Bitnami package
tensorflow
pkg:bitnami/tensorflow
Vulnerabilities (423)
| CVE | Sev | CVSS | KEV | Affected versions | Fixed in | Published | Description |
|---|---|---|---|---|---|---|---|
| CVE-2021-29519 | Low | 2.5 | < 2.1.4 | 2.1.4 | May 14, 2021 | TensorFlow is an end-to-end open source platform for machine learning. The API of `tf.raw_ops.SparseCross` allows combinations which would result in a `CHECK`-failure and denial of service. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/3d782b7d4 | |
| CVE-2021-29518 | Low | 2.5 | < 2.1.4 | 2.1.4 | May 14, 2021 | TensorFlow is an end-to-end open source platform for machine learning. In eager mode (default in TF 2.0 and later), session operations are invalid. However, users could still call the raw ops associated with them and trigger a null pointer dereference. The implementation(https:// | |
| CVE-2021-29517 | Low | 2.5 | < 2.1.4 | 2.1.4 | May 14, 2021 | TensorFlow is an end-to-end open source platform for machine learning. A malicious user could trigger a division by 0 in `Conv3D` implementation. The implementation(https://github.com/tensorflow/tensorflow/blob/42033603003965bffac51ae171b51801565e002d/tensorflow/core/kernels/conv | |
| CVE-2021-29516 | Low | 2.5 | < 2.1.4 | 2.1.4 | May 14, 2021 | TensorFlow is an end-to-end open source platform for machine learning. Calling `tf.raw_ops.RaggedTensorToVariant` with arguments specifying an invalid ragged tensor results in a null pointer dereference. The implementation of `RaggedTensorToVariant` operations(https://github.com/ | |
| CVE-2021-29515 | Low | 2.5 | < 2.1.4 | 2.1.4 | May 14, 2021 | TensorFlow is an end-to-end open source platform for machine learning. The implementation of `MatrixDiag*` operations(https://github.com/tensorflow/tensorflow/blob/4c4f420e68f1cfaf8f4b6e8e3eb857e9e4c3ff33/tensorflow/core/kernels/linalg/matrix_diag_op.cc#L195-L197) does not valida | |
| CVE-2021-29514 | Low | 2.5 | >= 2.3.0, < 2.3.3 | 2.3.3 | May 14, 2021 | TensorFlow is an end-to-end open source platform for machine learning. If the `splits` argument of `RaggedBincount` does not specify a valid `SparseTensor`(https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor), then an attacker can trigger a heap buffer overflow. Thi | |
| CVE-2021-29513 | Low | 2.5 | < 2.1.4 | 2.1.4 | May 14, 2021 | TensorFlow is an end-to-end open source platform for machine learning. Calling TF operations with tensors of non-numeric types when the operations expect numeric tensors result in null pointer dereferences. The conversion from Python array to C++ array(https://github.com/tensorfl | |
| CVE-2021-29554 | Low | 2.5 | < 2.1.4 | 2.1.4 | May 14, 2021 | TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service via a FPE runtime error in `tf.raw_ops.DenseCountSparseOutput`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/efff014f3b2d8ef6141da3 | |
| CVE-2021-29512 | Low | 2.5 | >= 2.3.0, < 2.3.3 | 2.3.3 | May 14, 2021 | TensorFlow is an end-to-end open source platform for machine learning. If the `splits` argument of `RaggedBincount` does not specify a valid `SparseTensor`(https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor), then an attacker can trigger a heap buffer overflow. Thi | |
| CVE-2020-26270 | Med | 4.4 | < 1.15.5 | 1.15.5 | Dec 10, 2020 | In affected versions of TensorFlow running an LSTM/GRU model where the LSTM/GRU layer receives an input with zero-length results in a CHECK failure when using the CUDA backend. This can result in a query-of-death vulnerability, via denial of service, if users can control the inpu | |
| CVE-2020-26269 | Hig | 7.5 | >= 2.4.0-rc0, < 2.4.0 | 2.4.0 | Dec 10, 2020 | In TensorFlow release candidate versions 2.4.0rc*, the general implementation for matching filesystem paths to globbing pattern is vulnerable to an access out of bounds of the array holding the directories. There are multiple invariants and preconditions that are assumed by the p | |
| CVE-2020-26268 | Med | 4.4 | < 1.15.5 | 1.15.5 | Dec 10, 2020 | In affected versions of TensorFlow the tf.raw_ops.ImmutableConst operation returns a constant tensor created from a memory mapped file which is assumed immutable. However, if the type of the tensor is not an integral type, the operation crashes the Python interpreter as it tries | |
| CVE-2020-26267 | Med | 4.4 | < 1.15.5 | 1.15.5 | Dec 10, 2020 | In affected versions of TensorFlow the tf.raw_ops.DataFormatVecPermute API does not validate the src_format and dst_format attributes. The code assumes that these two arguments define a permutation of NHWC. This can result in uninitialized memory accesses, read outside of bounds | |
| CVE-2020-26266 | Med | 4.4 | < 1.15.5 | 1.15.5 | Dec 10, 2020 | In affected versions of TensorFlow under certain cases a saved model can trigger use of uninitialized values during code execution. This is caused by having tensor buffers be filled with the default value of the type but forgetting to default initialize the quantized floating poi | |
| CVE-2020-26271 | Med | 4.4 | < 1.15.5 | 1.15.5 | Dec 10, 2020 | In affected versions of TensorFlow under certain cases, loading a saved model can result in accessing uninitialized memory while building the computation graph. The MakeEdge function creates an edge between one output tensor of the src node (given by output_index) and the input s | |
| CVE-2020-15266 | Low | 3.7 | < 2.4.0 | 2.4.0 | Oct 21, 2020 | In Tensorflow before version 2.4.0, when the `boxes` argument of `tf.image.crop_and_resize` has a very large value, the CPU kernel implementation receives it as a C++ `nan` floating point value. Attempting to operate on this is undefined behavior which later produces a segmentati | |
