{"resultsPerPage":1,"startIndex":0,"totalResults":1,"format":"NVD_CVE","version":"2.0","timestamp":"2026-04-19T03:24:36.047","vulnerabilities":[{"cve":{"id":"CVE-2025-24357","sourceIdentifier":"security-advisories@github.com","published":"2025-01-27T18:15:41.523","lastModified":"2025-06-27T19:30:59.223","vulnStatus":"Analyzed","cveTags":[],"descriptions":[{"lang":"en","value":"vLLM is a library for LLM inference and serving. vllm/model_executor/weight_utils.py implements hf_model_weights_iterator to load the model checkpoint, which is downloaded from huggingface. It uses the torch.load function and the weights_only parameter defaults to False. When torch.load loads malicious pickle data, it will execute arbitrary code during unpickling. This vulnerability is fixed in v0.7.0."},{"lang":"es","value":"vLLM es una librería para la inferencia y el servicio de LLM. vllm/model_executor/weight_utils.py implementa hf_model_weights_iterator para cargar el punto de control del modelo, que se descarga desde huggingface. Utiliza la función Torch.load y el parámetro weights_only tiene el valor predeterminado Falso. Cuando Torch.load carga datos pickle maliciosos, ejecutará código arbitrario durante el desensamblaje. Esta vulnerabilidad se corrigió en la versión v0.7.0."}],"metrics":{"cvssMetricV31":[{"source":"security-advisories@github.com","type":"Secondary","cvssData":{"version":"3.1","vectorString":"CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:H","baseScore":7.5,"baseSeverity":"HIGH","attackVector":"NETWORK","attackComplexity":"HIGH","privilegesRequired":"NONE","userInteraction":"REQUIRED","scope":"UNCHANGED","confidentialityImpact":"HIGH","integrityImpact":"HIGH","availabilityImpact":"HIGH"},"exploitabilityScore":1.6,"impactScore":5.9},{"source":"nvd@nist.gov","type":"Primary","cvssData":{"version":"3.1","vectorString":"CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H","baseScore":8.8,"baseSeverity":"HIGH","attackVector":"NETWORK","attackComplexity":"LOW","privilegesRequired":"NONE","userInteraction":"REQUIRED","scope":"UNCHANGED","confidentialityImpact":"HIGH","integrityImpact":"HIGH","availabilityImpact":"HIGH"},"exploitabilityScore":2.8,"impactScore":5.9}]},"weaknesses":[{"source":"security-advisories@github.com","type":"Secondary","description":[{"lang":"en","value":"CWE-502"}]}],"configurations":[{"nodes":[{"operator":"OR","negate":false,"cpeMatch":[{"vulnerable":true,"criteria":"cpe:2.3:a:vllm:vllm:*:*:*:*:*:*:*:*","versionEndExcluding":"0.7.0","matchCriteriaId":"78210BFE-5D31-4D84-BA73-75C1594A3A3C"}]}]}],"references":[{"url":"https://github.com/vllm-project/vllm/commit/d3d6bb13fb62da3234addf6574922a4ec0513d04","source":"security-advisories@github.com","tags":["Patch"]},{"url":"https://github.com/vllm-project/vllm/pull/12366","source":"security-advisories@github.com","tags":["Issue Tracking","Patch"]},{"url":"https://github.com/vllm-project/vllm/security/advisories/GHSA-rh4j-5rhw-hr54","source":"security-advisories@github.com","tags":["Vendor Advisory"]},{"url":"https://pytorch.org/docs/stable/generated/torch.load.html","source":"security-advisories@github.com","tags":["Technical Description"]}]}}]}