Описание
Sensitive data written to disk unencrypted in Spark
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.
Ссылки
- https://nvd.nist.gov/vuln/detail/CVE-2019-10099
- https://github.com/pypa/advisory-database/tree/main/vulns/pyspark/PYSEC-2019-114.yaml
- https://lists.apache.org/thread.html/c2a39c207421797f82823a8aff488dcd332d9544038307bf69a2ba9e@%3Cuser.spark.apache.org%3E
- https://lists.apache.org/thread.html/ra216b7b0dd82a2c12c2df9d6095e689eb3f3d28164e6b6587da69fae@%3Ccommits.spark.apache.org%3E
- https://lists.apache.org/thread.html/rabe1d47e2bf8b8f6d9f3068c8d2679731d57fa73b3a7ed1fa82406d2@%3Cissues.spark.apache.org%3E
Пакеты
org.apache.spark:spark-core_2.11
< 2.3.3
2.3.3
pyspark
< 2.3.3
2.3.3
Связанные уязвимости
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.
Prior to Spark 2.3.3, in certain situations Spark would write user dat ...