{"id":"CVE-2025-62164","state":"PUBLISHED","title":"VLLM deserialization vulnerability leading to DoS and potential RCE","description":"vLLM is an inference and serving engine for large language models (LLMs). From versions 0.10.2 to before 0.11.1, a memory corruption vulnerability could lead to a crash (denial-of-service) and potentially remote code execution (RCE), exists in the Completions API endpoint. When processing user-supplied prompt embeddings, the endpoint loads serialized tensors using torch.load() without sufficient validation. Due to a change introduced in PyTorch 2.8.0, sparse tensor integrity checks are disabled by default. As a result, maliciously crafted tensors can bypass internal bounds checks and trigger an out-of-bounds memory write during the call to to_dense(). This memory corruption can crash vLLM and potentially lead to code execution on the server hosting vLLM. This issue has been patched in version 0.11.1.","publishedAt":"2025-11-21T01:18:38.803Z","updatedAt":"2025-11-24T18:12:44.195Z","severity":{"score":8.8,"label":"High","version":"3.1","vector":"CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H","source":"GitHub_M"},"assigner":"GitHub_M","products":["vllm-project vllm"],"affected":[{"vendor":"vllm-project","product":"vllm","versions":[{"version":">= 0.10.2, < 0.11.1","status":"affected"}]}],"references":["https://github.com/vllm-project/vllm/security/advisories/GHSA-mrw7-hf4f-83pf","https://github.com/vllm-project/vllm/pull/27204","https://github.com/vllm-project/vllm/commit/58fab50d82838d5014f4a14d991fdb9352c9c84b"],"weaknesses":["CWE-20","CWE-123","CWE-502","CWE-787"],"ingestedAt":"2026-10-29T20:09:48.677Z","source":{"repository":"CVEProject/cvelistV5","path":"cves/2025/62xxx/CVE-2025-62164.json","commit":"556c9d3a8cd17e218bb8e452ba7cd619a384ff47"},"raw":{"dataType":"CVE_RECORD","dataVersion":"5.2","cveMetadata":{"cveId":"CVE-2025-62164","state":"PUBLISHED","datePublished":"2025-11-21T01:18:38.803Z","dateUpdated":"2025-11-24T18:12:44.195Z","assignerShortName":"GitHub_M","assignerOrgId":"a0819718-46f1-4df5-94e2-005712e83aaa","dateReserved":"2025-10-07T16:12:03.425Z"},"containers":{"cna":{"title":"VLLM deserialization vulnerability leading to DoS and potential RCE","descriptions":[{"lang":"en","value":"vLLM is an inference and serving engine for large language models (LLMs). From versions 0.10.2 to before 0.11.1, a memory corruption vulnerability could lead to a crash (denial-of-service) and potentially remote code execution (RCE), exists in the Completions API endpoint. When processing user-supplied prompt embeddings, the endpoint loads serialized tensors using torch.load() without sufficient validation. Due to a change introduced in PyTorch 2.8.0, sparse tensor integrity checks are disabled by default. As a result, maliciously crafted tensors can bypass internal bounds checks and trigger an out-of-bounds memory write during the call to to_dense(). This memory corruption can crash vLLM and potentially lead to code execution on the server hosting vLLM. This issue has been patched in version 0.11.1."}],"affected":[{"vendor":"vllm-project","product":"vllm","versions":[{"version":">= 0.10.2, < 0.11.1","status":"affected"}]}],"references":[{"url":"https://github.com/vllm-project/vllm/security/advisories/GHSA-mrw7-hf4f-83pf","name":"https://github.com/vllm-project/vllm/security/advisories/GHSA-mrw7-hf4f-83pf","tags":["x_refsource_CONFIRM"]},{"url":"https://github.com/vllm-project/vllm/pull/27204","name":"https://github.com/vllm-project/vllm/pull/27204","tags":["x_refsource_MISC"]},{"url":"https://github.com/vllm-project/vllm/commit/58fab50d82838d5014f4a14d991fdb9352c9c84b","name":"https://github.com/vllm-project/vllm/commit/58fab50d82838d5014f4a14d991fdb9352c9c84b","tags":["x_refsource_MISC"]}],"metrics":[{"cvssV3_1":{"attackComplexity":"LOW","attackVector":"NETWORK","availabilityImpact":"HIGH","baseScore":8.8,"baseSeverity":"HIGH","confidentialityImpact":"HIGH","integrityImpact":"HIGH","privilegesRequired":"LOW","scope":"UNCHANGED","userInteraction":"NONE","vectorString":"CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H","version":"3.1"}}],"problemTypes":[{"descriptions":[{"cweId":"CWE-20","lang":"en","description":"CWE-20: Improper Input Validation","type":"CWE"}]},{"descriptions":[{"cweId":"CWE-123","lang":"en","description":"CWE-123: Write-what-where Condition","type":"CWE"}]},{"descriptions":[{"cweId":"CWE-502","lang":"en","description":"CWE-502: Deserialization of Untrusted Data","type":"CWE"}]},{"descriptions":[{"cweId":"CWE-787","lang":"en","description":"CWE-787: Out-of-bounds Write","type":"CWE"}]}],"providerMetadata":{"shortName":"GitHub_M","orgId":"a0819718-46f1-4df5-94e2-005712e83aaa","dateUpdated":"2025-11-21T01:18:38.803Z"},"source":{"advisory":"GHSA-mrw7-hf4f-83pf","discovery":"UNKNOWN"}},"adp":[{"title":"CISA ADP Vulnrichment","metrics":[{"other":{"type":"ssvc","content":{"timestamp":"2025-11-24T17:15:13.097938Z","id":"CVE-2025-62164","options":[{"Exploitation":"none"},{"Automatable":"no"},{"Technical Impact":"total"}],"role":"CISA Coordinator","version":"2.0.3"}}}],"providerMetadata":{"shortName":"CISA-ADP","orgId":"134c704f-9b21-4f2e-91b3-4a467353bcc0","dateUpdated":"2025-11-24T18:12:44.195Z"}}]}}}