Deserialization Of Untrusted Data

mlflow is vulnerable to Deserialization of Untrusted Data. The vulnerability is due to improper handling of untrusted data in the loadmodelfromlocalfile function within the sklearn/init.py. The vulnerability allows an attacker to inject a malicious pickle object into a model file on upload, which...