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https://issues.apache.org/jira/browse/HADOOP-8803?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13455473#comment-13455473
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Luke Lu commented on HADOOP-8803:
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Hi Xianqing, if I understand your proposal correctly, you're essentially trying
to do two things:
# A more restrictive HDFS delegation token to reduce the damage in case a token
is compromised. As Owen said, byte range check based on split info won't work
for many mapreduce jobs, where splits are across record boundaries. The only
thing that would always work is file level check if you consider all the corner
cases. You have to design an ACL language to cover all cases, where default
works for most cases. You'll need to account for all the distributed cache
files as well.
# Unique secret keys for every datanode to generate block tokens to reduce the
damage in case a datanode is compromised. This means you need a block token for
each replica, unlike the current one block token for all replicas. This adds
some overhead to the normal operations.
A meta question though is that are you sure that all these machinery actually
increases security in real (vs theorectical) situations? Your implied
assumption is that compromise/root escalation on DN/TT is random and uniformly
distributed. My guess is that the assumption is wrong. Security breaches these
days are mostly due to zero-day bugs in system software that the likelihood of
all the TT/DN being compromised at the same time is extremely high due to the
fact they're likely have the same OS/software versions.
> Make Hadoop running more secure public cloud envrionment
> --------------------------------------------------------
>
> Key: HADOOP-8803
> URL: https://issues.apache.org/jira/browse/HADOOP-8803
> Project: Hadoop Common
> Issue Type: New Feature
> Components: fs, ipc, security
> Affects Versions: 0.20.204.0
> Reporter: Xianqing Yu
> Labels: hadoop
> Original Estimate: 2m
> Remaining Estimate: 2m
>
> I am a Ph.D student in North Carolina State University. I am modifying the
> Hadoop's code (which including most parts of Hadoop, e.g. JobTracker,
> TaskTracker, NameNode, DataNode) to achieve better security.
>
> My major goal is that make Hadoop running more secure in the Cloud
> environment, especially for public Cloud environment. In order to achieve
> that, I redesign the currently security mechanism and achieve following
> proprieties:
> 1. Bring byte-level access control to Hadoop HDFS. Based on 0.20.204, HDFS
> access control is based on user or block granularity, e.g. HDFS Delegation
> Token only check if the file can be accessed by certain user or not, Block
> Token only proof which block or blocks can be accessed. I make Hadoop can do
> byte-granularity access control, each access party, user or task process can
> only access the bytes she or he least needed.
> 2. I assume that in the public Cloud environment, only Namenode, secondary
> Namenode, JobTracker can be trusted. A large number of Datanode and
> TaskTracker may be compromised due to some of them may be running under less
> secure environment. So I re-design the secure mechanism to make the damage
> the hacker can do to be minimized.
>
> a. Re-design the Block Access Token to solve wildly shared-key problem of
> HDFS. In original Block Access Token design, all HDFS (Namenode and Datanode)
> share one master key to generate Block Access Token, if one DataNode is
> compromised by hacker, the hacker can get the key and generate any Block
> Access Token he or she want.
>
> b. Re-design the HDFS Delegation Token to do fine-grain access control for
> TaskTracker and Map-Reduce Task process on HDFS.
>
> In the Hadoop 0.20.204, all TaskTrackers can use their kerberos credentials
> to access any files for MapReduce on HDFS. So they have the same privilege as
> JobTracker to do read or write tokens, copy job file, etc.. However, if one
> of them is compromised, every critical thing in MapReduce directory (job
> file, Delegation Token) is exposed to attacker. I solve the problem by making
> JobTracker to decide which TaskTracker can access which file in MapReduce
> Directory on HDFS.
>
> For Task process, once it get HDFS Delegation Token, it can access everything
> belong to this job or user on HDFS. By my design, it can only access the
> bytes it needed from HDFS.
>
> There are some other improvement in the security, such as TaskTracker can not
> know some information like blockID from the Block Token (because it is
> encrypted by my way), and HDFS can set up secure channel to send data as a
> option.
>
> By those features, Hadoop can run much securely under uncertain environment
> such as Public Cloud. I already start to test my prototype. I want to know
> that whether community is interesting about my work? Is that a value work to
> contribute to production Hadoop?
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