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From pwendell <...@git.apache.org>
Subject [GitHub] spark pull request: Add Security to Spark - Akka, Http, Connection...
Date Mon, 03 Mar 2014 17:42:16 GMT
Github user pwendell commented on a diff in the pull request:

    https://github.com/apache/spark/pull/33#discussion_r10219868
  
    --- Diff: core/src/main/scala/org/apache/spark/SecurityManager.scala ---
    @@ -0,0 +1,259 @@
    +/*
    + * Licensed to the Apache Software Foundation (ASF) under one or more
    + * contributor license agreements.  See the NOTICE file distributed with
    + * this work for additional information regarding copyright ownership.
    + * The ASF licenses this file to You under the Apache License, Version 2.0
    + * (the "License"); you may not use this file except in compliance with
    + * the License.  You may obtain a copy of the License at
    + *
    + *    http://www.apache.org/licenses/LICENSE-2.0
    + *
    + * Unless required by applicable law or agreed to in writing, software
    + * distributed under the License is distributed on an "AS IS" BASIS,
    + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
    + * See the License for the specific language governing permissions and
    + * limitations under the License.
    + */
    +
    +package org.apache.spark
    +
    +import java.net.{Authenticator, PasswordAuthentication}
    +import org.apache.hadoop.io.Text
    +import org.apache.hadoop.security.Credentials
    +import org.apache.hadoop.security.UserGroupInformation
    +import org.apache.spark.deploy.SparkHadoopUtil
    +
    +import scala.collection.mutable.ArrayBuffer
    +
    +/** 
    + * Spark class responsible for security. 
    + * 
    + * In general this class should be instantiated by the SparkEnv and most components
    + * should access it from that. There are some cases where the SparkEnv hasn't been 
    + * initialized yet and this class must be instantiated directly.
    + * 
    + * Spark currently supports authentication via a shared secret.
    + * Authentication can be configured to be on via the 'spark.authenticate' configuration
    + * parameter. This parameter controls whether the Spark communication protocols do 
    + * authentication using the shared secret. This authentication is a basic handshake to
    + * make sure both sides have the same shared secret and are allowed to communicate.
    + * If the shared secret is not identical they will not be allowed to communicate. 
    + * 
    + * The Spark UI can also be secured by using javax servlet filters. A user may want to

    + * secure the UI if it has data that other users should not be allowed to see. The javax

    + * servlet filter specified by the user can authenticate the user and then once the user

    + * is logged in, Spark can compare that user versus the view acls to make sure they are

    + * authorized to view the UI. The configs 'spark.ui.acls.enable' and 'spark.ui.view.acls'

    + * control the behavior of the acls. Note that the person who started the application
    + * always has view access to the UI.
    + *
    + * Spark does not currently support encryption after authentication.
    + * 
    + * At this point spark has multiple communication protocols that need to be secured and
    + * different underlying mechisms are used depending on the protocol:
    + *
    + *  - Akka -> The only option here is to use the Akka Remote secure-cookie functionality.

    + *            Akka remoting allows you to specify a secure cookie that will be exchanged

    + *            and ensured to be identical in the connection handshake between the client

    + *            and the server. If they are not identical then the client will be refused

    + *            to connect to the server. There is no control of the underlying 
    + *            authentication mechanism so its not clear if the password is passed in

    + *            plaintext or uses DIGEST-MD5 or some other mechanism.
    + *            Akka also has an option to turn on SSL, this option is not currently supported
    + *            but we could add a configuration option in the future.
    + * 
    + *  - HTTP for broadcast and file server (via HttpServer) ->  Spark currently uses
Jetty 
    + *            for the HttpServer. Jetty supports multiple authentication mechanisms -

    + *            Basic, Digest, Form, Spengo, etc. It also supports multiple different login

    + *            services - Hash, JAAS, Spnego, JDBC, etc.  Spark currently uses the HashLoginService
    + *            to authenticate using DIGEST-MD5 via a single user and the shared secret.

