CVE-2025-29953
April 18, 2025, 6:15 p.m.
None
No Score
Description
Deserialization of Untrusted Data vulnerability in Apache ActiveMQ NMS OpenWire Client.
This issue affects Apache ActiveMQ NMS OpenWire Client before 2.1.1 when performing connections to untrusted servers. Such servers could abuse the unbounded deserialization in the client to provide malicious responses that may eventually cause arbitrary code execution on the client. Version 2.1.0 introduced a allow/denylist feature to restrict deserialization, but this feature could be bypassed.
The .NET team has deprecated the built-in .NET binary serialization feature starting with .NET 9 and suggests migrating away from binary serialization. The project is considering to follow suit and drop this part of the NMS API altogether.
Users are recommended to upgrade to version 2.1.1, which fixes the issue. We also recommend to migrate away from relying on .NET binary serialization as a hardening method for the future.
Product(s) Impacted
| Vendor | Product | Versions |
|---|---|---|
| Apache |
|
|
Weaknesses
Common security weaknesses mapped to this vulnerability.
CWE-502
Deserialization of Untrusted Data
The product deserializes untrusted data without sufficiently verifying that the resulting data will be valid.
*CPE(s)
Affected systems and software identified for this CVE.
| Type | Vendor | Product | Version | Update | Edition | Language | Software Edition | Target Software | Target Hardware | Other Information |
|---|---|---|---|---|---|---|---|---|---|---|
| a | apache | activemq_nms_openwire_client | <2.1.1 | / | / | / | / | / | / | / |
| a | apache | activemq_nms_openwire_client | 2.1.1 | / | / | / | / | / | / | / |
Tags
Timeline
Published: April 18, 2025, 4:15 p.m.
Last Modified: April 18, 2025, 6:15 p.m.
Last Modified: April 18, 2025, 6:15 p.m.
Status : Received
CVE has been recently published to the CVE List and has been received by the NVD.
More infoSource
security@apache.org
*Disclaimer: Some vulnerabilities do not have an associated CPE. To enhance the data, we use AI to infer CPEs based on CVE details. This is an automated process and might not always be accurate.