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A vulnerability (CVE-2024-32498) was discovered in OpenStack's QCOW2 image processing affecting multiple components: Cinder through 24.0.0, Glance before 28.0.2, and Nova before 29.0.3. The vulnerability was reported by Martin Kaesberger and disclosed on July 2, 2024. The issue affects all Cinder and Nova deployments, while only Glance deployments with image conversion enabled are vulnerable (OpenStack OSSA, NVD).
The vulnerability allows arbitrary file access through custom QCOW2 external data. The issue stems from QCOW2's mechanisms to read from another file, specifically the external data file feature. While a previous vulnerability related to backing files was addressed in OSSA-2015-014, this separate vector remained undiscovered. The vulnerability has a CVSS v3.1 base score of 6.5 (Medium) with vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:N (NVD).
When exploited, this vulnerability allows an authenticated user to access potentially sensitive data by convincing systems to return copies of arbitrary file contents from the server. The attacker can achieve this by supplying a specially crafted QCOW2 image that references specific data file paths (OpenStack OSSA).
Patches have been released for all affected versions of Cinder, Glance, and Nova. The fixes involve implementing checks to detect and reject QCOW2 images with data-file attributes. Organizations should upgrade to Cinder version 22.1.3 or later, Glance version 28.0.2 or later, and Nova version 29.0.3 or later. Multiple patches have been provided for different versions and components to address the vulnerability comprehensively (OpenStack OSSA).
Due to the scope of the problem and complexity of the resulting fixes, there were some challenges during the coordinated disclosure period. The initial publication date had to be rescheduled, extending four days beyond the standard ninety-day maximum embargo length. This led to additional work for stakeholders as regression fixes and patches were supplied (OpenStack OSSA).
Source: This report was generated using AI
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