CVE-2026-35337

April 13, 2026, 3:17 p.m.

8.8
High

Description

Deserialization of Untrusted Data vulnerability in Apache Storm. Versions Affected: before 2.8.6. Description: When processing topology credentials submitted via the Nimbus Thrift API, Storm deserializes the base64-encoded TGT blob using ObjectInputStream.readObject() without any class filtering or validation. An authenticated user with topology submission rights could supply a crafted serialized object in the "TGT" credential field, leading to remote code execution in both the Nimbus and Worker JVMs. Mitigation: 2.x users should upgrade to 2.8.6. Users who cannot upgrade immediately should monkey-patch an ObjectInputFilter allow-list to ClientAuthUtils.deserializeKerberosTicket() restricting deserialized classes to javax.security.auth.kerberos.KerberosTicket and its known dependencies. A guide on how to do this is available in the release notes of 2.8.6. Credit: This issue was discovered by K.

Product(s) Impacted

Vendor Product Versions
Apache
  • Storm
  • <2.8.6

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 storm <2.8.6 / / / / / / /

CVSS Score

8.8 / 10

CVSS Data - 3.1

  • Attack Vector: NETWORK
  • Attack Complexity: LOW
  • Privileges Required: LOW
  • Scope: UNCHANGED
  • Confidentiality Impact: HIGH
  • Integrity Impact: HIGH
  • Availability Impact: HIGH
  • CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H

    View Vector String

Timeline

Published: April 13, 2026, 10:16 a.m.
Last Modified: April 13, 2026, 3:17 p.m.

Status : Awaiting Analysis

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.