Integer overflow

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...

Null pointer dereference

In eager mode, TensorFlow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1 does not set the session state. Hence, calling tf.rawops.GetSessionHandle or tf.rawops.GetSessionHandleV2 results in a null pointer dereference In linked snippet, in eager mode, ctx-sessionstate returns nullptr. Since...

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-2020-120

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-2020-127

In eager mode, TensorFlow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1 does not set the session state. Hence, calling tf.rawops.GetSessionHandle or tf.rawops.GetSessionHandleV2 results in a null pointer dereference In linked snippet, in eager mode, ctx-sessionstate returns nullptr. Since...

PYSEC-2020-277

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-2020-284

In eager mode, TensorFlow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1 does not set the session state. Hence, calling tf.rawops.GetSessionHandle or tf.rawops.GetSessionHandleV2 results in a null pointer dereference In linked snippet, in eager mode, ctx-sessionstate returns nullptr. Since...

PYSEC-2020-305

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...

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-2020-314

In Tensorflow before version 2.3.1, the RaggedCountSparseOutput does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the splits tensor has the minimum required number of elements. Code uses this quantity to initialize a different data...

Out-of-bounds

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...

Memory corruption

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...

Out-of-bounds

In TensorFlow Lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, saved models in the flatbuffer format use a double indexing scheme: a model has a set of subgraphs, each subgraph has a set of operators and each operator has a set of input/output tensors. The flatbuffer format uses indice...

Memory corruption

In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger a write out bounds / segmentation fault if the segment ids are not sorted. Code assumes that the segment ids are in increasing order, using the last element of the tensor holding them to determine the...

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-2020-131

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-2020-136

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-2020-286

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...

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-2020-290

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...