CVE-2026-31237

{"dataType": "CVE_RECORD", "cveMetadata": {"state": "PUBLISHED", "cveId": "CVE-2026-31237", "assignerOrgId": "8254265b-2729-46b6-b9e3-3dfca2d5bfca", "assignerShortName": "mitre", "dateUpdated": "2026-05-14T19:54:23.672Z", "dateReserved": "2026-03-09T00:00:00.000Z", "datePublished": "2026-05-12T00:00:00.000Z"}, "containers": {"cna": {"providerMetadata": {"orgId": "8254265b-2729-46b6-b9e3-3dfca2d5bfca", "shortName": "mitre", "dateUpdated": "2026-05-12T17:13:00.667Z"}, "descriptions": [{"lang": "en", "value": "The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) through its predict() method. When a user provides a dataset file path to the predict() method, the framework automatically determines the file format. If the file is a pickle (.pkl) file, it is loaded using pandas.read_pickle() without any validation or security restrictions. This allows the deserialization of arbitrary Python objects via the unsafe pickle module. A remote attacker can exploit this by providing a maliciously crafted pickle file, leading to arbitrary code execution on the system running the Ludwig prediction."}], "affected": [{"vendor": "n/a", "product": "n/a", "versions": [{"version": "n/a", "status": "affected"}]}], "references": [{"url": "https://github.com/ludwig-ai/ludwig"}, {"url": "https://www.notion.so/CVE-2026-31237-35d1e139318881fb95a2ee7c5d0e17d8"}], "problemTypes": [{"descriptions": [{"type": "text", "lang": "en", "description": "n/a"}]}]}, "adp": [{"problemTypes": [{"descriptions": [{"type": "CWE", "cweId": "CWE-502", "lang": "en", "description": "CWE-502 Deserialization of Untrusted Data"}]}], "metrics": [{"cvssV3_1": {"scope": "UNCHANGED", "version": "3.1", "baseScore": 9.8, "attackVector": "NETWORK", "baseSeverity": "CRITICAL", "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H", "integrityImpact": "HIGH", "userInteraction": "NONE", "attackComplexity": "LOW", "availabilityImpact": "HIGH", "privilegesRequired": "NONE", "confidentialityImpact": "HIGH"}}, {"other": {"type": "ssvc", "content": {"timestamp": "2026-05-14T16:56:05.309414Z", "id": "CVE-2026-31237", "options": [{"Exploitation": "none"}, {"Automatable": "yes"}, {"Technical Impact": "total"}], "role": "CISA Coordinator", "version": "2.0.3"}}}], "title": "CISA ADP Vulnrichment", "providerMetadata": {"orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0", "shortName": "CISA-ADP", "dateUpdated": "2026-05-14T19:54:23.672Z"}}]}, "dataVersion": "5.2"}

{"dataType": "CVE_RECORD", "containers": {"adp": [{"title": "CISA ADP Vulnrichment", "metrics": [{"cvssV3_1": {"scope": "UNCHANGED", "version": "3.1", "baseScore": 9.8, "attackVector": "NETWORK", "baseSeverity": "CRITICAL", "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H", "integrityImpact": "HIGH", "userInteraction": "NONE", "attackComplexity": "LOW", "availabilityImpact": "HIGH", "privilegesRequired": "NONE", "confidentialityImpact": "HIGH"}}, {"other": {"type": "ssvc", "content": {"id": "CVE-2026-31237", "role": "CISA Coordinator", "options": [{"Exploitation": "none"}, {"Automatable": "yes"}, {"Technical Impact": "total"}], "version": "2.0.3", "timestamp": "2026-05-14T16:56:05.309414Z"}}}], "problemTypes": [{"descriptions": [{"lang": "en", "type": "CWE", "cweId": "CWE-502", "description": "CWE-502 Deserialization of Untrusted Data"}]}], "providerMetadata": {"orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0", "shortName": "CISA-ADP", "dateUpdated": "2026-05-14T16:56:23.072Z"}}], "cna": {"affected": [{"vendor": "n/a", "product": "n/a", "versions": [{"status": "affected", "version": "n/a"}]}], "references": [{"url": "https://github.com/ludwig-ai/ludwig"}, {"url": "https://www.notion.so/CVE-2026-31237-35d1e139318881fb95a2ee7c5d0e17d8"}], "descriptions": [{"lang": "en", "value": "The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) through its predict() method. When a user provides a dataset file path to the predict() method, the framework automatically determines the file format. If the file is a pickle (.pkl) file, it is loaded using pandas.read_pickle() without any validation or security restrictions. This allows the deserialization of arbitrary Python objects via the unsafe pickle module. A remote attacker can exploit this by providing a maliciously crafted pickle file, leading to arbitrary code execution on the system running the Ludwig prediction."}], "problemTypes": [{"descriptions": [{"lang": "en", "type": "text", "description": "n/a"}]}], "providerMetadata": {"orgId": "8254265b-2729-46b6-b9e3-3dfca2d5bfca", "shortName": "mitre", "dateUpdated": "2026-05-12T17:13:00.667Z"}}}, "cveMetadata": {"cveId": "CVE-2026-31237", "state": "PUBLISHED", "dateUpdated": "2026-05-14T19:54:23.672Z", "dateReserved": "2026-03-09T00:00:00.000Z", "assignerOrgId": "8254265b-2729-46b6-b9e3-3dfca2d5bfca", "datePublished": "2026-05-12T00:00:00.000Z", "assignerShortName": "mitre"}, "dataVersion": "5.2"}

