Vllm
CVE-2025-48887
MEDIUM
Severity by source
AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Primary rating from GitHub Advisory.
CVSS VectorGitHub Advisory
Lifecycle Timeline
4DescriptionGitHub 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.
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Same technique Denial Of Service
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