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https://issues.apache.org/jira/browse/SPARK-27742?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16851924#comment-16851924
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Stavros Kontopoulos edited comment on SPARK-27742 at 5/30/19 2:53 PM:
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{quote}From client side the max lifetime can be only decreased for security
reasons + see my previous point.
{quote}
In general since Kafka allows me to set this value, I should be able to do so.
"Max lifetime for the token in milliseconds. If the value is -1, then
MaxLifeTime will default to a server side config value
(delegation.token.max.lifetime.ms)."
For the user this means better flexibility per job to setup an upper limit.
Again I see the point repeatedly get new tokens, no max life time. From a
security perspective this allows the user renew a ticket for ever, if not
mistaken, which is less restrictive than setting a hard limit. Imagine you have
multiple Spark apps and you want to setup limits. Anyway my 2 cents.
{quote}There is no possibility to obtain token for anybody else (pls see the
comment in the code).
{quote}
When proxy user will be supported I guess there will be.
was (Author: skonto):
{quote}From client side the max lifetime can be only decreased for security
reasons + see my previous point.
{quote}
In general since Kafka allows me to set this value, I should be able to do so.
"Max lifetime for the token in milliseconds. If the value is -1, then
MaxLifeTime will default to a server side config value
(delegation.token.max.lifetime.ms)."
For the user this means better flexibility per job to setup an upper limit.
Again I see the point repeatedly get new tokens, no max life time. From a
security perspective this allows the user renew a ticket for ever, if not
mistaken, which is less restrictive than the setting a hard limit. Imagine I
have multiple Spark apps and I want to setup limits. Anyway some thoughts.
{quote}There is no possibility to obtain token for anybody else (pls see the
comment in the code).
{quote}
When proxy user will be supported I guess there will be.
> Security Support in Sources and Sinks for SS and Batch
> ------------------------------------------------------
>
> Key: SPARK-27742
> URL: https://issues.apache.org/jira/browse/SPARK-27742
> Project: Spark
> Issue Type: Brainstorming
> Components: SQL, Structured Streaming
> Affects Versions: 3.0.0
> Reporter: Stavros Kontopoulos
> Priority: Major
>
> As discussed with [~erikerlandson] on the [Big Data on K8s
> UG|https://docs.google.com/document/d/1pnF38NF6N5eM8DlK088XUW85Vms4V2uTsGZvSp8MNIA]
> it would be good to capture current status and identify work that needs to
> be done for securing Spark when accessing sources and sinks. For example what
> is the status of SSL, Kerberos support in different scenarios. The big
> concern nowadays is how to secure data pipelines end-to-end.
> Note: Not sure if this overlaps with some other ticket.
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