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 lmfo…
Medium CVSS 5.3
Summary
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 cata…
In-depth triage
No in-depth report has been generated yet (DR-003 v2 AI pipeline is under construction).
Sources
- NVD DATABASE
Original Links
- https://github.com/vllm-project/vllm/commit/c9a788eedc412acceaa5112e0d44624b49841577
- https://github.com/vllm-project/vllm/pull/47595
- https://github.com/vllm-project/vllm/releases/tag/v0.26.0
- https://github.com/vllm-project/vllm/security/advisories/GHSA-48jh-3gj7-fg8v
- https://github.com/vllm-project/vllm/security/advisories/GHSA-48jh-3gj7-fg8v
Timeline
- nvd_ingest NVD