CVE-2026-34755vLLM is an inference and serving engine for large language models (LLMs).

vLLM is an inference and serving engine for large language models (LLMs). From 0.7.0 to before 0.19.0, the VideoMediaIO.load_base64() method at vllm/multimodal/media/video.py splits video/jpeg data URLs by comma to extract individual JPEG frames, but does not enforce a frame count limit. The num_frames parameter (default: 32), which is enforced by the load_bytes() code path, is completely bypassed in the video/jpeg base64 path. An attacker can send a single API request containing thousands of comma-separated base64-encoded JPEG frames, causing the server to decode all frames into memory and crash with OOM. This vulnerability is fixed in 0.19.0.

CVSS

6.5 MEDIUM (v3.1, NVD)CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H

Weakness (CWE)

CWE-770

Known exploited

Not in CISA's KEV catalog

EPSS (exploitation in the next 30 days)

Not loaded for this CVE

Assigned by

Not given

NVD analysis

Modified

Record last updated

Aug 25, 2026

First seen by InfoSec Signals

Oct 9, 2026

The CVE record on cve.org · NVD's entry

The CVE record is authoritative. Products marked “from the name” were identified from the CNA's free-text names, not a CPE, and are matched less certainly. This product uses the NVD API but is not endorsed or certified by the NVD.