{"dataType":"CVE_RECORD","dataVersion":"5.2","cveMetadata":{"cveId":"CVE-2026-105760","assignerOrgId":"a0819718-46f1-4df5-94e2-005712e83aaa","state":"PUBLISHED","assignerShortName":"GitHub_M","dateReserved":"2026-10-05T19:11:07.948Z","datePublished":"2026-10-05T23:01:54.972Z","dateUpdated":"2026-10-06T14:39:17.058Z"},"containers":{"cna":{"title":"vLLM: GLMGA video sampling permits request-driven CPU and memory exhaustion","problemTypes":[{"descriptions":[{"cweId":"CWE-400","lang":"en","description":"CWE-400: Uncontrolled Resource Consumption","type":"CWE"}]}],"metrics":[{"cvssV3_1":{"attackComplexity":"LOW","attackVector":"NETWORK","availabilityImpact":"LOW","baseScore":5.3,"baseSeverity":"MEDIUM","confidentialityImpact":"NONE","integrityImpact":"NONE","privilegesRequired":"NONE","scope":"UNCHANGED","userInteraction":"NONE","vectorString":"CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L","version":"3.1"}}],"references":[{"name":"https://github.com/vllm-project/vllm/security/advisories/GHSA-58v5-2m8f-94pr","tags":["x_refsource_CONFIRM"],"url":"https://github.com/vllm-project/vllm/security/advisories/GHSA-58v5-2m8f-94pr"},{"name":"https://github.com/vllm-project/vllm/pull/54935","tags":["x_refsource_MISC"],"url":"https://github.com/vllm-project/vllm/pull/54935"},{"name":"https://github.com/vllm-project/vllm/commit/8b6de0eb9a09ef53f20cf06bd4d17ee264b9c2a7","tags":["x_refsource_MISC"],"url":"https://github.com/vllm-project/vllm/commit/8b6de0eb9a09ef53f20cf06bd4d17ee264b9c2a7"},{"name":"https://github.com/vllm-project/vllm/releases/tag/v0.30.0","tags":["x_refsource_MISC"],"url":"https://github.com/vllm-project/vllm/releases/tag/v0.30.0"}],"affected":[{"vendor":"vllm-project","product":"vllm","versions":[{"version":">= 0.23.0rc2, < 0.30.0","status":"affected"}]}],"providerMetadata":{"orgId":"a0819718-46f1-4df5-94e2-005712e83aaa","shortName":"GitHub_M","dateUpdated":"2026-10-05T23:01:54.972Z"},"descriptions":[{"lang":"en","value":"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."}],"source":{"advisory":"GHSA-58v5-2m8f-94pr","discovery":"UNKNOWN"}},"adp":[{"metrics":[{"other":{"type":"ssvc","content":{"timestamp":"2026-10-06T14:38:28.658453Z","id":"CVE-2026-105760","options":[{"Exploitation":"none"},{"Automatable":"yes"},{"Technical Impact":"partial"}],"role":"CISA Coordinator","version":"2.0.3"}}}],"title":"CISA ADP Vulnrichment","providerMetadata":{"orgId":"134c704f-9b21-4f2e-91b3-4a467353bcc0","shortName":"CISA-ADP","dateUpdated":"2026-10-06T14:39:17.058Z"}}]}}