Evidence used
- No CISA KEV confirmation is currently recorded.
- EPSS is 75.95% for the current model date.
BlackTreeCVE IntelligenceApache Software Foundation · Apache Spark
High technical severity; prioritise exposed affected systems while verifying vendor guidance.
These OSV and GitHub advisory ranges apply only to the named package and ecosystem. A listed fixed version is not a universal product patch or proof that an update is installed.
| Ecosystem and package | Affected range | First fixed version | Evidence |
|---|---|---|---|
| mavenorg.apache.spark:spark-parent_2.12 | >= 3.1.1, < 3.2.2 | 3.2.2 | GitHub advisory ↗github reviewed aggregator · 13 Feb 2025 |
| pippyspark | >= 3.1.1, < 3.2.2 | 3.2.2 | GitHub advisory ↗github reviewed aggregator · 13 Feb 2025 |
High technical severity; prioritise exposed affected systems while verifying vendor guidance.
Fix not verified** 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.
** 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.
Untrusted input reaches a command interpreter without sufficient validation or separation from command syntax.
An attacker operating through a network path may attempt exploitation with low privileges. If successful, the issue may cause the confidentiality, integrity or availability impact described by the vendor.
** 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.
Untrusted input reaches a command interpreter without sufficient validation or separation from command syntax.
An attacker operating through a network path may attempt exploitation with low privileges. If successful, the issue may cause the confidentiality, integrity or availability impact described by the vendor.
CVSS severity, EPSS forecast probability, public exploit material and CISA-confirmed exploitation are separate signals.
No CISA KEV match was present at the last successful refresh. This means no confirmation from that source, not proof of no exploitation.
No exploit-tagged reference or CISA SSVC proof-of-concept state is currently recorded. Research may still exist outside the structured feeds.
CWE-77: Improper Neutralization of Special Elements used in a Command ('Command Injection'). The product constructs all or part of a command using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the intended command when it is sent to a downstream component.
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:HCommon Vulnerability Scoring System 3.1: the compact vector below is decoded into plain language.
Operational remediation based on structured source evidence.
Published 2 May 2023 · Last source change 13 Feb 2025, 16:50 UTC · CWE-77 · Improper Neutralization of Special Elements used in a Command ('Command Injection')
Core structured fields are present and their contributing authorities are shown above.
No material field changes have been recorded since change tracking began. Routine source refreshes and cosmetic edits are intentionally excluded.