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Posted to issues@spark.apache.org by "Imran Rashid (JIRA)" <ji...@apache.org> on 2019/08/05 15:04:00 UTC

[jira] [Updated] (SPARK-28626) Spark leaves unencrypted data on local disk, even with encryption turned on (CVE-2019-10099)

     [ https://issues.apache.org/jira/browse/SPARK-28626?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Imran Rashid updated SPARK-28626:
---------------------------------
    Description: 
Severity: Important

 

Vendor: The Apache Software Foundation

 

Versions affected:

All Spark 1.x, Spark 2.0.x, Spark 2.1.x, and 2.2.x versions

Spark 2.3.0 to 2.3.2

 

Description:

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.

 

 

Mitigation:

1.x, 2.0.x, 2.1.x, 2.2.x, 2.3.x  users should upgrade to 2.3.3 or newer

 

Credit:

This issue was reported by Thomas Graves of NVIDIA.

 

References:

[https://spark.apache.org/security.html]

 

The following commits were used to fix this issue, in branch-2.3 (there may be other commits in master / branch-2.4, that are equivalent.)
{noformat}
commit 575fea120e25249716e3f680396580c5f9e26b5b
Author: Imran Rashid <ir...@cloudera.com>
Date:   Wed Aug 22 16:38:28 2018 -0500

    [CORE] Updates to remote cache reads

    Covered by tests in DistributedSuite

 
commit 6d742d1bd71aa3803dce91a830b37284cb18cf70
Author: Imran Rashid <ir...@cloudera.com>
Date:   Thu Sep 6 12:11:47 2018 -0500

    [PYSPARK][SQL] Updates to RowQueue

    Tested with updates to RowQueueSuite

 
commit 09dd34cb1706f2477a89174d6a1a0f17ed5b0a65
Author: Imran Rashid <ir...@cloudera.com>
Date:   Mon Aug 13 21:35:34 2018 -0500 

    [PYSPARK] Updates to pyspark broadcast

 
commit 12717ba0edfa5459c9ac2085f46b1ecc0ee759aa
Author: hyukjinkwon <gu...@apache.org>
Date:   Mon Sep 24 19:25:02 2018 +0800 

    [SPARKR] Match pyspark features in SparkR communication protocol
{noformat}

  was:
Severity: Important

 

Vendor: The Apache Software Foundation

 

Versions affected:

All Spark 1.x, Spark 2.0.x, Spark 2.1.x, and 2.2.x versions

Spark 2.3.0 to 2.3.2

 

Description:

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.

 

 

Mitigation:

1.x, 2.0.x, 2.1.x, 2.2.x, 2.3.x  users should upgrade to 2.3.3 or newer

2.3.x users should upgrade to 2.3.3 or newer.

 

Credit:

This issue was reported by Thomas Graves of NVIDIA.

 

References:

[https://spark.apache.org/security.html]

 

The following commits were used to fix this issue, in branch-2.3 (there may be other commits in master / branch-2.4, that are equivalent.)

{noformat}
commit 575fea120e25249716e3f680396580c5f9e26b5b
Author: Imran Rashid <ir...@cloudera.com>
Date:   Wed Aug 22 16:38:28 2018 -0500

    [CORE] Updates to remote cache reads

    Covered by tests in DistributedSuite

 
commit 6d742d1bd71aa3803dce91a830b37284cb18cf70
Author: Imran Rashid <ir...@cloudera.com>
Date:   Thu Sep 6 12:11:47 2018 -0500

    [PYSPARK][SQL] Updates to RowQueue

    Tested with updates to RowQueueSuite

 
commit 09dd34cb1706f2477a89174d6a1a0f17ed5b0a65
Author: Imran Rashid <ir...@cloudera.com>
Date:   Mon Aug 13 21:35:34 2018 -0500 

    [PYSPARK] Updates to pyspark broadcast

 
commit 12717ba0edfa5459c9ac2085f46b1ecc0ee759aa
Author: hyukjinkwon <gu...@apache.org>
Date:   Mon Sep 24 19:25:02 2018 +0800 

    [SPARKR] Match pyspark features in SparkR communication protocol
{noformat}


> Spark leaves unencrypted data on local disk, even with encryption turned on (CVE-2019-10099)
> --------------------------------------------------------------------------------------------
>
>                 Key: SPARK-28626
>                 URL: https://issues.apache.org/jira/browse/SPARK-28626
>             Project: Spark
>          Issue Type: Bug
>          Components: Security
>    Affects Versions: 2.3.2
>            Reporter: Imran Rashid
>            Priority: Major
>             Fix For: 2.3.3, 2.4.0
>
>
> Severity: Important
>  
> Vendor: The Apache Software Foundation
>  
> Versions affected:
> All Spark 1.x, Spark 2.0.x, Spark 2.1.x, and 2.2.x versions
> Spark 2.3.0 to 2.3.2
>  
> Description:
> 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.
>  
>  
> Mitigation:
> 1.x, 2.0.x, 2.1.x, 2.2.x, 2.3.x  users should upgrade to 2.3.3 or newer
>  
> Credit:
> This issue was reported by Thomas Graves of NVIDIA.
>  
> References:
> [https://spark.apache.org/security.html]
>  
> The following commits were used to fix this issue, in branch-2.3 (there may be other commits in master / branch-2.4, that are equivalent.)
> {noformat}
> commit 575fea120e25249716e3f680396580c5f9e26b5b
> Author: Imran Rashid <ir...@cloudera.com>
> Date:   Wed Aug 22 16:38:28 2018 -0500
>     [CORE] Updates to remote cache reads
>     Covered by tests in DistributedSuite
>  
> commit 6d742d1bd71aa3803dce91a830b37284cb18cf70
> Author: Imran Rashid <ir...@cloudera.com>
> Date:   Thu Sep 6 12:11:47 2018 -0500
>     [PYSPARK][SQL] Updates to RowQueue
>     Tested with updates to RowQueueSuite
>  
> commit 09dd34cb1706f2477a89174d6a1a0f17ed5b0a65
> Author: Imran Rashid <ir...@cloudera.com>
> Date:   Mon Aug 13 21:35:34 2018 -0500 
>     [PYSPARK] Updates to pyspark broadcast
>  
> commit 12717ba0edfa5459c9ac2085f46b1ecc0ee759aa
> Author: hyukjinkwon <gu...@apache.org>
> Date:   Mon Sep 24 19:25:02 2018 +0800 
>     [SPARKR] Match pyspark features in SparkR communication protocol
> {noformat}



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