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.

Classification

CVE ID: CVE-2025-48887

CVSS Base Severity: MEDIUM

CVSS Base Score: 6.5

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

Affected Products

Vendor: vllm-project

Product: vllm

References

https://nvd.nist.gov/vuln/detail/CVE-2025-48887
https://github.com/vllm-project/vllm/security/advisories/GHSA-w6q7-j642-7c25
https://github.com/vllm-project/vllm/pull/18454
https://github.com/vllm-project/vllm/commit/4fc1bf813ad80172c1db31264beaef7d93fe0601

Timeline