Vulnerability-Lookup

CNVD-2025-02606

Vulnerability from cnvd - Published: 2025-02-10

Title

NVIDIA GPU Display Driver for Windows and Linux输入验证错误漏洞（CNVD-2025-02606）

Description

NVIDIA GPU Display Driver for Windows是美国英伟达（Nvidia）公司的一个用于Windows系统中对显卡显示模块进行交互支持的驱动软件。 NVIDIA GPU Display Driver for Windows and Linux的DXGKDDISCAPE的内核模式层（nvlddmkm.sys）处理程序存在输入验证错误漏洞，该漏洞源于程序未正确验证输入是否符合安全处理数据所需的属性。攻击者可利用该漏洞导致拒绝服务。

Severity

中

Patch Name

NVIDIA GPU Display Driver for Windows and Linux输入验证错误漏洞（CNVD-2025-02606）的补丁

Patch Description

Formal description

厂商已发布了漏洞修复程序，请及时关注更新： https://nvidia.custhelp.com/app/answers/detail/a_id/5353

Reference

https://nvd.nist.gov/vuln/detail/CVE-2022-28188

Impacted products

Name
['NVIDIA vGPU Software <=13.2', 'NVIDIA vGPU Software <=11.7', 'NVIDIA vGPU Software <=14.0']

Show details on source website

JSON

To clipboard

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      "cveNumber": "CVE-2022-28188",
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  "title": "NVIDIA GPU Display Driver for Windows and Linux\u8f93\u5165\u9a8c\u8bc1\u9519\u8bef\u6f0f\u6d1e\uff08CNVD-2025-02606\uff09"
}

CVE-2022-28188 (GCVE-0-2022-28188)

Vulnerability from cvelistv5 – Published: 2022-05-17 19:15 – Updated: 2024-08-03 05:48

Summary

NVIDIA GPU Display Driver for Windows contains a vulnerability in the kernel mode layer (nvlddmkm.sys) handler for DxgkDdiEscape, where the product receives input or data, but does not validate or incorrectly validates that the input has the properties that are required to process the data safely and correctly, which may lead to denial of service.

Severity

5.5 (Medium)


                        
                          CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H

CWE

CWE-20 - Improper Input Validation

Assigner

nvidia mitre root

References

1 reference

URL	Tags
https://nvidia.custhelp.com/app/answers/detail/a_…	x_refsource_MISC

Impacted products

1 product

Vendor	Product	Version
NVIDIA	NVIDIA GPU Display Driver	Affected: All GPU Driver versions for Windows

Show details on NVD website

JSON

To clipboard

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            "confidentialityImpact": "NONE",
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Sightings

Author	Source	Type	Date	Other

Nomenclature

Seen: The vulnerability was mentioned, discussed, or observed by the user.
Confirmed: The vulnerability has been validated from an analyst's perspective.
Published Proof of Concept: A public proof of concept is available for this vulnerability.
Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
Not confirmed: The user expressed doubt about the validity of the vulnerability.
Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.

Detection rules are retrieved from Rulezet.

The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base model, served locally by ML-Gateway. They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.

Related by attack behaviour

Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.