PYSEC-2020-114

In Tensorflow before versions 2.2.1 and 2.3.1, if a user passes an invalid argument to dlpack.todlpack the expected validations will cause variables to bind to nullptr while setting a status variable to the error condition. However, this status argument is not properly checked. Hence, code...

PYSEC-2020-128

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the datasplits argument of tf.rawops.StringNGrams lacks validation. This allows a user to pass values that can cause heap overflow errors and even leak contents of memory In the linked code snippet, all the binary strings after ...

PYSEC-2020-293

In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger a denial of service by causing an out of memory allocation in the implementation of segment sum. Since code uses the last element of the tensor holding them to determine the dimensionality of output tensor,...

PYSEC-2020-324

In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, a crafted TFLite model can force a node to have as input a tensor backed by a nullptr buffer. This can be achieved by changing a buffer index in the flatbuffer serialization to convert a read-only tensor to a read-write one...

PYSEC-2020-126

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, by controlling the fill argument of tf.strings.asstring, a malicious attacker is able to trigger a format string vulnerability due to the way the internal format use in a printf call is constructed. This may result in segmentati...

PYSEC-2020-280

In Tensorflow before version 2.3.1, the RaggedCountSparseOutput implementation does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the values in the splits tensor generate a valid partitioning of the values tensor. Thus, the code sets ...

PYSEC-2020-121

In Tensorflow before version 2.3.1, the SparseCountSparseOutput implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the indices tensor has the same shape as the values one. The values in these tensors are always accessed...

PYSEC-2020-283

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, by controlling the fill argument of tf.strings.asstring, a malicious attacker is able to trigger a format string vulnerability due to the way the internal format use in a printf call is constructed. This may result in segmentati...

PYSEC-2020-321

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, changing the TensorFlow's SavedModel protocol buffer and altering the name of required keys results in segfaults and data corruption while loading the model. This can cause a denial of service in products using tensorflow-servin...

Null pointer dereference

In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, a crafted TFLite model can force a node to have as input a tensor backed by a nullptr buffer. This can be achieved by changing a buffer index in the flatbuffer serialization to convert a read-only tensor to a read-write one...

PYSEC-2020-120

In Tensorflow before version 2.3.1, the SparseCountSparseOutput implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the indices tensor has rank 2. This tensor must be a matrix because code assumes its elements are access...

PYSEC-2020-309

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the SparseFillEmptyRowsGrad implementation has incomplete validation of the shapes of its arguments. Although reverseindexmapt and gradvaluest are accessed in a similar pattern, only reverseindexmapt is validated to be of proper...

PYSEC-2020-117

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the SparseFillEmptyRowsGrad implementation has incomplete validation of the shapes of its arguments. Although reverseindexmapt and gradvaluest are accessed in a similar pattern, only reverseindexmapt is validated to be of proper...

PYSEC-2020-278

In Tensorflow before version 2.3.1, the SparseCountSparseOutput implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the indices tensor has the same shape as the values one. The values in these tensors are always accessed...

PYSEC-2020-288

In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, when determining the common dimension size of two tensors, TFLite uses a DCHECK which is no-op outside of debug compilation modes. Since the function always returns the dimension of the first tensor, malicious attackers can...

PYSEC-2020-282

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the Shard API in TensorFlow expects the last argument to be a function taking two int64 i.e., long long arguments. However, there are several places in TensorFlow where a lambda taking int or int32 arguments is being used. In...

PYSEC-2020-272

In Tensorflow before versions 2.2.1 and 2.3.1, if a user passes a list of strings to dlpack.todlpack there is a memory leak following an expected validation failure. The issue occurs because the status argument during validation failures is not properly checked. Since each of the above methods ca...

PYSEC-2020-325

In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, if a TFLite saved model uses the same tensor as both input and output of an operator, then, depending on the operator, we can observe a segmentation fault or just memory corruption. We have patched the issue in d58c96946b a...

PYSEC-2020-115

In Tensorflow before versions 2.2.1 and 2.3.1, if a user passes a list of strings to dlpack.todlpack there is a memory leak following an expected validation failure. The issue occurs because the status argument during validation failures is not properly checked. Since each of the above methods ca...

PYSEC-2020-113

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the tf.rawops.Switch operation takes as input a tensor and a boolean and outputs two tensors. Depending on the boolean value, one of the tensors is exactly the input tensor whereas the other one should be an empty tensor. Howeve...