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SciKit-Learn 0.23.2 Denial Of Service Vulnerability
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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) # 0day.today [2024-11-16] #