CVE-2020-15193

In Tensorflow before versions 2.2.1 and 2.3.1, the implementation of dlpack.todlpack can be made to use uninitialized memory resulting in further memory corruption. This is because the pybind11 glue code assumes that the argument is a tensor. However, there is nothing stopping users from passing ...

CVE-2020-15194

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...

CVE-2020-15191

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...

CVE-2020-15190

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...

CVE-2020-15196

In Tensorflow version 2.3.0, the SparseCountSparseOutput and RaggedCountSparseOutput implementations don't validate that the weights tensor has the same shape as the data. The check exists for DenseCountSparseOutput, where both tensors are fully specified. In the sparse and ragged count weights a...

CVE-2020-15197

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...

CVE-2020-15191

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...

CVE-2020-15193

In Tensorflow before versions 2.2.1 and 2.3.1, the implementation of dlpack.todlpack can be made to use uninitialized memory resulting in further memory corruption. This is because the pybind11 glue code assumes that the argument is a tensor. However, there is nothing stopping users from passing ...

CVE-2020-15195

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the implementation of SparseFillEmptyRowsGrad uses a double indexing pattern. It is possible for reverseindexmapi to be an index outside of bounds of gradvalues, thus resulting in a heap buffer overflow. The issue is patched in...

CVE-2020-15196

In Tensorflow version 2.3.0, the SparseCountSparseOutput and RaggedCountSparseOutput implementations don't validate that the weights tensor has the same shape as the data. The check exists for DenseCountSparseOutput, where both tensors are fully specified. In the sparse and ragged count weights a...

PYSEC-2020-116

In Tensorflow before versions 2.2.1 and 2.3.1, the implementation of dlpack.todlpack can be made to use uninitialized memory resulting in further memory corruption. This is because the pybind11 glue code assumes that the argument is a tensor. However, there is nothing stopping users from passing ...

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-2020-125

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-2020-316

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. Hence, the code is...

PYSEC-2020-133

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...

Design/Logic Flaw

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...

PYSEC-2020-129

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-2020-113

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...

Out-of-bounds

In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger writes outside of bounds of heap allocated buffers by inserting negative elements in the segment ids tensor. Users having access to segmentidsdata can alter outputindex and then write to outside of outputdata...

PYSEC-2020-326

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...