks whether a user has access permissions to view or modify the application. If ACLs are enabled, a code path in HttpSecurityFilter can allow someone to perform impersonation by providing an arbitrary user name. A malicious user might then be able to reach a permission check function that will ultimately build a Unix shell command based on their input, and execute it. This will result in arbitrary shell command execution as the user Spark is currently running as. This issue was disclosed earlier as CVE-2022-33891, but incorrectly claimed version 3.1.3 (which has since gone EOL) would not be affected. NOTE: This vulnerability only affects products that are no longer supported by the maintainer. Users are recommended to upgrade to a supported version of Apache Spark, such as version 3.4.0.

Category

8.8
CVSS
Severity: High
CVSS 3.1 •
EPSS 90.78% Top 5%
Vendor Advisory apache.org Vendor Advisory apache.org
Affected: Apache Software Foundation Apache Spark
Published at:
Updated at:

References

Frequently Asked Questions

What is the severity of CVE-2023-32007?
CVE-2023-32007 has been scored as a high severity vulnerability.
How to fix CVE-2023-32007?
To fix CVE-2023-32007, make sure you are using an up-to-date version of the affected component(s) by checking the vendor release notes. As for now, there are no other specific guidelines available.
Is CVE-2023-32007 being actively exploited in the wild?
It is possible that CVE-2023-32007 is being exploited or will be exploited in a near future based on public information. According to its EPSS score, there is a ~91% probability that this vulnerability will be exploited by malicious actors in the next 30 days.
What software or system is affected by CVE-2023-32007?
CVE-2023-32007 affects Apache Software Foundation Apache Spark.
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