CVE-2025-54325
Nov. 4, 2025, 9:15 p.m.
5.3
Medium
Description
An issue was discovered in VTS in Samsung Mobile Processor and Wearable Processor Exynos 1080, 1280, 2200, 1380, 1480, 2400, 1580, 2500, W920, W930, W1000. A race condition in the VTS driver results in an out-of-bounds read, leading to an information leak.
Product(s) Impacted
| Vendor | Product | Versions |
|---|---|---|
| Samsung |
|
|
Weaknesses
Common security weaknesses mapped to this vulnerability.
CWE-125
Out-of-bounds Read
The product reads data past the end, or before the beginning, of the intended buffer.
*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 |
|---|---|---|---|---|---|---|---|---|---|---|
| a | samsung | exynos_1080 | / | / | / | / | / | / | / | / |
| a | samsung | exynos_1280 | / | / | / | / | / | / | / | / |
| a | samsung | exynos_2200 | / | / | / | / | / | / | / | / |
| a | samsung | exynos_1380 | / | / | / | / | / | / | / | / |
| a | samsung | exynos_1480 | / | / | / | / | / | / | / | / |
| a | samsung | exynos_2400 | / | / | / | / | / | / | / | / |
| a | samsung | exynos_1580 | / | / | / | / | / | / | / | / |
| a | samsung | exynos_2500 | / | / | / | / | / | / | / | / |
| a | samsung | w920 | / | / | / | / | / | / | / | / |
| a | samsung | w930 | / | / | / | / | / | / | / | / |
| a | samsung | w1000 | / | / | / | / | / | / | / | / |
Tags
CVSS Score
CVSS Data - 3.1
- Attack Vector: NETWORK
- Attack Complexity: LOW
- Privileges Required: NONE
- Scope: UNCHANGED
- Confidentiality Impact: NONE
- Integrity Impact: NONE
- Availability Impact: LOW
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L
Timeline
Published: Nov. 4, 2025, 6:16 p.m.
Last Modified: Nov. 4, 2025, 9:15 p.m.
Last Modified: Nov. 4, 2025, 9:15 p.m.
Status : Received
CVE has been recently published to the CVE List and has been received by the NVD.
More infoSource
cve@mitre.org
*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.