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Apache Airflow vulnerable arbitrary code execution via Spark server

High severity GitHub Reviewed Published Aug 28, 2023 to the GitHub Advisory Database • Updated Nov 5, 2023

Package

pip apache-airflow-providers-apache-spark (pip)

Affected versions

< 4.1.3

Patched versions

None

Description

Deserialization of Untrusted Data, Inclusion of Functionality from Untrusted Control Sphere vulnerability in Apache Software Foundation Apache Airflow Spark Provider.

When the Apache Spark provider is installed on an Airflow deployment, an Airflow user that is authorized to configure Spark hooks can effectively run arbitrary code on the Airflow node by pointing it at a malicious Spark server. Prior to version 4.1.3, this was not called out in the documentation explicitly, so it is possible that administrators provided authorizations to configure Spark hooks without taking this into account. We recommend administrators to review their configurations to make sure the authorization to configure Spark hooks is only provided to fully trusted users.

To view the warning in the docs please visit  https://airflow.apache.org/docs/apache-airflow-providers-apache-spark/4.1.3/connections/spark.html

References

Published by the National Vulnerability Database Aug 28, 2023
Published to the GitHub Advisory Database Aug 28, 2023
Reviewed Aug 30, 2023
Last updated Nov 5, 2023

Severity

High
8.8
/ 10

CVSS base metrics

Attack vector
Network
Attack complexity
Low
Privileges required
Low
User interaction
None
Scope
Unchanged
Confidentiality
High
Integrity
High
Availability
High
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H

Weaknesses

CVE ID

CVE-2023-40195

GHSA ID

GHSA-8q28-pw9g-w82c

Source code

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