Division by zero in optimized pooling implementations in TFLite

Impact Optimized pooling implementations in TFLite fail to check that the stride arguments are not 0 before calling ComputePaddingHeightWidth. Since users can craft special models which will have params-strideheight,width be zero, this will result in a division by zero. Patches We have patched th...

GHSA-MV78-G7WQ-MHP4 Division by zero in padding computation in TFLite

Impact The TFLite computation for size of output after padding, ComputeOutSize, does not check that the stride argument is not 0 before doing the division. cc inline int ComputeOutSizeTfLitePadding padding, int imagesize, int filtersize, int stride, int dilationrate = 1 int effectivefiltersize =...

Division by zero in padding computation in TFLite

Impact The TFLite computation for size of output after padding, ComputeOutSize, does not check that the stride argument is not 0 before doing the division. cc inline int ComputeOutSizeTfLitePadding padding, int imagesize, int filtersize, int stride, int dilationrate = 1 int effectivefiltersize =...

CHECK-fail due to integer overflow

Impact An attacker can trigger a denial of service via a CHECK-fail in caused by an integer overflow in constructing a new tensor shape: python import tensorflow as tf inputlayer = 260-1 sparsedata = tf.rawops.SparseSplit splitdim=1, indices=0, 0, 0, 1, 0, 2, 4, 3, 5, 0, 5, 1, values=1.0, 1.0, 1....

GHSA-XVJM-FVXX-Q3HV CHECK-fail due to integer overflow

Impact An attacker can trigger a denial of service via a CHECK-fail in caused by an integer overflow in constructing a new tensor shape: python import tensorflow as tf inputlayer = 260-1 sparsedata = tf.rawops.SparseSplit splitdim=1, indices=0, 0, 0, 1, 0, 2, 4, 3, 5, 0, 5, 1, values=1.0, 1.0, 1....

Heap buffer overflow and undefined behavior in `FusedBatchNorm`

Impact The implementation of tf.rawops.FusedBatchNorm is vulnerable to a heap buffer overflow: python import tensorflow as tf x = tf.zeros10, 10, 10, 6, dtype=tf.float32 scale = tf.constant0.0, shape=1, dtype=tf.float32 offset = tf.constant0.0, shape=1, dtype=tf.float32 mean = tf.constant0.0,...

Heap OOB read in `tf.raw_ops.Dequantize`

Impact Due to lack of validation in tf.rawops.Dequantize, an attacker can trigger a read from outside of bounds of heap allocated data: python import tensorflow as tf inputtensor=tf.constant 75, 75, 75, 75, -6, -9, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10,\ -10, -10, -10, -10, -10, -10,...

Segfault in `CTCBeamSearchDecoder`

Impact Due to lack of validation in tf.rawops.CTCBeamSearchDecoder, an attacker can trigger denial of service via segmentation faults: python import tensorflow as tf inputs = tf.constant, shape=18, 8, 0, dtype=tf.float32 sequencelength = tf.constant11, -43, -92, 11, -89, -83, -35, -100, shape=8,...

Undefined behavior and `CHECK`-fail in `FractionalMaxPoolGrad`

Impact The implementation of tf.rawops.FractionalMaxPoolGrad triggers an undefined behavior if one of the input tensors is empty: python import tensorflow as tf originput = tf.constant2, 3, shape=1, 1, 1, 2, dtype=tf.int64 origoutput = tf.constant, dtype=tf.int64 outbackprop = tf.zeros2, 3, 6, 6,...

GHSA-79FV-9865-4QCV Heap buffer overflow in `MaxPoolGrad`

Impact The implementation of tf.rawops.MaxPoolGrad is vulnerable to a heap buffer overflow: python import tensorflow as tf originput = tf.constant0.0, shape=1, 1, 1, 1, dtype=tf.float32 origoutput = tf.constant0.0, shape=1, 1, 1, 1, dtype=tf.float32 grad = tf.constant, shape=0, 0, 0, 0,...

Heap buffer overflow in `MaxPoolGrad`

Impact The implementation of tf.rawops.MaxPoolGrad is vulnerable to a heap buffer overflow: python import tensorflow as tf originput = tf.constant0.0, shape=1, 1, 1, 1, dtype=tf.float32 origoutput = tf.constant0.0, shape=1, 1, 1, 1, dtype=tf.float32 grad = tf.constant, shape=0, 0, 0, 0,...

