{"id":"CVE-2026-105758","title":"vLLM is an inference and serving engine for large language models","summary":"vLLM is an inference and serving engine for large language models. From 0.24.0 until 0.30.0, the Qwen2VLVideoBackend and Qwen3VLVideoBackend classes accept request-level values for the media_io_kwargs.video.max_frames and media_io_kwargs…","severity":"medium","cvss":5.3,"cvssVector":"CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L","cwe":["CWE-770"],"vendor":"vllm","product":"vllm","affected":["vllm >= 0.24.0, < 0.30.0"],"patched":["vllm 0.30.0"],"published":"2026-10-05","updated":"2026-10-08","sourceUpdated":"2026-10-08T03:16:35.407","source":"NVD","sourceUrl":"https://nvd.nist.gov/vuln/detail/CVE-2026-105758","references":[{"url":"https://github.com/vllm-project/vllm/commit/ea723c81c3ea26425cb69503a5d5e90822a04a45","label":"security-advisories@github.com"},{"url":"https://github.com/vllm-project/vllm/pull/56729","label":"security-advisories@github.com"},{"url":"https://github.com/vllm-project/vllm/releases/tag/v0.30.0","label":"security-advisories@github.com"},{"url":"https://github.com/vllm-project/vllm/security/advisories/GHSA-x6mc-67gf-chw4","label":"security-advisories@github.com"},{"url":"https://github.com/advisories/GHSA-x6mc-67gf-chw4"},{"url":"https://github.com/vllm-project/vllm"},{"url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-105758.json"},{"url":"https://access.redhat.com/security/cve/CVE-2026-105758"},{"url":"https://bugzilla.redhat.com/show_bug.cgi?id=2546187"},{"url":"https://www.cve.org/CVERecord?id=CVE-2026-105758"},{"url":"https://nvd.nist.gov/vuln/detail/CVE-2026-105758"},{"url":"https://pypi.org/project/vllm"}],"tags":["nvd","cve.org","ghsa","pip","osv","csaf","vex","red-hat"],"epss":0.00303,"epssPercentile":0.22922,"aliases":["GHSA-x6mc-67gf-chw4","PYSEC-2026-4310"],"ecosystem":"pip","ssvc":{"exploitation":"none","automatable":"yes","technicalImpact":"partial","timestamp":"2026-10-08T02:32:16.874942Z"},"ingestedAt":"2026-10-05T23:36:21.157Z","slug":"CVE-2026-105758","body":"## Overview\n\nvLLM is an inference and serving engine for large language models. From 0.24.0 until 0.30.0, the Qwen2VLVideoBackend and Qwen3VLVideoBackend classes accept request-level values for the media_io_kwargs.video.max_frames and media_io_kwargs.video.fps fields without enforcing server-side ceilings. An unauthenticated caller can submit these values to the /tokenize endpoint, causing the sampler to decode every frame selected from attacker-controlled video input, consume disproportionate frontend memory, and potentially terminate the API process before scheduling or admission control. The Rust frontend is not affected because it rejects the media_io_kwargs field. This issue is fixed in version 0.30.0.\n\n## Affected\n\n- `vllm >= 0.24.0, < 0.30.0`\n\n## Remediation\n\nUpgrade past the affected range:\n\n- `vllm 0.30.0`\n\n## Package advisory (CVE-2026-105758)\n\nAffected packages:\n\n- `vllm >= 0.24.0, < 0.30.0`\n\nPatched in:\n\n- `vllm 0.30.0`\n\nSource: https://github.com/advisories/GHSA-x6mc-67gf-chw4\n\n## Vendor advisories\n\n- **Red Hat VEX** · Moderate · affected: Red Hat AI Inference Server, Red Hat Enterprise Linux AI (RHEL AI) 3, Red Hat OpenShift AI (RHOAI) · no fix planned: Red Hat AI Inference Server, Red Hat Enterprise Linux AI (RHEL AI) 3, Red Hat OpenShift AI (RHOAI) · updated 2026-10-06 · [vex](https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-105758.json)","depth":"sunlit","depthScore":29,"depthScoreParts":{"impact":29.2,"likelihood":0.1,"exploitation":0,"ransomware":0},"changes":[]}