Evidence used
- No CISA KEV confirmation is currently recorded.
- A structured source references public exploit or proof-of-concept material.
- EPSS is 0.52% for the current model date.
BlackTreeCVE Intelligencevllm-project · vllm
Official source article: GitHub GHSA-W6Q7-J642-7C25 ↗. Check the applicable product and release in the original source.
Medium technical severity with public exploit material referenced by a structured source; prioritise exposed affected systems while verifying vendor guidance.
These OSV and GitHub advisory ranges apply only to the named package and ecosystem. A listed fixed version is not a universal product patch or proof that an update is installed.
| Ecosystem and package | Affected range | First fixed version | Evidence |
|---|---|---|---|
| pipvllm | >= 0.6.4, < 0.9.0 | 0.9.0 | GitHub advisory ↗upstream repository advisory · 19 Jun 2025 |
Medium technical severity with public exploit material referenced by a structured source; prioritise exposed affected systems while verifying vendor guidance.
Patch availablevLLM, 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.
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.
The product uses a regular expression with a worst-case computational complexity that is inefficient and possibly exponential.
An attacker operating through a network path may attempt exploitation with low privileges. If successful, the issue may disrupt the affected service.
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.
The product uses a regular expression with a worst-case computational complexity that is inefficient and possibly exponential.
An attacker operating through a network path may attempt exploitation with low privileges. If successful, the issue may disrupt the affected service.
CVSS severity, EPSS forecast probability, public exploit material and CISA-confirmed exploitation are separate signals.
No CISA KEV match was present at the last successful refresh. This means no confirmation from that source, not proof of no exploitation.
A structured CVE source labels at least one public reference as exploit material. BlackTree has not independently validated that it is safe, reliable or weaponised.
CWE-1333: Inefficient Regular Expression Complexity. The product uses a regular expression with a worst-case computational complexity that is inefficient and possibly exponential.
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:HCommon Vulnerability Scoring System 3.1: the compact vector below is decoded into plain language.
Operational remediation based on structured source evidence.
Published 30 May 2025 · Last source change 30 May 2025, 17:58 UTC · CWE-1333 · Inefficient Regular Expression Complexity
Core structured fields are present and their contributing authorities are shown above.
No material field changes have been recorded since change tracking began. Routine source refreshes and cosmetic edits are intentionally excluded.