CVE-2021-29603
A specially crafted TFLite model could trigger an OOB write on heap in the
TFLite implementation of
ArgMin
/ArgMax
:
TfLiteIntArray* output_dims = TfLiteIntArrayCreate(NumDimensions(input) - 1);
int j = 0;
for (int i = 0; i < NumDimensions(input); ++i) {
if (i != axis_value) {
output_dims->data[j] = SizeOfDimension(input, i);
++j;
}
}
If axis_value
is not a value between 0 and NumDimensions(input)
, then the
condition in the if
is never true, so code writes past the last valid element
of output_dims->data
.
We have patched the issue in GitHub commit c59c37e7b2d563967da813fa50fe20b21f4da683.
The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
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This vulnerability has been reported by members of the Aivul Team from Qihoo 360.