CVE-2021-29521 Segfault in SparseCountSparseOutput

TensorFlow is an end-to-end open source platform for machine learning. Specifying a negative dense shape in tf.rawops.SparseCountSparseOutput results in a segmentation fault being thrown out from the standard library as std::vector invariants are broken. This is because the...

CVE-2021-29619 Segfault in `tf.raw_ops.SparseCountSparseOutput`

TensorFlow is an end-to-end open source platform for machine learning. Passing invalid arguments e.g., discovered via fuzzing to tf.rawops.SparseCountSparseOutput results in segfault. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow...

CVE-2021-29619

TensorFlow is an end-to-end open source platform for machine learning. Passing invalid arguments e.g., discovered via fuzzing to tf.rawops.SparseCountSparseOutput results in segfault. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow...

Google TensorFlow 安全漏洞

Google TensorFlow is a suite of end-to-end open source platforms for machine learning from Google USA. A security vulnerability exists in TensorFlow 2.4.2,2.3.3,2.2.3,2.1.4, which stems from the fact that tf.rawops.SparseCountSparseOutput causes a segmentation error to be thrown from the standard...

PT-2021-18272 · Google · Tensorflow

Name of the Vulnerable Software and Affected Versions: TensorFlow versions prior to 2.5.0 TensorFlow versions 2.4.1 and earlier TensorFlow versions 2.3.2 and earlier Description: Specifying a negative dense shape in tf.raw ops.SparseCountSparseOutput results in a segmentation fault being thrown o...

Google TensorFlow 安全漏洞

Google TensorFlow is a suite of end-to-end open source platforms for machine learning from Google USA. Google TensorFlow suffers from an unspecified vulnerability that stems from passing invalid parameters to tf.rawops.SparseCountSparseOutput.No details of the vulnerability are provided at this...

Information Disclosure

tensorflow is vulnerable to information disclosure. Lack of validation of weights tensor against the data in the functions SparseCountSparseOutput and RaggedCountSparseOutput allows a user to pass fewer weights than the values for the tensors to read out of heap buffer boundary, potentially...

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-2020-15198

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-2020-15197

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-2020-15196

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-2020-15196

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-2020-277

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-2020-121

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...

Out-of-bounds

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-2020-119

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-2020-278

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...

Heap overflow

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...