Raw vector
CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:H/I:H/A:HSummary
CVE-2026-32590 is a high-severity Deserialization of Untrusted Data (CWE-502) vulnerability in Redhat Mirror Registry For Red Hat Openshift. Its CVSS base score is 7.1 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 34th percentile by exploit likelihood (below the median); 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-2026-32590 is a deserialization vulnerability (CWE-502) in Red Hat Quay's handling of resumable container image layer uploads. The upload process stores intermediate data in the database using a format that, if tampered with, could allow an attacker to execute arbitrary code on the Quay server. The vulnerability has a CVSS v3.1 base score of 7.1 (AV:N/AC:H/PR:L/UI:R/S:U/C:H/I:H/A:H) and was published on 2026-04-08.
An attacker with low privileges (PR:L), such as an authenticated Quay user, could exploit this over the network (AV:N) by tampering with the intermediate upload data stored in the database. Exploitation requires high attack complexity (AC:H) and user interaction (UI:R), potentially tricking a user into initiating or resuming a malicious upload. Successful exploitation enables arbitrary code execution on the Quay server with high impacts on confidentiality, integrity, and availability (C:H/I:H/A:H), but with unchanged scope (S:U).
Mitigation details, including patches and advisories, are available in the Red Hat security bulletin at https://access.redhat.com/security/cve/CVE-2026-32590 and the associated Bugzilla entry at https://bugzilla.redhat.com/show_bug.cgi?id=2446964.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-20515
Vulnerability Data
A flaw was found in Red Hat Quay's handling of resumable container image layer uploads. The upload process stores intermediate data in the database using a format that, if tampered with, could allow an attacker to execute arbitrary code on…
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the Quay server.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
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.