vLLM: GLMGA video sampling permits request-driven CPU and memory exhaustion (vllm-project vllm)

CVE-2026-105760
MEDIUM 5.3

At a glance

Source
NVD
EPSS
EPSS 0.30 % Β· percentile 22 ()
State
PUBLISHED
Published
Updated
Assigner
GitHub_M
NVD status
Analyzed

Description

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.

Weaknesses (CWE)

  • CWE-400 β€” Uncontrolled Resource Consumption

References

Scores

VersionScoreVectorScored by
CVSS 3.1MEDIUM 5.3CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:LGitHub_M
CVSS 3.1MEDIUM 5.3CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:LNVD Β· security-advisories@github.com (Secondary)

Advisories

European references

Affected configurations (NVD CPE)

Affected products

ProductVersions
vllm-project Β· vllmaffected >= 0.23.0rc2, < 0.30.0

Sources

SourceLicence
CVE List (CVEProject cvelistV5)CVE Program Terms of Use
EPSS (FIRST.org)FIRST β€” attribution requested
ENISA EUVDENISA β€” reproduction authorised, source acknowledged
NVD (NIST) via fkie-cad/nvd-json-data-feedsPublic domain β€” this product uses data from the NVD API but is not endorsed or certified by the NVD