Answer in brief
CVE-2026-105760 records a Medium severity (CVSS 5.3) vulnerability in vLLM: GLMGA video sampling permits request-driven CPU and memory exhaustion. The current sources do not mark it as known exploited. The current feed maps vllm-project/vllm (generic), vllm (pip). Check affected ranges and fixed versions before updating.
Analysis pending evidence review
HOL Guard separates source facts from reviewed analysis. See the methodology.
CVSS is 5.3. The current sources do not mark it as known exploited. Treat this as a source-backed prioritization signal, not a statement about your environment.
Analysis status
Analysis pending evidence review
Factual feed record only; HOL analysis is not approved for indexing. Read the methodology.
The current feed maps vllm-project/vllm (generic), vllm (pip). Check affected ranges and fixed versions before updating.
| Package | Affected range | Fixed version |
|---|---|---|
| vllm-project/vllmgeneric | >=0.23.0rc2 <0.30.0 | 0.30.0 |
| vllmpip | >=0.23.0rc2,<0.30.0 | 0.30.0 |
Published upstream
Oct 5, 2026
Evidence: source:cvelist:source_dates:source-dates:recordSource modified
Oct 5, 2026
Evidence: source:cvelist:source_dates:source-dates:recordFirst seen by HOL
Oct 5, 2026
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.
Quoted source text, attributed separately from HOL analysis.