CVE Vulnerabilities

CVE-2023-37941

Deserialization of Untrusted Data

Published: Sep 06, 2023 | Modified: Oct 13, 2023
CVSS 3.x
6.6
MEDIUM
Source:
NVD
CVSS:3.1/AV:N/AC:H/PR:H/UI:N/S:U/C:H/I:H/A:H
CVSS 2.x
RedHat/V2
RedHat/V3
Ubuntu

If an attacker gains write access to the Apache Superset metadata database, they could persist a specifically crafted Python object that may lead to remote code execution on Supersets web backend.

The Superset metadata db is an internal component that is typically only accessible directly by the system administrator and the superset process itself. Gaining access to that database should be difficult and require significant privileges.

This vulnerability impacts Apache Superset versions 1.5.0 up to and including 2.1.0. Users are recommended to upgrade to version 2.1.1 or later.

Weakness

The product deserializes untrusted data without sufficiently verifying that the resulting data will be valid.

Affected Software

Name Vendor Start Version End Version
Superset Apache 1.5.0 (including) 2.1.0 (including)

Extended Description

It is often convenient to serialize objects for communication or to save them for later use. However, deserialized data or code can often be modified without using the provided accessor functions if it does not use cryptography to protect itself. Furthermore, any cryptography would still be client-side security – which is a dangerous security assumption. Data that is untrusted can not be trusted to be well-formed. When developers place no restrictions on “gadget chains,” or series of instances and method invocations that can self-execute during the deserialization process (i.e., before the object is returned to the caller), it is sometimes possible for attackers to leverage them to perform unauthorized actions, like generating a shell.

Potential Mitigations

  • Make fields transient to protect them from deserialization.
  • An attempt to serialize and then deserialize a class containing transient fields will result in NULLs where the transient data should be. This is an excellent way to prevent time, environment-based, or sensitive variables from being carried over and used improperly.

References