Headline
CVE-2022-21741: [lite] Add validation check for dilation height/width to be positive … · tensorflow/tensorflow@e5b0eec
Tensorflow is an Open Source Machine Learning Framework. ### Impact An attacker can craft a TFLite model that would trigger a division by zero in the implementation of depthwise convolutions. The parameters of the convolution can be user controlled and are also used within a division operation to determine the size of the padding that needs to be added before applying the convolution. There is no check before this division that the divisor is strictly positive. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
@@ -115,6 +115,8 @@ TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
TF_LITE_ENSURE_EQ(context, NumDimensions(input), 4);
TF_LITE_ENSURE_EQ(context, NumDimensions(filter), 4);
TF_LITE_ENSURE(context, params->dilation_height_factor > 0);
TF_LITE_ENSURE(context, params->dilation_width_factor > 0);
const TfLiteType data_type = input->type;