CVE-2021-29559

TensorFlow is an end-to-end open source platform for machine learning. An attacker can access data outside of bounds of heap allocated array in tf.rawops.UnicodeEncode. This is because the...

PYSEC-2021-638

TensorFlow is an end-to-end open source platform for machine learning. If the splits argument of RaggedBincount does not specify a valid SparseTensorhttps://www.tensorflow.org/apidocs/python/tf/sparse/SparseTensor, then an attacker can trigger a heap buffer overflow. This will cause a read from...

PYSEC-2021-149

TensorFlow is an end-to-end open source platform for machine learning. If the splits argument of RaggedBincount does not specify a valid SparseTensorhttps://www.tensorflow.org/apidocs/python/tf/sparse/SparseTensor, then an attacker can trigger a heap buffer overflow. This will cause a read from...

CVE-2021-29545

TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a denial of service via a CHECK-fail in converting sparse tensors to CSR Sparse matrices. This is because the...

CVE-2021-29512

TensorFlow is an end-to-end open source platform for machine learning. If the splits argument of RaggedBincount does not specify a valid SparseTensorhttps://www.tensorflow.org/apidocs/python/tf/sparse/SparseTensor, then an attacker can trigger a heap buffer overflow. This will cause a read from...

Arbitrary Code Execution

tensorlfow is vulnerable to arbitrary code execution. The SparseCountSparseOutput implementation does not validate that the input arguments form a valid sparse tensor, allowing an attacker to execute arbitrary code on the host OS by causing a shape mismatch that can result in accesses outside of...

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-2020-313

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-2020-312

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-2020-121

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-2020-120

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-2020-120

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-2020-277

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...

Information disclosure

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 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-2020-15198

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...

GHSA-QC53-44CJ-VFVX Denial of Service in Tensorflow

Impact 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 accessed as elements of a matrix:...

Heap buffer overflow in Tensorflow

Impact 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 in parallel:...