{"affected": [{"affectedData": [{"product": "n/a", "vendor": "n/a", "versions": [{"status": "affected", "version": "n/a"}]}], "source": "cve@mitre.org"}], "cveTags": [], "descriptions": [{"lang": "en", "value": "The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) through its predict() method. When a user provides a dataset file path to the predict() method, the framework automatically determines the file format. If the file is a pickle (.pkl) file, it is loaded using pandas.read_pickle() without any validation or security restrictions. This allows the deserialization of arbitrary Python objects via the unsafe pickle module. A remote attacker can exploit this by providing a maliciously crafted pickle file, leading to arbitrary code execution on the system running the Ludwig prediction."}, {"lang": "es", "value": "El framework Ludwig hasta la versi\u00f3n 0.10.4 es vulnerable a la deserializaci\u00f3n insegura (CWE-502) a trav\u00e9s de su m\u00e9todo predict(). Cuando un usuario proporciona una ruta de archivo de conjunto de datos al m\u00e9todo predict(), el framework determina autom\u00e1ticamente el formato del archivo. Si el archivo es un archivo pickle (.pkl), se carga usando pandas.read_pickle() sin ninguna validaci\u00f3n ni restricciones de seguridad. Esto permite la deserializaci\u00f3n de objetos Python arbitrarios a trav\u00e9s del m\u00f3dulo pickle inseguro. Un atacante remoto puede explotar esto al proporcionar un archivo pickle creado maliciosamente, lo que lleva a la ejecuci\u00f3n de c\u00f3digo arbitrario en el sistema que ejecuta la predicci\u00f3n de Ludwig."}], "id": "CVE-2026-31237", "lastModified": "2026-10-19T22:10:00.130", "metrics": {"cvssMetricV31": [{"cvssData": {"attackComplexity": "LOW", "attackVector": "NETWORK", "availabilityImpact": "HIGH", "baseScore": 9.8, "baseSeverity": "CRITICAL", "confidentialityImpact": "HIGH", "integrityImpact": "HIGH", "privilegesRequired": "NONE", "scope": "UNCHANGED", "userInteraction": "NONE", "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H", "version": "3.1"}, "exploitabilityScore": 3.9, "impactScore": 5.9, "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0", "type": "Secondary"}], "ssvcV203": [{"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0", "ssvcData": {"id": "CVE-2026-31237", "options": [{"exploitation": "none"}, {"automatable": "yes"}, {"technicalImpact": "total"}], "role": "CISA Coordinator", "timestamp": "2026-05-14T16:56:05.309414Z", "version": "2.0.3"}}]}, "published": "2026-05-12T18:16:52.087", "references": [{"source": "cve@mitre.org", "url": "https://github.com/ludwig-ai/ludwig"}, {"source": "cve@mitre.org", "url": "https://www.notion.so/CVE-2026-31237-35d1e139318881fb95a2ee7c5d0e17d8"}], "sourceIdentifier": "cve@mitre.org", "vulnStatus": "Deferred", "weaknesses": [{"description": [{"lang": "en", "value": "CWE-502"}], "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0", "type": "Secondary"}]}

{}

{"affected": [{"configurations": [{"platform": null, "status": "affected", "versions": {"scheme": "semver", "value": "0.10.4"}}], "enrichment": {"confidence": 80.0, "confidence_source": "inferred", "scores": [{"score": 80.0, "source": "inferred"}]}, "original": {"product": "n/a", "source": "cna", "vendor": "n/a"}, "product": "ludwig", "vendor": "ludwig-ai"}], "created": "2026-05-12T18:30:22.229991+00:00", "updated": "2026-05-14T22:00:10.681215+00:00", "vendors": ["ludwig-ai", "ludwig-ai$PRODUCT$ludwig"]}