CVE-2022-49715
Linux Kernel vulnerability analysis and mitigation

Overview

CVE-2022-49715 is a vulnerability in the Linux kernel's GIC-v3 (Generic Interrupt Controller version 3) implementation, specifically in the gic_populate_ppi_partitions function. The vulnerability was discovered and disclosed in February 2025, affecting various versions of the Linux kernel from version 4.7 through 5.19-rc2 (CVE Mitre).

Technical details

The vulnerability stems from a reference count leak in the gic_populate_ppi_partitions function within the irqchip/gic-v3 driver. The issue occurs because of_find_node_by_phandle() returns a node pointer with an incremented reference count, but the code failed to properly release this reference count using of_node_put() when it was no longer needed. This oversight results in a reference count leak in the kernel's memory management system (Kernel Git). The vulnerability has been assigned a CVSS v3.1 score with the following vector: AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H (NVD).

Impact

The reference count leak could potentially lead to memory resource exhaustion in the Linux kernel, affecting system availability. The impact is primarily focused on system availability rather than confidentiality or integrity, as indicated by the CVSS scoring which shows no impact on confidentiality (C:N) or integrity (I:N), but high impact on availability (A:H) (NVD).

Exploitability

The vulnerability requires local access with low privileges to exploit, as indicated by the CVSS metrics (AV:L/AC:L/PR:L/UI:N). No user interaction is required for exploitation, but the attacker must have local access to the system (NVD).

Mitigation and workarounds

The vulnerability has been fixed by adding the missing of_node_put() call in the affected code path. The fix was implemented in multiple kernel versions through backporting. The patch ensures proper reference count management by adding the necessary of_node_put() call when the CPU node is no longer needed (Kernel Git).

Additional resources


SourceThis report was generated using AI

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