Product:

Spark

(Apache)
Repositories

Unknown:

This might be proprietary software.
#Vulnerabilities 19
Date Id Summary Products Score Patch Annotated
2018-07-12 CVE-2018-1334 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. Spark 4.7
2018-07-12 CVE-2018-8024 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. Spark, Firefox 5.4
2018-11-19 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... Spark 9.8
2019-02-04 CVE-2018-11760 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. Spark 5.5
2019-08-07 CVE-2019-10099 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. Spark 7.5
2020-01-29 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. Spark, Ubuntu_linux, Debian_linux, Fedora, Netty, Jboss_amq_clients, Jboss_enterprise_application_platform 9.1
2019-11-18 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. Spark, Debian_linux, Jackson\-Mapper\-Asl, Jboss_enterprise_application_platform, Jboss_fuse 7.5
2017-07-12 CVE-2017-7678 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... Spark 6.1
2017-09-13 CVE-2017-12612 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... Spark 7.8