CVE-2026-55646
vLLM is an inference and serving engine for large language models.
Does this matter?
Lower severity and a low EPSS score (0.52%). Track it; it rarely justifies an emergency change on its own.
Description
vLLM is an inference and serving engine for large language models. From 0.22.0 to 0.23.0, the /v1/audio/transcriptions and /v1/audio/translations routes call request.file.read() to fully materialize an uploaded audio file into memory before vLLM checks the documented VLLM_MAX_AUDIO_CLIP_FILESIZE_MB compressed upload size limit (default 25 MB) later in the speech-to-text preprocessing step, so an API caller who can reach those routes can submit an oversized multipart upload and cause vLLM to allocate memory proportional to the uploaded file size before the request is rejected as too large, creating memory pressure or terminating the process depending on deployment resource limits. This issue is fixed in version 0.24.0.
- CVSS 3.1
- 6.5 MEDIUMCVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
- EPSS
- 0.52% probability · 44th percentile
- Public exploits
- None in Exploit-DB
- CISA KEV
- Not listed
- Weakness
- CWE-400, CWE-770
- Affected
- vllm/vllm
- Source
- security-advisories@github.com
EPSS 0.5% since 26 October 2026; no change recorded yet. Points are recorded when the score first appears and whenever it moves by a percentage point or more.
References
- https://github.com/vllm-project/vllm/commit/b997071ec493765abbed990c65843ed05e4708a8Patch
- https://github.com/vllm-project/vllm/pull/45510Issue Tracking, Patch
- https://github.com/vllm-project/vllm/security/advisories/GHSA-v82g-2437-67m2Vendor Advisory
- https://github.com/vllm-project/vllm/security/advisories/GHSA-v82g-2437-67m2Vendor Advisory
Source: NVD record, EPSS from FIRST.org, KEV from CISA, exploits from Exploit-DB. Refreshed daily. Download this record as JSON.