org.apache.spark:spark-core_2.10@2.0.1 vulnerabilities

Direct Vulnerabilities

Known vulnerabilities in the org.apache.spark:spark-core_2.10 package. This does not include vulnerabilities belonging to this package’s dependencies.

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Vulnerability Vulnerable Version
  • C
Arbitrary Code Execution

org.apache.spark:spark-core_2.10 is a cluster computing system for Big Data.

Affected versions of this package are vulnerable to Arbitrary Code Execution. The 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.

How to fix Arbitrary Code Execution?

There is no fixed version for org.apache.spark:spark-core_2.10.

[0,)
  • M
Information Exposure

org.apache.spark:spark-core_2.10 is a cluster computing system for Big Data.

Affected versions of this package are vulnerable to Information Exposure. 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.

How to fix Information Exposure?

There is no fixed version for org.apache.spark:spark-core_2.10.

[0,)
  • H
Information Exposure

org.apache.spark:spark-core_2.10 is a cluster computing system for Big Data.

Affected versions of this package are vulnerable to Information Exposure. 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 This vulnerability only affects developers building Spark from source code, and does not affect Spark end users.

[0,)
  • M
Insecure Defaults

org.apache.spark:spark-core is a fast and general cluster computing system for Big Data.

Affected versions of this package are vulnerable to Insecure Defaults. 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. 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.

How to fix Insecure Defaults?

There is no fix version for org.apache.spark:spark-core. To mitigate the problem, standalone masters, should disable the REST API by setting spark.master.rest.enabled to false if it is unused, and/or ensure that all network access to the REST API is restricted to hosts that are trusted to submit jobs. Mesos users can stop the MesosClusterDispatcher, though that will prevent them from running jobs in cluster mode. Alternatively, they can ensure access to the MesosRestSubmissionServer is restricted to trusted hosts.

[1.3.0,)
  • M
Cross-site Scripting (XSS)

Apache Spark is a general cluster computing system for Big Data.

Affected versions of this package are vulnerable to Cross-site Scripting (XSS) attacks. It is 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.

How to fix Cross-site Scripting (XSS)?

Upgrade org.apache.spark:spark-core to version 2.1.3, 2.2.2, 2.3.1 or higher.

[,2.1.3) [2.2.0,2.2.2)
  • H
Deserialization of Untrusted Data

org.apache.spark:spark-core is a general cluster computing system for Big Data.

Affected versions of this package are vulnerable to Deserialization of Untrusted Data. 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.

How to fix Deserialization of Untrusted Data?

Upgrade org.apache.spark:spark-core to versions 2.1.2 or higher.

[1.6.0,2.1.2)
  • H
Deserialization of Untrusted Data

org.apache.spark:spark-core_2.10 is a general cluster computing system for Big Data.

Affected versions of this package are vulnerable to Deserialization of Untrusted Data. 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.

How to fix Deserialization of Untrusted Data?

Upgrade org.apache.spark:spark-core_2.10 to versions 2.1.2 or higher.

[1.6.0,2.1.2)
  • M
Privilege Escalation

org.apache.spark:spark-core_2.10 is a cluster computing system for Big Data.

Affected versions of this package are vulnerable to Privilege Escalation. When using PySpark or SparkR, it was possible for a different local user to connect to the Spark application and impersonate the user running the Spark application.

How to fix Privilege Escalation?

Upgrade org.apache.spark:spark-core_2.10 to version 2.1.3, 2.2.2 or higher.

[,2.1.3) [2.2.0,2.2.2)
  • M
Cross-site Scripting (XSS)

org.apache.spark:spark-core is a fast and general cluster computing system for Big Data.

Affected versions of this package are vulnerable to Cross-site Scripting (XSS) attacks.

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.

How to fix Cross-site Scripting (XSS)?

Upgrade org.apache.spark:spark-core to version 2.2.0 or higher.

[,2.2.0)
  • M
Cross-site Scripting (XSS)

org.apache.spark:spark-core_2.10 is a fast and general cluster computing system for Big Data.

Affected versions of this package are vulnerable to Cross-site Scripting (XSS) attacks.

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.

How to fix Cross-site Scripting (XSS)?

Upgrade org.apache.spark:spark-core_2.10 to version 2.2.0 or higher.

[,2.2.0)