Security Bulletin
Summary
There is a vulnerability in Apache Spark®, Version 2.0.1 that is used by IBM Operations Analytics Predictive Insights 1.3.6.
IBM Operations Analytics Predictive Insights has addressed the applicable CVE.
Vulnerability Details
CVEID: CVE-2018-17190
DESCRIPTION: Apache Spark could allow a remote attacker to execute arbitrary code on the system, caused by the acceptance and running of code on a master host by an unsecured standalone resource manager. If authentication is disabled, an attacker could send a specially crafted request to execute arbitrary code on the system.
CVSS Base Score: 5.6
CVSS Temporal Score: See https://exchange.xforce.ibmcloud.com/vulnerabilities/153121 for the current score
CVSS Environmental Score*: Undefined
CVSS Vector: (CVSS:3.0/AV:N/AC:H/PR:N/UI:N/S:U/C:L/I:L/A:L)
Also refer to external Disclosure URL specified below
https://seclists.org/oss-sec/2018/q4/151
https://spark.apache.org/security.html
Affected Products and Versions
IBM Operations Analytics Predictive Insights v1.3.6
Remediation/Fixes
For standalone masters, as is used with Predictive Insights, disable the REST API by setting spark.authenticate to true. When you do this, you will also need to set a value for spark.authenticate.secret
That is, set the following in the file $SPARK_HOME/conf/spark-defaults.conf:-
spark.authenticate true
spark.authenticate.secret mySecret1234!
Workarounds and Mitigations
None
Get Notified about Future Security Bulletins
References
Change History
18 December 2018: Original version published
*The CVSS Environment Score is customer environment specific and will ultimately impact the Overall CVSS Score. Customers can evaluate the impact of this vulnerability in their environments by accessing the links in the Reference section of this Security Bulletin.
Disclaimer
Review the IBM security bulletin disclaimer and definitions regarding your responsibilities for assessing potential impact of security vulnerabilities to your environment.
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Document Information
Modified date:
18 December 2018
UID
ibm10791139