Spark Apache Spark

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By the Year

In 2022 there have been 1 vulnerability in Apache Spark with an average score of 7.5 out of ten. Last year Spark had 1 security vulnerability published. If vulnerabilities keep coming in at the current rate, it appears that number of security vulnerabilities in Spark in 2022 could surpass last years number. However, the average CVE base score of the vulnerabilities in 2022 is greater by 2.20.

Year Vulnerabilities Average Score
2022 1 7.50
2021 1 5.30
2020 3 7.90
2019 3 6.83
2018 5 6.32

It may take a day or so for new Spark vulnerabilities to show up in the stats or in the list of recent security vulnerabilties. Additionally vulnerabilities may be tagged under a different product or component name.

Recent Apache Spark Security Vulnerabilities

Apache Spark supports end-to-end encryption of RPC connections via "spark.authenticate" and "spark.network.crypto.enabled"

CVE-2021-38296 7.5 - High - March 10, 2022

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

Authentication Bypass by Capture-replay

In Eclipse Jetty 9.4.6.v20170531 to 9.4.36.v20210114 (inclusive)

CVE-2020-27223 5.3 - Medium - February 26, 2021

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.

Resource Exhaustion

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

CVE-2020-27218 4.8 - Medium - November 28, 2020

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.

In Apache Spark 2.4.5 and earlier, a standalone resource manager's master may be configured to require authentication (spark.authenticate)

CVE-2020-9480 9.8 - Critical - June 23, 2020

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).

Missing Authentication for Critical Function

HttpObjectDecoder.java in Netty before 4.1.44

CVE-2019-20445 9.1 - Critical - January 29, 2020

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.

HTTP Request Smuggling

A flaw was found in org.codehaus.jackson:jackson-mapper-asl:1.9.x libraries

CVE-2019-10172 7.5 - High - November 18, 2019

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.

XXE

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

CVE-2019-10099 7.5 - High - August 07, 2019

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.

Cleartext Storage of Sensitive Information

When using PySpark

CVE-2018-11760 5.5 - Medium - February 04, 2019

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.

In all versions of Apache Spark, its standalone resource manager accepts code to execute on a 'master' host

CVE-2018-17190 9.8 - Critical - November 19, 2018

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.

Spark's Apache Maven-based build includes a convenience script, 'build/mvn', that downloads and runs a zinc server to speed up compilation

CVE-2018-11804 7.5 - High - October 24, 2018

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.

Improper Input Validation

From version 1.3.0 onward

CVE-2018-11770 4.2 - Medium - August 13, 2018

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'.

authentification

In Apache Spark 1.0.0 to 2.1.2

CVE-2018-1334 4.7 - Medium - July 12, 2018

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.

Information Disclosure

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

CVE-2018-8024 5.4 - Medium - July 12, 2018

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.

Information Disclosure

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