CVE-2026-44223

{"id": "CVE-2026-44223", "cveTags": [], "metrics": {"ssvcV203": [{"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0", "ssvcData": {"id": "CVE-2026-44223", "role": "CISA Coordinator", "options": [{"exploitation": "poc"}, {"automatable": "no"}, {"technicalImpact": "partial"}], "version": "2.0.3", "timestamp": "2026-05-15T14:44:05.012494Z"}}], "cvssMetricV31": [{"type": "Secondary", "source": "security-advisories@github.com", "cvssData": {"scope": "UNCHANGED", "version": "3.1", "baseScore": 6.5, "attackVector": "NETWORK", "baseSeverity": "MEDIUM", "vectorString": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H", "integrityImpact": "NONE", "userInteraction": "NONE", "attackComplexity": "LOW", "availabilityImpact": "HIGH", "privilegesRequired": "LOW", "confidentialityImpact": "NONE"}, "impactScore": 3.6, "exploitabilityScore": 2.8}]}, "affected": [{"source": "security-advisories@github.com", "affectedData": [{"vendor": "vllm-project", "product": "vllm", "versions": [{"status": "affected", "version": ">= 0.18.0, < 0.20.0"}]}]}], "published": "2026-05-12T20:16:43.293", "references": [{"url": "https://github.com/vllm-project/vllm/pull/38610", "tags": ["Issue Tracking", "Patch"], "source": "security-advisories@github.com"}, {"url": "https://github.com/vllm-project/vllm/security/advisories/GHSA-83vm-p52w-f9pw", "tags": ["Mitigation", "Vendor Advisory"], "source": "security-advisories@github.com"}, {"url": "https://github.com/vllm-project/vllm/pull/38610", "tags": ["Issue Tracking", "Patch"], "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0"}, {"url": "https://github.com/vllm-project/vllm/security/advisories/GHSA-83vm-p52w-f9pw", "tags": ["Mitigation", "Vendor Advisory"], "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0"}], "vulnStatus": "Modified", "weaknesses": [{"type": "Secondary", "source": "security-advisories@github.com", "description": [{"lang": "en", "value": "CWE-131"}, {"lang": "en", "value": "CWE-704"}]}], "descriptions": [{"lang": "en", "value": "vLLM is an inference and serving engine for large language models (LLMs). From 0.18.0 to before 0.20.0, the extract_hidden_states speculative decoding proposer in vLLM returns a tensor with an incorrect shape after the first decode step, causing a RuntimeError that crashes the EngineCore process. The crash is triggered when any request in the batch uses sampling penalty parameters (repetition_penalty, frequency_penalty, or presence_penalty). A single request with a penalty parameter (e.g., \"repetition_penalty\": 1.1) is sufficient to crash the server. This vulnerability is fixed in 0.20.0."}], "lastModified": "2026-06-22T22:16:45.507", "configurations": [{"nodes": [{"negate": false, "cpeMatch": [{"criteria": "cpe:2.3:a:vllm:vllm:*:*:*:*:*:*:*:*", "vulnerable": true, "matchCriteriaId": "443F32C2-B323-4FA0-AB97-F6445C91C89E", "versionEndExcluding": "0.20.0", "versionStartIncluding": "0.18.0"}], "operator": "OR"}]}], "sourceIdentifier": "security-advisories@github.com"}