CVE-2021-29529: Off-by-one Error
TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a heap buffer overflow in tf.raw_ops.QuantizedResizeBilinear
by manipulating input values so that float rounding results in off-by-one error in accessing image elements. This is because the implementation computes two integers by ceiling and flooring a floating point value. For some values of in
, interpolation->upperi might be smaller than
interpolation->loweri]. This is an issue if
interpolation->upper[i is capped at in_size-1
as it means that `interpolation->loweri of the image. Then, in the interpolation code, this would result in heap buffer overflow. 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.
References
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