CVE-2024-39469
Linux Kernel vulnerability analysis and mitigation

Overview

CVE-2024-39469 addresses a vulnerability in the Linux kernel's NILFS2 filesystem implementation. The issue was discovered in the nilfs_empty_dir() function, which contained incorrect error handling when a directory folio/page read fails. The vulnerability was disclosed on June 25, 2024, affecting the Linux kernel's NILFS2 filesystem component (NVD).

Technical details

The vulnerability stems from incorrect error handling in the nilfs_empty_dir() function. When a directory folio/page read fails or nilfs_check_folio() fails, the function would falsely determine the directory as empty, potentially corrupting the file system. Additionally, since nilfs_empty_dir() did not immediately return on a failed folio/page read but continued to loop, this could cause a long loop with I/O if i_size of the directory's inode was corrupted, causing the log writer thread to wait and hang (Kernel Commit).

Impact

The vulnerability could lead to filesystem corruption and system hangs. If exploited, it could cause the log writer thread to wait indefinitely, resulting in a denial of service condition. The issue could also lead to false determinations of directory status, potentially corrupting the filesystem (Kernel Commit).

Exploitability

The vulnerability was discovered through automated testing by syzbot, suggesting it could be triggered through local access to a system using the NILFS2 filesystem. The issue has been confirmed to be exploitable, as demonstrated by syzbot's testing (Kernel Commit).

Mitigation and workarounds

The issue has been fixed by modifying nilfs_empty_dir() to immediately return a false value (0) if it fails to get a directory folio/page. This fix has been implemented in various kernel versions and is available through distribution updates. The fix was authored by Ryusuke Konishi and has been incorporated into multiple stable kernel branches (Oracle Linux, Ubuntu Security Notice).

Additional resources


SourceThis report was generated using AI

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