Disclosure summary
vLLM is an inference and serving engine for large language models. Prior to 0.30.0, a caller can use the request-level media_io_kwargs field to select the GLMGA video backend and supply large values for the fps and max_frames options without a strict work ceiling. GLMGA constructs and deduplicates an attacker-sized pre-decode frame-index list, allowing a compact request and tiny valid video to consume disproportionate CPU time and memory in the shared media-loading executor. This issue is fixed in version 0.30.0.
Source-reported weakness categories
CWE-400
Source-specific records & product guidance
Sources retain their own attribution and scoring. Follow the original record to confirm affected versions, fixed releases, and configuration conditions.
NIST National Vulnerability Database · NVD-CVE-2026-105760
Open original source · Updated Oct 06, 2026
Only CPE matches marked vulnerable=true are indexed. AND/OR platform conditions must be checked in the original NVD record.
GitHub Reviewed Security Advisories · GHSA-58v5-2m8f-94pr
Open original source · Updated Oct 05, 2026
vLLM: GLMGA video sampling permits request-driven CPU and memory exhaustion
Source severity: MEDIUM / 0
| Ecosystem | Package | Affected range | First patched |
|---|---|---|---|
| pip | vllm | >= 0.23.0rc2, < 0.30.0 | 0.30.0 |
Original records & references
PUBLISHED 2026-10-05T19:17:02-04:00
MODIFIED 2026-10-06T11:17:15-04:00
INGESTED 2026-10-06T11:45:40-04:00