Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:HSummary
CVE-2026-35337 is a high-severity Deserialization of Untrusted Data (CWE-502) vulnerability in Apache Storm. Its CVSS base score is 8.8 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked in the top 40% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
The strongest mitigations our analysis identified map to SA-11 (Developer Testing and Evaluation) and SI-10 (Information Input Validation) — see the control section below for these in your framework.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
CVE-2026-35337 is a Deserialization of Untrusted Data vulnerability (CWE-502) in Apache Storm, affecting versions prior to 2.8.6. The issue arises when Storm processes topology credentials submitted via the Nimbus Thrift API, deserializing a base64-encoded TGT blob using ObjectInputStream.readObject() without any class filtering or validation. This flaw has a CVSS v3.1 base score of 8.8 (AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H).
An authenticated user with topology submission rights can exploit this vulnerability by supplying a crafted serialized object in the "TGT" credential field. Successful exploitation leads to remote code execution in both the Nimbus and Worker JVMs.
Apache Storm advisories recommend that 2.x users upgrade to version 2.8.6 for a complete fix. As an interim measure, users unable to upgrade immediately can apply a monkey-patch to ClientAuthUtils.deserializeKerberosTicket() using an ObjectInputFilter allow-list that restricts deserialized classes to javax.security.auth.kerberos.KerberosTicket and its known dependencies; a guide is available in the 2.8.6 release notes. Additional details are provided in the Storm release announcement at https://storm.apache.org/2026/04/12/storm286-released.html and the oss-security mailing list at http://www.openwall.com/lists/oss-security/2026/04/12/6.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-21902
Vulnerability Data
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…
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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.
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Related Threats
MITRE ATT&CK Enterprise Techniques
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Affected Assets
Mitigating Controls
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation can uncover deserialization flaws before deployment.
Input validation directly stops deserialization of untrusted data by ensuring inputs are valid before processing.
Engineering principles such as safe deserialization and input sanitization structurally prevent the weakness from being introduced.
Integrity verification tools can detect malformed or tampered serialized data after the fact.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
PR.PS-02 addresses only post-deployment updates/patching and cannot prevent introduction of unsafe deserialization code, yet it can remediate some instances when the flaw exists in outdated libraries or components.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
Security testing includes validation of deserialization routines and the use of untrusted data, reducing the likelihood that unsafe object reconstruction will be deployed.
Requiring vetted libraries, regular updates and SAST before release reduces the likelihood that deserialization logic will accept and act on attacker-controlled serialized objects.
Regular scanning of third-party libraries and timely patching reduce the likelihood that unsafe deserialization vulnerabilities remain active.
Mandatory malware scanning of data received over networks or storage media intercepts malicious serialized payloads before they are deserialized by the target application.