Description
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.
CVSS Metrics
- Vector
- CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
- Attack Vector
- network
- Complexity
- low
- Privileges
- low
- User Action
- none
- Scope
- unchanged
- Confidentiality
- none
- Integrity
- none
- Availability
- high
- Weaknesses
- CWE-1333
Metadata
- Primary Vendor
- VLLM
- Published
- 5/30/2025
- Last Modified
- 6/19/2025
- Source
- NIST NVD
- Note: Verify all details with official vendor sources before applying patches.
Affected Products
vllm : vllm
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