{"id":"CVE-2026-105754","title":"vLLM is an inference and serving engine for large language models","summary":"vLLM is an inference and serving engine for large language models. Prior to 0.30.0, the /inference/v1/generate endpoint in the disaggregated scale-out path accepts caller-supplied tensors in the features.kwargs_data field, cache identifi…","severity":"medium","cvss":6.5,"cvssVector":"CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H","cwe":["CWE-20","CWE-617","CWE-639","CWE-668","CWE-704","CWE-1284"],"vendor":"vllm","product":"vllm","affected":["vllm < 0.30.0"],"patched":["vllm 0.30.0"],"published":"2026-10-05","updated":"2026-10-08","sourceUpdated":"2026-10-08T03:16:35.230","source":"NVD","sourceUrl":"https://nvd.nist.gov/vuln/detail/CVE-2026-105754","references":[{"url":"https://github.com/vllm-project/vllm/commit/1970f3ed4be7fa8620e4ddc4a12c36a8384cfc27","label":"security-advisories@github.com"},{"url":"https://github.com/vllm-project/vllm/pull/51898","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-ph72-cqr5-qpp7","label":"security-advisories@github.com"},{"url":"https://github.com/advisories/GHSA-ph72-cqr5-qpp7"},{"url":"https://github.com/vllm-project/vllm"},{"url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-105754.json"},{"url":"https://access.redhat.com/security/cve/CVE-2026-105754"},{"url":"https://bugzilla.redhat.com/show_bug.cgi?id=2546186"},{"url":"https://www.cve.org/CVERecord?id=CVE-2026-105754"},{"url":"https://nvd.nist.gov/vuln/detail/CVE-2026-105754"},{"url":"https://pypi.org/project/vllm"}],"tags":["nvd","cve.org","ghsa","pip","osv","csaf","vex","red-hat"],"epss":0.00269,"epssPercentile":0.18966,"aliases":["GHSA-ph72-cqr5-qpp7","PYSEC-2026-4309"],"ecosystem":"pip","ssvc":{"exploitation":"none","automatable":"no","technicalImpact":"partial","timestamp":"2026-10-08T02:31:20.281715Z"},"ingestedAt":"2026-10-05T23:36:21.156Z","slug":"CVE-2026-105754","body":"## Overview\n\nvLLM is an inference and serving engine for large language models. Prior to 0.30.0, the /inference/v1/generate endpoint in the disaggregated scale-out path accepts caller-supplied tensors in the features.kwargs_data field, cache identifiers in the features.mm_hashes field, ranges in the features.mm_placeholders field, and wire-selected multimodal field processors without rebinding them to the active model renderer contract. Forged grid geometry, field types, or non-positive placeholder lengths can terminate the shared EngineCore; when an attacker knows or can induce a victim's content hash, forged cache hashes can poison or retrieve cross-request encoder-cache state; and dropped sparse placeholder masks can alter replayed transport semantics. This issue is fixed in version 0.30.0.\n\n## Affected\n\n- `vllm < 0.30.0`\n\n## Remediation\n\nUpgrade past the affected range:\n\n- `vllm 0.30.0`\n\n## Package advisory (CVE-2026-105754)\n\nAffected packages:\n\n- `vllm < 0.30.0`\n\nPatched in:\n\n- `vllm 0.30.0`\n\nSource: https://github.com/advisories/GHSA-ph72-cqr5-qpp7\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-2026-105754.json)","depth":"sunlit","depthScore":36,"depthScoreParts":{"impact":35.8,"likelihood":0.1,"exploitation":0,"ransomware":0},"changes":[]}