CVE-2022-49621
March 11, 2025, 10:18 p.m.
5.5
Medium
Description
In the Linux kernel, the following vulnerability has been resolved:
cpufreq: pmac32-cpufreq: Fix refcount leak bug
In pmac_cpufreq_init_MacRISC3(), we need to add corresponding
of_node_put() for the three node pointers whose refcount have
been incremented by of_find_node_by_name().
Product(s) Impacted
| Vendor | Product | Versions |
|---|---|---|
| Linux |
|
|
Weaknesses
Common security weaknesses mapped to this vulnerability.
*CPE(s)
Affected systems and software identified for this CVE.
| Type | Vendor | Product | Version | Update | Edition | Language | Software Edition | Target Software | Target Hardware | Other Information |
|---|---|---|---|---|---|---|---|---|---|---|
| o | linux | linux_kernel | / | / | / | / | / | / | / | / |
| o | linux | linux_kernel | / | / | / | / | / | / | / | / |
| o | linux | linux_kernel | / | / | / | / | / | / | / | / |
| o | linux | linux_kernel | / | / | / | / | / | / | / | / |
| o | linux | linux_kernel | / | / | / | / | / | / | / | / |
| o | linux | linux_kernel | / | / | / | / | / | / | / | / |
| o | linux | linux_kernel | / | / | / | / | / | / | / | / |
| o | linux | linux_kernel | 5.19 | rc1 | / | / | / | / | / | / |
| o | linux | linux_kernel | 5.19 | rc2 | / | / | / | / | / | / |
| o | linux | linux_kernel | 5.19 | rc3 | / | / | / | / | / | / |
| o | linux | linux_kernel | 5.19 | rc4 | / | / | / | / | / | / |
References
Tags
CVSS Score
CVSS Data - 3.1
- Attack Vector: LOCAL
- Attack Complexity: LOW
- Privileges Required: LOW
- Scope: UNCHANGED
- Confidentiality Impact: NONE
- Integrity Impact: NONE
- Availability Impact: HIGH
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Timeline
Published: Feb. 26, 2025, 7:01 a.m.
Last Modified: March 11, 2025, 10:18 p.m.
Last Modified: March 11, 2025, 10:18 p.m.
Status : Analyzed
CVE has been recently published to the CVE List and has been received by the NVD.
More infoSource
416baaa9-dc9f-4396-8d5f-8c081fb06d67
*Disclaimer: Some vulnerabilities do not have an associated CPE. To enhance the data, we use AI to infer CPEs based on CVE details. This is an automated process and might not always be accurate.