GHSA-6F89-8J54-29XF Heap buffer overflow in `FractionalAvgPoolGrad`

Impact The implementation of tf.rawops.FractionalAvgPoolGrad is vulnerable to a heap buffer overflow: python import tensorflow as tf originputtensorshape = tf.constant1, 3, 2, 3, shape=4, dtype=tf.int64 outbackprop = tf.constant2, shape=1, 1, 1, 1, dtype=tf.int64 rowpoolingsequence = tf.constant1...

Heap buffer overflow in `FractionalAvgPoolGrad`

Impact The implementation of tf.rawops.FractionalAvgPoolGrad is vulnerable to a heap buffer overflow: python import tensorflow as tf originputtensorshape = tf.constant1, 3, 2, 3, shape=4, dtype=tf.int64 outbackprop = tf.constant2, shape=1, 1, 1, 1, dtype=tf.int64 rowpoolingsequence = tf.constant1...

GHSA-V6R6-84GR-92RM Heap buffer overflow in `AvgPool3DGrad`

Impact The implementation of tf.rawops.AvgPool3DGrad is vulnerable to a heap buffer overflow: python import tensorflow as tf originputshape = tf.constant10, 6, 3, 7, 7, shape=5, dtype=tf.int32 grad = tf.constant0.01, 0, 0, shape=3, 1, 1, 1, 1, dtype=tf.float32 ksize = 1, 1, 1, 1, 1 strides = 1, 1...

Heap buffer overflow in `AvgPool3DGrad`

Impact The implementation of tf.rawops.AvgPool3DGrad is vulnerable to a heap buffer overflow: python import tensorflow as tf originputshape = tf.constant10, 6, 3, 7, 7, shape=5, dtype=tf.int32 grad = tf.constant0.01, 0, 0, shape=3, 1, 1, 1, 1, dtype=tf.float32 ksize = 1, 1, 1, 1, 1 strides = 1, 1...

GHSA-7CQX-92HP-X6WH Heap buffer overflow in `MaxPool3DGradGrad`

Impact The implementation of tf.rawops.MaxPool3DGradGrad is vulnerable to a heap buffer overflow: python import tensorflow as tf values = 0.01 11 originput = tf.constantvalues, shape=11, 1, 1, 1, 1, dtype=tf.float32 origoutput = tf.constant0.01, shape=1, 1, 1, 1, 1, dtype=tf.float32 grad =...

Heap buffer overflow in `MaxPool3DGradGrad`

Impact The implementation of tf.rawops.MaxPool3DGradGrad is vulnerable to a heap buffer overflow: python import tensorflow as tf values = 0.01 11 originput = tf.constantvalues, shape=11, 1, 1, 1, 1, dtype=tf.float32 origoutput = tf.constant0.01, shape=1, 1, 1, 1, 1, dtype=tf.float32 grad =...

Overflow/denial of service in `tf.raw_ops.ReverseSequence`

Impact The implementation of tf.rawops.ReverseSequence allows for stack overflow and/or CHECK-fail based denial of service. python import tensorflow as tf input = tf.zeros1, 1, 1, dtype=tf.int32 seqlengths = tf.constant0, shape=1, dtype=tf.int32 tf.rawops.ReverseSequence input=input,...

GHSA-6QGM-FV6V-RFPV Overflow/denial of service in `tf.raw_ops.ReverseSequence`

Impact The implementation of tf.rawops.ReverseSequence allows for stack overflow and/or CHECK-fail based denial of service. python import tensorflow as tf input = tf.zeros1, 1, 1, dtype=tf.int32 seqlengths = tf.constant0, shape=1, dtype=tf.int32 tf.rawops.ReverseSequence input=input,...

GHSA-828X-QC2P-WPRQ Undefined behavior in `MaxPool3DGradGrad`

Impact The implementation of tf.rawops.MaxPool3DGradGrad exhibits undefined behavior by dereferencing null pointers backing attacker-supplied empty tensors: python import tensorflow as tf originput = tf.constant0.0, shape=1, 1, 1, 1, 1, dtype=tf.float32 origoutput = tf.constant0.0, shape=1, 1, 1,...