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Vllm CVE-2025-48887

MEDIUM
Inefficient Regular Expression Complexity (ReDoS) (CWE-1333)
2025-05-30 security-advisories@github.com
6.5
CVSS 3.1 · GitHub Advisory
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Severity by source

GitHub Advisory PRIMARY
6.5 MEDIUM
AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Red Hat
6.5 MEDIUM
qualitative

Primary rating from GitHub Advisory.

CVSS VectorGitHub Advisory

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

4
Analysis Generated
Mar 28, 2026 - 18:44 vuln.today
Patch released
Mar 28, 2026 - 18:44 nvd
Patch available
PoC Detected
Jun 19, 2025 - 00:55 vuln.today
Public exploit code
CVE Published
May 30, 2025 - 18:15 nvd
MEDIUM 6.5

DescriptionGitHub Advisory

vLLM, an inference and serving engine for large language models (LLMs), has a Regular Expression Denial of Service (ReDoS) vulnerability in the file vllm/entrypoints/openai/tool_parsers/pythonic_tool_parser.py of versions 0.6.4 up to but excluding 0.9.0. The root cause is the use of a highly complex and nested regular expression for tool call detection, which can be exploited by an attacker to cause severe performance degradation or make the service unavailable. The pattern contains multiple nested quantifiers, optional groups, and inner repetitions which make it vulnerable to catastrophic backtracking. Version 0.9.0 contains a patch for the issue.

AnalysisAI

vLLM, an inference and serving engine for large language models (LLMs), has a Regular Expression Denial of Service (ReDoS) vulnerability in the file. Rated medium severity (CVSS 6.5), this vulnerability is remotely exploitable, low attack complexity. Public exploit code available.

Technical ContextAI

This vulnerability is classified under CWE-1333. vLLM, an inference and serving engine for large language models (LLMs), has a Regular Expression Denial of Service (ReDoS) vulnerability in the file vllm/entrypoints/openai/tool_parsers/pythonic_tool_parser.py of versions 0.6.4 up to but excluding 0.9.0. The root cause is the use of a highly complex and nested regular expression for tool call detection, which can be exploited by an attacker to cause severe performance degradation or make the service unavailable. The pattern contains multiple nested quantifiers, optional groups, and inner repetitions which make it vulnerable to catastrophic backtracking. Version 0.9.0 contains a patch for the issue. Affected products include: Vllm. Version information: Version 0.9.0.

RemediationAI

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.

Vendor StatusVendor

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CVE-2025-48887 vulnerability details – vuln.today

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