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https://issues.apache.org/jira/browse/HADOOP-12345?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Vinod Kumar Vavilapalli updated HADOOP-12345:
---------------------------------------------
    Target Version/s: 2.8.0  (was: 2.6.0, 2.7.0, 2.7.1)

Also 2.6.0/2.7.0/2.7.1 are released, targeting for 2.8.0.

> Credential length in CredentialsSys.java incorrect
> --------------------------------------------------
>
>                 Key: HADOOP-12345
>                 URL: https://issues.apache.org/jira/browse/HADOOP-12345
>             Project: Hadoop Common
>          Issue Type: Bug
>          Components: nfs
>    Affects Versions: 2.7.0
>            Reporter: Pradeep Nayak Udupi Kadbet
>            Priority: Blocker
>
> Hi -
> There is a bug in the way hadoop-nfs sets the credential length in 
> "Credentials" field of the NFS RPC packet when using AUTH_SYS
> In CredentialsSys.java, when we are writing the creds in to XDR object, we 
> set the length as follows:
>  // mStamp + mHostName.length + mHostName + mUID + mGID + mAuxGIDs.count
> 96     mCredentialsLength = 20 + mHostName.getBytes().length;
> (20 corresponds to 4 bytes for mStamp, 4 bytes for mUID, 4 bytes for mGID, 4 
> bytes for length field of hostname, 4 bytes for number of aux 4 gids) and 
> this is okay.
> However when we add the length of the hostname to this, we are not adding the 
> extra padded bytes for the hostname (If the length is not a multiple of 4) 
> and thus when the NFS server reads the packet, it returns GARBAGE_ARGS 
> because it doesn't read the uid field when it is expected to read. I can 
> reproduce this issue constantly on machines where the hostname length is not 
> a multiple of 4.
> A possible fix is to do something this:
> int pad = mHostName.getBytes().length % 4;
>  // mStamp + mHostName.length + mHostName + mUID + mGID + mAuxGIDs.count
> mCredentialsLength = 20 + mHostName.getBytes().length + pad;
> I would be happy to submit the patch but I need some help to commit into 
> mainline. I haven't committed into Hadoop yet.
> Cheers!
> Pradeep



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