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Party Advisory","advisory","web"]},{"url":"https://nvd.nist.gov/vuln/detail/CVE-2024-37053","tags":["web","advisory"]},{"url":"https://github.com/advisories/GHSA-43c4-9qgj-x742","tags":["advisory"]},{"url":"https://github.com/mlflow/mlflow","tags":["package"]},{"url":"https://pypi.org/project/mlflow","tags":["package"]}],"sources":{"cve":[{"id":"CVE-2024-37053","description":"Deserialization of untrusted data can occur in versions of the MLflow platform running version 1.1.0 or newer, enabling a maliciously uploaded scikit-learn model to run arbitrary code on an end user’s system when interacted with.","status":"published","published":"2024-06-04T12:00:15.162Z","modified":"2024-08-02T03:43:50.998Z","cvss":[{"version":"3.1","score":8.8,"vector":"CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H","level":"high","assessor":"cna"}],"cwes":["CWE-502"],"updated_at":"2026-11-02T14:34:00.585327Z"}],"euvd":[{"id":"EUVD-2024-1907","description":"Deserialization of untrusted data can occur in versions 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