Total
19 CVE
| CVE | Vendors | Products | Updated | CVSS v2 | CVSS v3 |
|---|---|---|---|---|---|
| CVE-2023-32007 | 1 Apache | 1 Spark | 2024-10-15 | N/A | 8.8 HIGH |
| ** 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. | |||||
| CVE-2018-11804 | 1 Apache | 1 Spark | 2024-06-10 | 5.0 MEDIUM | 7.5 HIGH |
| Spark's Apache Maven-based build includes a convenience script, 'build/mvn', 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. | |||||
| CVE-2018-11770 | 1 Apache | 1 Spark | 2024-06-10 | 4.9 MEDIUM | 4.2 MEDIUM |
| 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'. | |||||
| CVE-2020-27218 | 5 Apache, Debian, Eclipse and 2 more | 17 Kafka, Spark, Debian Linux and 14 more | 2024-02-16 | 5.8 MEDIUM | 4.8 MEDIUM |
| 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. | |||||
| CVE-2023-22946 | 1 Apache | 1 Spark | 2024-02-04 | N/A | 9.9 CRITICAL |
| In Apache Spark versions prior to 3.4.0, applications using spark-submit can specify a 'proxy-user' to run as, limiting privileges. The application can execute code with the privileges of the submitting user, however, by providing malicious configuration-related classes on the classpath. This affects architectures relying on proxy-user, for example those using Apache Livy to manage submitted applications. Update to Apache Spark 3.4.0 or later, and ensure that spark.submit.proxyUser.allowCustomClasspathInClusterMode is set to its default of "false", and is not overridden by submitted applications. | |||||
| CVE-2022-31777 | 1 Apache | 1 Spark | 2024-02-04 | N/A | 5.4 MEDIUM |
| A stored cross-site scripting (XSS) vulnerability in Apache Spark 3.2.1 and earlier, and 3.3.0, allows remote attackers to execute arbitrary JavaScript in the web browser of a user, by including a malicious payload into the logs which would be returned in logs rendered in the UI. | |||||
| CVE-2022-33891 | 1 Apache | 1 Spark | 2024-02-04 | N/A | 8.8 HIGH |
| 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 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. | |||||
| CVE-2021-38296 | 1 Apache | 1 Spark | 2024-02-04 | 5.0 MEDIUM | 7.5 HIGH |
| Apache Spark supports end-to-end encryption of RPC connections via "spark.authenticate" and "spark.network.crypto.enabled". In versions 3.1.2 and earlier, it uses a bespoke mutual authentication protocol that allows for full encryption key recovery. After an initial interactive attack, this would allow someone to decrypt plaintext traffic offline. Note that this does not affect security mechanisms controlled by "spark.authenticate.enableSaslEncryption", "spark.io.encryption.enabled", "spark.ssl", "spark.ui.strictTransportSecurity". Update to Apache Spark 3.1.3 or later | |||||
| CVE-2020-27223 | 5 Apache, Debian, Eclipse and 2 more | 16 Nifi, Solr, Spark and 13 more | 2024-02-04 | 4.3 MEDIUM | 5.3 MEDIUM |
| 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. | |||||
| CVE-2020-9480 | 2 Apache, Oracle | 2 Spark, Business Intelligence | 2024-02-04 | 9.3 HIGH | 9.8 CRITICAL |
| 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). | |||||
| CVE-2019-20445 | 6 Apache, Canonical, Debian and 3 more | 8 Spark, Ubuntu Linux, Debian Linux and 5 more | 2024-02-04 | 6.4 MEDIUM | 9.1 CRITICAL |
| 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. | |||||
| CVE-2019-10172 | 4 Apache, Debian, Fasterxml and 1 more | 5 Spark, Debian Linux, Jackson-mapper-asl and 2 more | 2024-02-04 | 5.0 MEDIUM | 7.5 HIGH |
| 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. | |||||
| CVE-2019-10099 | 1 Apache | 1 Spark | 2024-02-04 | 4.3 MEDIUM | 7.5 HIGH |
| Prior to Spark 2.3.3, in certain situations Spark would write user data to local disk unencrypted, even if spark.io.encryption.enabled=true. This includes cached blocks that are fetched to disk (controlled by spark.maxRemoteBlockSizeFetchToMem); in SparkR, using parallelize; in Pyspark, using broadcast and parallelize; and use of python udfs. | |||||
| CVE-2018-1334 | 1 Apache | 1 Spark | 2024-02-04 | 1.9 LOW | 4.7 MEDIUM |
| In Apache Spark 1.0.0 to 2.1.2, 2.2.0 to 2.2.1, and 2.3.0, when using PySpark or SparkR, it's possible for a different local user to connect to the Spark application and impersonate the user running the Spark application. | |||||
| CVE-2018-17190 | 1 Apache | 1 Spark | 2024-02-04 | 7.5 HIGH | 9.8 CRITICAL |
| 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. | |||||
| CVE-2018-8024 | 2 Apache, Mozilla | 2 Spark, Firefox | 2024-02-04 | 4.9 MEDIUM | 5.4 MEDIUM |
| In Apache Spark 2.1.0 to 2.1.2, 2.2.0 to 2.2.1, and 2.3.0, it's possible for a malicious user to construct a URL pointing to a Spark cluster's UI's job and stage info pages, and if a user can be tricked into accessing the URL, can be used to cause script to execute and expose information from the user's view of the Spark UI. While some browsers like recent versions of Chrome and Safari are able to block this type of attack, current versions of Firefox (and possibly others) do not. | |||||
| CVE-2018-11760 | 1 Apache | 1 Spark | 2024-02-04 | 2.1 LOW | 5.5 MEDIUM |
| When using PySpark , it's possible for a different local user to connect to the Spark application and impersonate the user running the Spark application. This affects versions 1.x, 2.0.x, 2.1.x, 2.2.0 to 2.2.2, and 2.3.0 to 2.3.1. | |||||
| CVE-2017-12612 | 1 Apache | 1 Spark | 2024-02-04 | 7.2 HIGH | 7.8 HIGH |
| In Apache Spark 1.6.0 until 2.1.1, the launcher API performs unsafe deserialization of data received by its socket. This makes applications launched programmatically using the launcher API potentially vulnerable to arbitrary code execution by an attacker with access to any user account on the local machine. It does not affect apps run by spark-submit or spark-shell. The attacker would be able to execute code as the user that ran the Spark application. Users are encouraged to update to version 2.2.0 or later. | |||||
| CVE-2017-7678 | 1 Apache | 1 Spark | 2024-02-04 | 4.3 MEDIUM | 6.1 MEDIUM |
| In Apache Spark before 2.2.0, it is possible for an attacker to take advantage of a user's trust in the server to trick them into visiting a link that points to a shared Spark cluster and submits data including MHTML to the Spark master, or history server. This data, which could contain a script, would then be reflected back to the user and could be evaluated and executed by MS Windows-based clients. It is not an attack on Spark itself, but on the user, who may then execute the script inadvertently when viewing elements of the Spark web UIs. | |||||