CVE-2026-33248

March 26, 2026, 4:22 p.m.

4.2
Medium

Description

NATS-Server is a High-Performance server for NATS.io, a cloud and edge native messaging system. Prior to versions 2.11.15 and 2.12.6, when using mTLS for client identity, with `verify_and_map` to derive a NATS identity from the client certificate's Subject DN, certain patterns of RDN would not be correctly enforced, allowing for authentication bypass. This does require a valid certificate from a CA already trusted for client certificates, and `DN` naming patterns which the NATS maintainers consider highly unlikely. So this is an unlikely attack. Nonetheless, administrators who have been very sophisticated in their `DN` construction patterns might conceivably be impacted. Versions 2.11.15 and 2.12.6 contain a fix. As a workaround, developers should review their CA issuing practices.

Product(s) Impacted

Vendor Product Versions
Linuxfoundation
  • Nats-server
  • *

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-287
Improper Authentication
When an actor claims to have a given identity, the product does not prove or insufficiently proves that the claim is correct.

*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 linuxfoundation nats-server / / / / / / / /
a linuxfoundation nats-server / / / / / / / /

CVSS Score

4.2 / 10

CVSS Data - 3.1

  • Attack Vector: NETWORK
  • Attack Complexity: HIGH
  • Privileges Required: LOW
  • Scope: UNCHANGED
  • Confidentiality Impact: LOW
  • Integrity Impact: LOW
  • Availability Impact: NONE
  • CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:U/C:L/I:L/A:N

    View Vector String

Timeline

Published: March 25, 2026, 9:16 p.m.
Last Modified: March 26, 2026, 4:22 p.m.

Status : Analyzed

CVE has been recently published to the CVE List and has been received by the NVD.

More info

*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.