1208 matches found
USN-4692-1 tar vulnerabilities
Chris Siebenmann discovered that tar incorrectly handled extracting files resized during extraction when invoked with the --sparse flag. An attacker could possibly use this issue to cause a denial of service. This issue only affected Ubuntu 12.04 ESM, Ubuntu 14.04 ESM, Ubuntu 16.04 LTS and Ubuntu...
SUSE SLES12 Security Update : tar (SUSE-SU-2020:2806-1)
This update for tar fixes the following issues : Security issues fixed : CVE-2019-9923: Fixed a denial of service while parsing certain archives with malformed extended headers in paxdecodeheader bsc1130496. CVE-2018-20482: Fixed a denial of service when the '--sparse' option mishandles file...
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...
Tensorflow Data Validation Vulnerability
Google TensorFlow is a suite of end-to-end open source platforms for machine learning from Google USA. A security vulnerability exists in Tensorflow version 2.3.0 that stems from the inability of the SparseCountSparseOutput and RaggedCountSparseOutput implementations to verify that the weights...
Google TensorFlow Buffer Overflow Vulnerability (CNVD-2020-54782)
Google TensorFlow is a suite of end-to-end open source platforms for machine learning from Google USA. A security vulnerability exists in Tensorflow SparseFillEmptyRowsGrad versions prior to 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1, and 2.3.1, which arises from a networked system or product that perfor...
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...
PYSEC-2020-276
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-2020-122
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-2020-274
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-2020-312
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-2020-309
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-2020-120
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-2020-119
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-2020-121
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-2020-122
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-2020-311
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-2020-313
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-2020-124
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-2020-311
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...