vLLM, an inference and serving engine for large language models (LLMs), has a Regular Expression Denial of Service (ReDoS) vulnerability in the file...
Full analysis pending. Showing NVD description excerpt.
Affected Systems
| Package | Ecosystem | Vulnerable Range | Patched |
|---|---|---|---|
| vllm | pip | >= 0.6.4, < 0.9.0 | 0.9.0 |
| vllm | pip | — | No patch |
Severity & Risk
Recommended Action
Patch available
Update vllm to version 0.9.0
Compliance Impact
Compliance analysis pending. Sign in for full compliance mapping when available.
Technical Details
NVD 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.
Weaknesses (CWE)
CVSS Vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H References
- github.com/vllm-project/vllm/security/advisories/GHSA-w6q7-j642-7c25 Exploit Vendor
- github.com/advisories/GHSA-w6q7-j642-7c25
- github.com/pypa/advisory-database/tree/main/vulns/vllm/PYSEC-2025-50.yaml
- github.com/vllm-project/vllm/commit/4fc1bf813ad80172c1db31264beaef7d93fe0601
- github.com/vllm-project/vllm/pull/18454
- github.com/vllm-project/vllm/security/advisories/GHSA-w6q7-j642-7c25
- nvd.nist.gov/vuln/detail/CVE-2025-48887
- github.com/vllm-project/vllm/commit/4fc1bf813ad80172c1db31264beaef7d93fe0601 Patch
- github.com/vllm-project/vllm/pull/18454 Issue Patch
- github.com/vllm-project/vllm/security/advisories/GHSA-w6q7-j642-7c25 Exploit Vendor