First published: Wed Aug 07 2019(Updated: )
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.
Credit: security@apache.org security@apache.org
Affected Software | Affected Version | How to fix |
---|---|---|
Apache Spark | >=1.0.2<=1.6.3 | |
Apache Spark | >=2.0.0<=2.0.2 | |
Apache Spark | >=2.1.0<=2.1.3 | |
Apache Spark | >=2.2.0<=2.2.2 | |
Apache Spark | >=2.3.0<2.3.2 | |
pip/pyspark | >=0<2.3.3 | 2.3.3 |
maven/org.apache.spark:spark-core_2.11 | <2.3.3 | 2.3.3 |
Sign up to SecAlerts for real-time vulnerability data matched to your software, aggregated from hundreds of sources.
The severity of CVE-2019-10099 is rated as high with a score of 7.5.
To mitigate CVE-2019-10099, users should upgrade to Spark version 2.3.3 or higher where the vulnerability has been fixed.
CVE-2019-10099 affects Apache Spark versions ranging from 1.0.2 to 2.3.2.
CVE-2019-10099 is classified under CWE-312, which is related to cleartext storage of sensitive information vulnerability.