    + *            Since we are using DIGEST-MD5, the shared secret is not passed on the wire
    + *            in plaintext.
    + *            We currently do not support SSL (https), but Jetty can be configured to
use it
    + *            so we could add a configuration option for this in the future.
    + *            
    + *            The Spark HttpServer installs the HashLoginServer and configures it to
DIGEST-MD5.
    + *            Any clients must specify the user and password. There is a default 
    + *            Authenticator installed in the SecurityManager to how it does the authentication
    + *            and in this case gets the user name and password from the request.
    + *
    + *  - ConnectionManager -> The Spark ConnectionManager uses java nio to asynchronously

    + *            exchange messages.  For this we use the Java SASL 
    + *            (Simple Authentication and Security Layer) API and again use DIGEST-MD5

    + *            as the authentication mechanism. This means the shared secret is not passed
    + *            over the wire in plaintext.
    + *            Note that SASL is pluggable as to what mechanism it uses.  We currently
use
    + *            DIGEST-MD5 but this could be changed to use Kerberos or other in the future.
    + *            Spark currently supports "auth" for the quality of protection, which means
    + *            the connection is not supporting integrity or privacy protection (encryption)
    + *            after authentication. SASL also supports "auth-int" and "auth-conf" which

    + *            SPARK could be support in the future to allow the user to specify the quality
    + *            of protection they want. If we support those, the messages will also have
to 
    + *            be wrapped and unwrapped via the SaslServer/SaslClient.wrap/unwrap API's.
    + * 
    + *            Since the connectionManager does asynchronous messages passing, the SASL

    + *            authentication is a bit more complex. A ConnectionManager can be both a
client
    + *            and a Server, so for a particular connection is has to determine what to
do.
    + *            A ConnectionId was added to be able to track connections and is used to

    + *            match up incoming messages with connections waiting for authentication.
    + *            If its acting as a client and trying to send a message to another ConnectionManager,
    + *            it blocks the thread calling sendMessage until the SASL negotiation has
occurred.
    + *            The ConnectionManager tracks all the sendingConnections using the ConnectionId
    + *            and waits for the response from the server and does the handshake.
    + *
    + *  - HTTP for the Spark UI -> the UI was changed to use servlets so that javax servlet
filters 
    + *            can be used. Yarn requires a specific AmIpFilter be installed for security
to work
    + *            properly. For non-Yarn deployments, users can write a filter to go through
a
    + *            companies normal login service. If an authentication filter is in place
then the
    + *            SparkUI can be configured to check the logged in user against the list
of users who
    + *            have view acls to see if that user is authorized.
    + *            The filters can also be used for many different purposes. For instance
filters 
    + *            could be used for logging, encypryption, or compression.
    + *            
    + *  The exact mechanisms used to generate/distributed the shared secret is deployment
specific.
    + * 
    + *  For Yarn deployments, the secret is automatically generated using the Akka remote
    + *  Crypt.generateSecureCookie() API. The secret is placed in the Hadoop UGI which gets
passed
    + *  around via the Hadoop RPC mechanism. Hadoop RPC can be configured to support different
levels
    + *  of protection. See the Hadoop documentation for more details. Each Spark application
on Yarn
    + *  gets a different shared secret. On Yarn, the Spark UI gets configured to use the
Hadoop Yarn
    + *  AmIpFilter which requires the user to go through the ResourceManager Proxy. That
Proxy is there
    + *  to reduce the possibility of web based attacks through YARN. Hadoop can be configured
to use
    + *  filters to do authentication. That authentication then happens via the ResourceManager
Proxy
    + *  and Spark will use that to do authorization against the view acls.
    + * 
    + *  For other Spark deployments, the shared secret should be specified via the SPARK_SECRET

    + *  environment variable. This isn't ideal but it means only the user who starts the
process 
    + *  has access to view that variable. Note that Spark does try to generate a secret for
    + *  you if the SPARK_SECRET environment variable is not set, but it gets put into the
java
    + *  system property which can be viewed by other users, so setting the SPARK_SECRET environment
    + *  variable is recommended.
    + *  All the nodes (Master and Workers) need to have the same shared secret
    --- End diff --
    
    That's what I figured. Thanks. 


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