CVE-2025-48943

MEDIUM
2025-05-30 [email protected]
6.5
CVSS 3.1
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CVSS Vector

CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Attack Vector
Network
Attack Complexity
Low
Privileges Required
Low
User Interaction
None
Scope
Unchanged
Confidentiality
None
Integrity
None
Availability
High

Lifecycle Timeline

3
Analysis Generated
Mar 28, 2026 - 18:44 vuln.today
Patch Released
Mar 28, 2026 - 18:44 nvd
Patch available
CVE Published
May 30, 2025 - 19:15 nvd
MEDIUM 6.5

Description

vLLM is an inference and serving engine for large language models (LLMs). Version 0.8.0 up to but excluding 0.9.0 have a Denial of Service (ReDoS) that causes the vLLM server to crash if an invalid regex was provided while using structured output. This vulnerability is similar to GHSA-6qc9-v4r8-22xg/CVE-2025-48942, but for regex instead of a JSON schema. Version 0.9.0 fixes the issue.

Analysis

vLLM is an inference and serving engine for large language models (LLMs). Rated medium severity (CVSS 6.5), this vulnerability is remotely exploitable, low attack complexity.

Technical Context

This vulnerability is classified under CWE-248. vLLM is an inference and serving engine for large language models (LLMs). Version 0.8.0 up to but excluding 0.9.0 have a Denial of Service (ReDoS) that causes the vLLM server to crash if an invalid regex was provided while using structured output. This vulnerability is similar to GHSA-6qc9-v4r8-22xg/CVE-2025-48942, but for regex instead of a JSON schema. Version 0.9.0 fixes the issue. Affected products include: Vllm. Version information: Version 0.8.0.

Affected Products

Vllm.

Remediation

A vendor patch is available. Apply the latest security update as soon as possible. Apply vendor patches when available. Implement network segmentation and monitoring as interim mitigations.

Priority Score

33
Low Medium High Critical
KEV: 0
EPSS: +0.2
CVSS: +32
POC: 0

Vendor Status

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CVE-2025-48943 vulnerability details – vuln.today

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