CVE-2020-15194 Denial of Service in Tensorflow

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-2020-15195

TensorFlow vulnerability CVE-2020-15195: SparseFillEmptyRowsGrad uses a double indexing pattern where reverse_index_map(i) can reference grad_values out of bounds, causing a heap-based buffer overflow. Affected releases include 1.15.4, 2.0.3, 2.1.2, 2.2.1, and 2.3.1. A fix was committed (390611e0...

CVE-2020-15195 Heap buffer overflow in Tensorflow

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-2020-15195

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 Heap buffer overflow in Tensorflow

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-2020-15196

CVE-2020-15196 affects TensorFlow 2.3.0: SparseCountSparseOutput and RaggedCountSparseOutput do not validate that the weights tensor has the same shape as the data, allowing reads beyond the weights buffer when fewer weights are provided. This heap-based overflow is mitigated in TensorFlow 2.3.1 ...

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 Denial of Service in Tensorflow

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-2020-15197

TensorFlow prior to 2.3.1 is affected by CVE-2020-15197 due to a validation gap in SparseCountSparseOutput: the indices tensor is not checked to be rank 2, though code treats it as a matrix. This can allow crafted input sparse tensors to cause a CHECK failure and crash, enabling denial of service...

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-2020-15198 Heap buffer overflow in Tensorflow

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...

CVE-2020-15198

CVE-2020-15198 affects TensorFlow up to 2.3.0: SparseCountSparseOutput may access heap buffers out of bounds due to missing validation that indices and values shapes match in a sparse tensor. This root cause enables a heap buffer overflow in pre-2.3.1 builds. A fix was committed (3cbb917b47147660...

CVE-2020-15198

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...

CVE-2020-15199 Denial of Service in Tensorflow

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...

CVE-2020-15199

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...

CVE-2020-15199

Summary: TensorFlow prior to 2.3.1 contains a bug in RaggedCountSparseOutput where input ragged tensors are not validated for proper splits; an empty or single-element splits can trigger a SIGABRT due to an initialization bound. Root cause: lack of validation in RaggedCountSparseOutput when formi...

CVE-2020-15200

CVE-2020-15200 affects TensorFlow before 2.3.1. The RaggedCountSparseOutput path does not validate that the input ragged tensor is well-formed, specifically not validating that the splits form a valid partition of values. This can set up conditions that lead to a heap-based buffer overflow and, i...

CVE-2020-15200 Segfault in Tensorflow

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 ...

CVE-2020-15200

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 ...

CVE-2020-15190

TensorFlow CVE-2020-15190 is a vulnerability in tf.raw_ops.Switch where, in eager mode, the runtime binds a reference to a nullptr when one of the two outputs is undefined. This causes undefined behavior and can segfault when compiled with -fsanitize=null. The issue affects TensorFlow versions 1....