
Cloud Vulnerability DB
A community-led vulnerabilities database
CVE-2025-22121 is a vulnerability discovered in the Linux kernel, specifically affecting the ext4 filesystem component. The issue was disclosed on April 16, 2025, and involves an out-of-bound read vulnerability in the ext4_xattr_inode_dec_ref_all() function. This vulnerability affects various Linux distributions including Debian and Red Hat Enterprise Linux systems (NVD, Debian Tracker).
The vulnerability manifests as a use-after-free bug in the ext4_xattr_inode_dec_ref_all() function. The issue occurs because ext4_xattr_delete_inode() fails to verify if the xattr is valid when it exists in an inode. The vulnerability has been assigned a CVSS v3.1 Base Score of 5.5 with the vector string CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H, indicating a local attack vector with low attack complexity (Red Hat).
The vulnerability can lead to system instability and potential denial of service through an out-of-bound read operation. The CVSS scoring indicates that while there is no impact on confidentiality or integrity, there is a high impact on availability of the affected system (Red Hat).
The vulnerability requires local access to the system and low privileges to exploit. The attack complexity is rated as low, indicating that the vulnerability is relatively straightforward to exploit under the right conditions (Red Hat).
The solution involves implementing a call to xattr_check_inode() to verify if the xattr is valid in the inode. Additionally, verification can be performed directly in ext4_iget_extra_inode() to prevent divergent verification. Various Linux distributions have either released or are preparing patches to address this vulnerability (Debian Tracker).
Fix availability across major Linux distributions and their releases.
bionic (esm-infra)
linux
bionic (fips-updates)
linux-fips
bionic (fips)
linux-fips
devel
linux
focal
linux-azure-fde-5.15
focal (esm-infra)
linux
focal (fips-updates)
linux-fips
focal (fips)
linux-fips
Source: This report was generated using AI
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