EUVD-2018-0127

Malware in sbrugna...

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...

Code injection

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...

PYSEC-2019-114

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...

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...

Exposure of Sensitive Information to an Unauthorized Actor in Apache Spark

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...

Apache Spark Spoofing Vulnerability

Apache Spark is a large-scale data processing engine that supports acyclic data streaming and in-memory computation. Apache Spark versions 1.0.0 through 2.1.2, 2.2.0 through 2.2.1, and 2.3.0 have a spoofing vulnerability in the implementation. When running PySpark and SparkR, a local attacker can...

Local Privilege Escalation

spark-core is vulnerable to privilege escalation. The application does not implement the SparkR communication protocol properly, allowing a malicious user with local access the ability to impersonate another user running the application...

PYSEC-2018-25

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...

Code injection

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...

PYSEC-2018-25

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-2018-1334

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...

CVE-2018-1334

Apache Spark up to version 2.3.0 (affected: 1.0.0–2.1.2, 2.2.0–2.2.1, 2.3.0) is vulnerable to an impersonation flaw when using PySpark or SparkR that lets a different local user connect to a Spark application and impersonate the Spark user. The issue is confirmed across multiple sources (e.g., SU...

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...