Description
vLLM is an inference and serving engine for large language models. Prior to 0.26.0, the structured_outputs.regex parameter in vllm/v1/structured_output/backend_lm_format_enforcer.py is passed to lmformatenforcer.RegexParser without compile_regex_with_timeout or validation in validate_structured_output_request_lm_format_enforcer, allowing an unauthenticated /v1/completions request against the lm-format-enforcer backend to consume a CPU core and stall the structured-output engine path with a catastrophic regular expression. This issue is fixed in version 0.26.0.
Affected products
vllm: vllm
References5
- github.com/vllm-project/vllm/security/advisories/GHSA-48jh-3gj7… Vendor Advisory
- github.com/vllm-project/vllm/security/advisories/GHSA-48jh-3gj7… Vendor Advisory
- github.com/vllm-project/vllm/commit/c9a788eedc412acceaa5112e0d4… Patch
- github.com/vllm-project/vllm/pull/47595 Issue TrackingPatch
- github.com/vllm-project/vllm/releases/tag/v0.26.0 Release Notes
Metrics
- CVSS 3.1
-
5.3
MEDIUM
Score source: CNA
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L - EPSS — exploit probability
- 1% percentile: 44 · as of 12 November 2026
- CWE
- CWE-400CWE-1333
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