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Total
7 CVE
| CVE | Vendors | Products | Updated | CVSS v2 | CVSS v3 |
|---|---|---|---|---|---|
| CVE-2020-27218 | 4 Apache, Eclipse, Netapp and 1 more | 16 Kafka, Spark, Jetty and 13 more | 2022-05-12 | 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-2020-27223 | 5 Apache, Debian, Eclipse and 2 more | 16 Nifi, Solr, Spark and 13 more | 2021-09-16 | 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-2018-11760 | 1 Apache | 1 Spark | 2019-10-03 | 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-2018-11770 | 1 Apache | 1 Spark | 2019-10-03 | 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-2018-8024 | 2 Apache, Mozilla | 2 Spark, Firefox | 2019-02-28 | 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-2018-1334 | 1 Apache | 1 Spark | 2018-09-10 | 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-2017-7678 | 1 Apache | 1 Spark | 2017-07-26 | 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. | |||||