CVE Vulnerabilities

CVE-2022-24289

Deserialization of Untrusted Data

Published: Feb 11, 2022 | Modified: Feb 18, 2022
CVSS 3.x
8.8
HIGH
Source:
NVD
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
CVSS 2.x
6.5 MEDIUM
AV:N/AC:L/Au:S/C:P/I:P/A:P
RedHat/V2
RedHat/V3
Ubuntu

Hessian serialization is a network protocol that supports object-based transmission. Apache Cayennes optional Remote Object Persistence (ROP) feature is a web services-based technology that provides object persistence and query functionality to remote applications. In Apache Cayenne 4.1 and earlier, running on non-current patch versions of Java, an attacker with client access to Cayenne ROP can transmit a malicious payload to any vulnerable third-party dependency on the server. This can result in arbitrary code execution.

Weakness

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

Affected Software

Name Vendor Start Version End Version
Cayenne Apache * *

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