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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 affects Apache Spark versions 3.0.3 and earlier, versions 3.1.1 to 3.1.2, and versions 3.2.0 to 3.2.1.","2022-07-18",8.8,"v3.1","High",0.93244,{"cveId":296,"description":297,"publishedDate":298,"cvssScore":299,"cvssVersion":292,"severity":300,"isKev":17,"epssScore":301},"CVE-2020-27223","In Eclipse Jetty 9.4.6.v20170531 to 9.4.36.v20210114 (inclusive), 10.0.0, and 11.0.0 when Jetty handles a request containing multiple Accept headers with a large number of “quality” (i.e. q) parameters, the server may enter a denial of service (DoS) state due to high CPU usage processing those quality values, resulting in minutes of CPU time exhausted processing those quality values.","2021-02-26",5.2,"Medium",0.78031,{"cveId":303,"description":304,"publishedDate":305,"cvssScore":291,"cvssVersion":292,"severity":293,"isKev":17,"epssScore":306},"CVE-2023-32007","** 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.\n\nNOTE: This vulnerability only affects products that are no longer supported by the maintainer.\n\nUsers are recommended to upgrade to a supported version of Apache Spark, such as version 3.4.0.","2023-05-02",0.75955,{"cveId":308,"description":309,"publishedDate":310,"cvssScore":311,"cvssVersion":292,"severity":300,"isKev":17,"epssScore":312},"CVE-2018-11770","From version 1.3.0 onward, Apache Spark's standalone master exposes a REST API for job submission, in addition to the submission mechanism used by spark-submit. In standalone, the config property 'spark.authenticate.secret' establishes a shared secret for authenticating requests to submit jobs via spark-submit. However, the REST API does not use this or any other authentication mechanism, and this is not adequately documented. In this case, a user would be able to run a driver program without authenticating, but not launch executors, using the REST API. This REST API is also used by Mesos, when set up to run in cluster mode (i.e., when also running MesosClusterDispatcher), for job submission. Future versions of Spark will improve documentation on these points, and prohibit setting 'spark.authenticate.secret' when running the REST APIs, to make this clear. Future versions will also disable the REST API by default in the standalone master by changing the default value of 'spark.master.rest.enabled' to 'false'.","2018-08-13",4.2,0.6583,{"cveId":314,"description":315,"publishedDate":316,"cvssScore":317,"cvssVersion":292,"severity":318,"isKev":17,"epssScore":319},"CVE-2020-9480","In Apache Spark 2.4.5 and earlier, a standalone resource manager's master may be configured to require authentication (spark.authenticate) via a shared secret. When enabled, however, a specially-crafted RPC to the master can succeed in starting an application's resources on the Spark cluster, even without the shared key. This can be leveraged to execute shell commands on the host machine. This does not affect Spark clusters using other resource managers (YARN, Mesos, etc).","2020-06-23",9.8,"Critical",0.2937,{"cveId":321,"description":322,"publishedDate":323,"cvssScore":324,"cvssVersion":292,"severity":293,"isKev":17,"epssScore":325},"CVE-2019-10172","A flaw was found in org.codehaus.jackson:jackson-mapper-asl:1.9.x libraries. XML external entity vulnerabilities similar CVE-2016-3720 also affects codehaus jackson-mapper-asl libraries but in different classes.","2019-11-18",7.5,0.17044,{"cveId":327,"description":328,"publishedDate":329,"cvssScore":330,"cvssVersion":292,"severity":318,"isKev":17,"epssScore":331},"CVE-2019-20445","HttpObjectDecoder.java in Netty before 4.1.44 allows a Content-Length header to be accompanied by a second Content-Length header, or by a Transfer-Encoding header.","2020-01-29",9.1,0.13834,{"cveId":333,"description":334,"publishedDate":335,"cvssScore":317,"cvssVersion":336,"severity":318,"isKev":17,"epssScore":337},"CVE-2018-17190","In all versions of Apache Spark, its standalone resource manager accepts code to execute on a 