{"dataType": "CVE_RECORD", "cveMetadata": {"state": "PUBLISHED", "cveId": "CVE-2026-31229", "assignerOrgId": "8254265b-2729-46b6-b9e3-3dfca2d5bfca", "assignerShortName": "mitre", "dateUpdated": "2026-05-12T17:05:49.367Z", "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": "2026-05-12T17:05:49.367Z"}, "descriptions": [{"lang": "en", "value": "The Adversarial Robustness Toolbox (ART) thru 1.20.1 contains an insecure deserialization vulnerability (CWE-502) in its Kubeflow component's model loading functionality. When loading model weights from a file (e.g., model.pt) during robustness evaluation, the code uses torch.load() without the security-restrictive weights_only=True parameter. This allows the deserialization of arbitrary Python objects via the Pickle module. An attacker can exploit this by uploading a maliciously crafted model file to an object storage location referenced by the pipeline, or by controlling the model_id parameter to point to such a file. When the pipeline loads the model, the malicious payload is executed, leading to remote code execution."}], "affected": [{"vendor": "n/a", "product": "n/a", "versions": [{"version": "n/a", "status": "affected"}]}], "references": [{"url": "https://github.com/Trusted-AI/adversarial-robustness-toolbox"}, {"url": "https://www.notion.so/CVE-2026-31229-35d1e13931888172863dcc20beeb6b70"}], "problemTypes": [{"descriptions": [{"type": "text", "lang": "en", "description": "n/a"}]}]}}, "dataVersion": "5.2"}

{}

{"cveTags": [], "descriptions": [{"lang": "en", "value": "The Adversarial Robustness Toolbox (ART) thru 1.20.1 contains an insecure deserialization vulnerability (CWE-502) in its Kubeflow component's model loading functionality. When loading model weights from a file (e.g., model.pt) during robustness evaluation, the code uses torch.load() without the security-restrictive weights_only=True parameter. This allows the deserialization of arbitrary Python objects via the Pickle module. An attacker can exploit this by uploading a maliciously crafted model file to an object storage location referenced by the pipeline, or by controlling the model_id parameter to point to such a file. When the pipeline loads the model, the malicious payload is executed, leading to remote code execution."}], "id": "CVE-2026-31229", "lastModified": "2026-05-12T18:16:51.160", "metrics": {}, "published": "2026-05-12T18:16:51.160", "references": [{"source": "cve@mitre.org", "url": "https://github.com/Trusted-AI/adversarial-robustness-toolbox"}, {"source": "cve@mitre.org", "url": "https://www.notion.so/CVE-2026-31229-35d1e13931888172863dcc20beeb6b70"}], "sourceIdentifier": "cve@mitre.org", "vulnStatus": "Received"}

{}

{}