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| purl | pkg:maven/org.apache.spark/spark-core_2.11@2.3.3 |
| Next non-vulnerable version | None. |
| Latest non-vulnerable version | None. |
| Risk | 4.5 |
| Vulnerability | Summary | Fixed by |
|---|---|---|
|
VCID-as3y-ffvw-rube
Aliases: CVE-2018-17190 GHSA-phg2-9c5g-m4q7 |
Improper Authentication In all versions of Apache Spark, 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. | There are no reported fixed by versions. |
| Vulnerability | Summary | Aliases |
|---|---|---|
| VCID-pa42-1gk4-9yhj | Improper Authentication Apache Spark 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. |
CVE-2018-11770
GHSA-w4r4-65mg-45x2 |
| VCID-vqmm-ru8x-ukcx | 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. |
CVE-2019-10099
GHSA-fp5j-3fpf-mhj5 PYSEC-2019-114 |