Vulnerability-Lookup

CNVD-2025-11394

Vulnerability from cnvd - Published: 2025-06-05

Title

NVIDIA TensorRT-LLM python执行器代码问题漏洞

Description

NVIDIA TensorRT-LLM是NVIDIA推出的一个高性能推理加速库，用于定义、优化和执行大型语言模型 (LLM) 在生产环境的推理。 NVIDIA TensorRT-LLM存在代码问题漏洞，该漏洞源于数据验证不足，攻击者可利用该漏洞提交特殊的请求，执行任意代码。

Severity

中

Patch Name

NVIDIA TensorRT-LLM python执行器代码问题漏洞的补丁

Patch Description

NVIDIA TensorRT-LLM是NVIDIA推出的一个高性能推理加速库，用于定义、优化和执行大型语言模型 (LLM) 在生产环境的推理。 NVIDIA TensorRT-LLM存在代码问题漏洞，该漏洞源于数据验证不足，攻击者可利用该漏洞提交特殊的请求，执行任意代码。目前，供应商发布了安全公告及相关补丁信息，修复了此漏洞。

Formal description

目前厂商已发布升级程序修复该安全问题，详情见厂商官网： https://nvidia.custhelp.com/app/answers/detail/a_id/5648

Reference

https://nvidia.custhelp.com/app/answers/detail/a_id/5648

Impacted products

Name
NVIDIA TensorRT-LLM

Show details on source website

JSON

To clipboard

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    "cve": {
      "cveNumber": "CVE-2025-23254",
      "cveUrl": "https://nvd.nist.gov/vuln/detail/CVE-2025-23254"
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  "number": "CNVD-2025-11394",
  "openTime": "2025-06-05",
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  "products": {
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  "serverity": "\u4e2d",
  "submitTime": "2025-05-07",
  "title": "NVIDIA TensorRT-LLM python\u6267\u884c\u5668\u4ee3\u7801\u95ee\u9898\u6f0f\u6d1e"
}

CVE-2025-23254 (GCVE-0-2025-23254)

Vulnerability from cvelistv5 – Published: 2025-05-01 14:05 – Updated: 2025-05-01 14:51

Summary

NVIDIA TensorRT-LLM for any platform contains a vulnerability in python executor where an attacker may cause a data validation issue by local access to the TRTLLM server. A successful exploit of this vulnerability may lead to code execution, information disclosure and data tampering.

Severity

8.8 (High)


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

SSVC

Exploitation: none Automatable: no Technical Impact: total

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2025-05-01 14:51 UTC

CWE

CWE-502 - Deserialization of Untrusted Data

Assigner

nvidia mitre root

References

1 reference

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

Impacted products

1 product

Vendor	Product	Version
NVIDIA	TensorRT-LLM	Affected: All versions prior to 0.18.2

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

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.