Vulnerability-Lookup

CNVD-2025-19536

Vulnerability from cnvd - Published: 2025-08-21

Title

NVIDIA Megatron-LM代码注入漏洞（CNVD-2025-19536）

Description

NVIDIA Megatron-LM是美国英伟达（NVIDIA）公司的一个基于PyTorch的分布式训练框架，专门用于训练大型Transformer语言模型。 NVIDIA Megatron-LM存在代码注入漏洞，该漏洞源于megatron/training/arguments.py组件，攻击者可利用该漏洞通过注入恶意代码并执行，获取系统权限或进行远程控制。

Severity

中

Patch Name

NVIDIA Megatron-LM代码注入漏洞（CNVD-2025-19536）的补丁

Patch Description

Formal description

厂商已提供漏洞修复程序，请及时关注厂商更新： https://nvidia.custhelp.com/app/answers/detail/a_id/5685

Reference

https://nvd.nist.gov/vuln/detail/CVE-2025-23306

Impacted products

Name
NVIDIA Megatron-LM

Show details on source website

JSON

To clipboard

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      "cveNumber": "CVE-2025-23306",
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}

CVE-2025-23306 (GCVE-0-2025-23306)

Vulnerability from cvelistv5 – Published: 2025-08-13 17:35 – Updated: 2025-08-13 17:59

Summary

NVIDIA Megatron-LM for all platforms contains a vulnerability in the megatron/training/ arguments.py component where an attacker could cause a code injection issue by providing a malicious input. A successful exploit of this vulnerability may lead to code execution, escalation of privileges, information disclosure, and data tampering.

Severity

7.8 (High)


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

SSVC

Exploitation: none Automatable: no Technical Impact: total

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2025-08-13 17:58 UTC

CWE

CWE-94 - Improper Control of Generation of Code ('Code Injection')

Assigner

nvidia mitre root

References

3 references

URL	Tags
https://nvd.nist.gov/vuln/detail/CVE-2025-23306
https://www.cve.org/CVERecord?id=CVE-2025-23306
https://nvidia.custhelp.com/app/answers/detail/a_…

Impacted products

1 product

Vendor	Product	Version
NVIDIA	Megatron-LM	Affected: All versions prior to 0.12.2

Show details on NVD website

JSON

To clipboard

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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

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