'master' host, that then runs that code on 'worker' hosts. The master itself does not, by design, execute user code. A specially-crafted request to the master can, however, cause the master to execute code too. Note that this does not affect standalone clusters with authentication enabled. While the master host typically has less outbound access to other resources than a worker, the execution of code on the master is nevertheless unexpected.","2018-11-19","v3.0",0.08792,{"cveId":339,"description":340,"publishedDate":341,"cvssScore":342,"cvssVersion":292,"severity":300,"isKev":17,"epssScore":343},"CVE-2020-27218","In Eclipse Jetty version 9.4.0.RC0 to 9.4.34.v20201102, 10.0.0.alpha0 to 10.0.0.beta2, and 11.0.0.alpha0 to 11.0.0.beta2, if GZIP request body inflation is enabled and requests from different clients are multiplexed onto a single connection, and if an attacker can send a request with a body that is received entirely but not consumed by the application, then a subsequent request on the same connection will see that body prepended to its body. The attacker will not see any data but may inject data into the body of the subsequent request.","2020-11-28",4.8,0.08277,{"cveId":345,"description":346,"publishedDate":347,"cvssScore":324,"cvssVersion":292,"severity":293,"isKev":17,"epssScore":348},"CVE-2018-11804","Spark's Apache Maven-based build includes a convenience script, 'build\u002Fmvn', that downloads and runs a zinc server to speed up compilation. It has been included in release branches since 1.3.x, up to and including master. This server will accept connections from external hosts by default. A specially-crafted request to the zinc server could cause it to reveal information in files readable to the developer account running the build. Note that this issue does not affect end users of Spark, only developers building Spark from source code.","2018-10-24",0.05696,[350],{"cveId":288,"description":289,"publishedDate":290,"cvssScore":291,"severity":293,"isKev":4,"epssScore":294,"cisaVulnName":351,"cisaDateAdded":352,"cisaShortDescription":353,"cisaRequiredAction":354},"Apache Spark Command Injection Vulnerability","2023-03-07","Apache Spark contains a command injection vulnerability via Spark User Interface (UI) when Access Control Lists (ACLs) are enabled.","Apply updates per vendor instructions.",{"title":356,"metaDescription":357,"keywords":358,"structuredData":359},"Spark by Apache - Security Vulnerabilities & Analysis | Precursor Intelligence","Comprehensive security analysis for Spark by Apache covering 89 versions with 20 tracked vulnerabilities including 0 critical and 1 high-severity issues and 1 CISA KEV vulnerability. Real-time threat intelligence, CVE tracking, and security recommendations.","Spark vulnerabilities, Spark security, Spark CVE, Apache Spark, Spark threat intelligence, Apache security, product security analysis, cybersecurity threats, vulnerability management, CVE tracking, Spark KEV, Spark exploited vulnerabilities",{"@context":360,"@type":361,"name":362,"description":357,"url":363,"manufacturer":364,"applicationCategory":368,"softwareVersion":369,"mainEntity":370},"https:\u002F\u002Fschema.org","SoftwareApplication","Spark","https:\u002F\u002Fprecursorintelligence.com\u002Fvulnerabilities\u002Ftechnologies\u002Fvendors\u002Fapache\u002Fspark",{"@type":365,"name":366,"url":367},"Organization","Apache","https:\u002F\u002Fprecursorintelligence.com\u002Fvendors\u002Fapache","Security Software","89 versions tracked",{"@type":371,"name":372,"description":373,"vulnerabilityCount":10,"dateModified":12},"SecurityVulnerability","Spark Security Vulnerabilities","Security vulnerabilities affecting Spark by Apache",{"totalVersions":9,"totalVulnerabilities":10,"kevVulnerabilities":11,"lastUpdated":12,"generatedAt":375,"apiVersion":376},"2026-10-17T13:07:15.745Z","3.0",{"rows":378,"total":11,"capped":17,"failed":11},[379],{"cveId":288,"name":351,"severity":293,"cvss":291,"added":352,"epss":294,"published":290,"ranges":380,"hits":381,"checked":17,"covers":17},[],[],[]]