| CVE-2020-15265 | Med | 5.9 | < 2.4.0 | 2.4.0 | Oct 21, 2020 | In Tensorflow before version 2.4.0, an attacker can pass an invalid `axis` value to `tf.quantization.quantize_and_dequantize`. This results in accessing a dimension outside the rank of the input tensor in the C++ kernel implementation. However, dim_size only does a DCHECK to vali | |
| CVE-2020-15214 | Hig | 8.1 | >= 2.2.0, < 2.2.1 | 2.2.1 | Sep 25, 2020 | In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger a write out bounds / segmentation fault if the segment ids are not sorted. Code assumes that the segment ids are in increasing order, using the last element of the tensor holding them to dete | |
| CVE-2020-15213 | Med | 4.0 | >= 2.2.0, < 2.2.1 | 2.2.1 | Sep 25, 2020 | In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger a denial of service by causing an out of memory allocation in the implementation of segment sum. Since code uses the last element of the tensor holding them to determine the dimensionality of | |
| CVE-2020-15212 | Hig | 8.1 | >= 2.2.0, < 2.2.1 | 2.2.1 | Sep 25, 2020 | 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 `segment_ids_data` can alter `output_index` and then write |
- affected < 2.1.4fixed 2.1.4
TensorFlow is an end-to-end open source platform for machine learning. The API of `tf.raw_ops.SparseCross` allows combinations which would result in a `CHECK`-failure and denial of service. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/3d782b7d4
- affected < 2.1.4fixed 2.1.4
TensorFlow is an end-to-end open source platform for machine learning. In eager mode (default in TF 2.0 and later), session operations are invalid. However, users could still call the raw ops associated with them and trigger a null pointer dereference. The implementation(https://
- affected < 2.1.4fixed 2.1.4
TensorFlow is an end-to-end open source platform for machine learning. A malicious user could trigger a division by 0 in `Conv3D` implementation. The implementation(https://github.com/tensorflow/tensorflow/blob/42033603003965bffac51ae171b51801565e002d/tensorflow/core/kernels/conv
- affected < 2.1.4fixed 2.1.4
TensorFlow is an end-to-end open source platform for machine learning. Calling `tf.raw_ops.RaggedTensorToVariant` with arguments specifying an invalid ragged tensor results in a null pointer dereference. The implementation of `RaggedTensorToVariant` operations(https://github.com/
- affected < 2.1.4fixed 2.1.4
TensorFlow is an end-to-end open source platform for machine learning. The implementation of `MatrixDiag*` operations(https://github.com/tensorflow/tensorflow/blob/4c4f420e68f1cfaf8f4b6e8e3eb857e9e4c3ff33/tensorflow/core/kernels/linalg/matrix_diag_op.cc#L195-L197) does not valida
- affected >= 2.3.0, < 2.3.3fixed 2.3.3
TensorFlow is an end-to-end open source platform for machine learning. If the `splits` argument of `RaggedBincount` does not specify a valid `SparseTensor`(https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor), then an attacker can trigger a heap buffer overflow. Thi
- affected < 2.1.4fixed 2.1.4
TensorFlow is an end-to-end open source platform for machine learning. Calling TF operations with tensors of non-numeric types when the operations expect numeric tensors result in null pointer dereferences. The conversion from Python array to C++ array(https://github.com/tensorfl
- affected < 2.1.4fixed 2.1.4
TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service via a FPE runtime error in `tf.raw_ops.DenseCountSparseOutput`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/efff014f3b2d8ef6141da3
- affected >= 2.3.0, < 2.3.3fixed 2.3.3
TensorFlow is an end-to-end open source platform for machine learning. If the `splits` argument of `RaggedBincount` does not specify a valid `SparseTensor`(https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor), then an attacker can trigger a heap buffer overflow. Thi
- affected < 1.15.5fixed 1.15.5
In affected versions of TensorFlow running an LSTM/GRU model where the LSTM/GRU layer receives an input with zero-length results in a CHECK failure when using the CUDA backend. This can result in a query-of-death vulnerability, via denial of service, if users can control the inpu
- affected >= 2.4.0-rc0, < 2.4.0fixed 2.4.0
In TensorFlow release candidate versions 2.4.0rc*, the general implementation for matching filesystem paths to globbing pattern is vulnerable to an access out of bounds of the array holding the directories. There are multiple invariants and preconditions that are assumed by the p
- affected < 1.15.5fixed 1.15.5
In affected versions of TensorFlow the tf.raw_ops.ImmutableConst operation returns a constant tensor created from a memory mapped file which is assumed immutable. However, if the type of the tensor is not an integral type, the operation crashes the Python interpreter as it tries
- affected < 1.15.5fixed 1.15.5
In affected versions of TensorFlow the tf.raw_ops.DataFormatVecPermute API does not validate the src_format and dst_format attributes. The code assumes that these two arguments define a permutation of NHWC. This can result in uninitialized memory accesses, read outside of bounds
- affected < 1.15.5fixed 1.15.5
In affected versions of TensorFlow under certain cases a saved model can trigger use of uninitialized values during code execution. This is caused by having tensor buffers be filled with the default value of the type but forgetting to default initialize the quantized floating poi
- affected < 1.15.5fixed 1.15.5
In affected versions of TensorFlow under certain cases, loading a saved model can result in accessing uninitialized memory while building the computation graph. The MakeEdge function creates an edge between one output tensor of the src node (given by output_index) and the input s
- affected < 2.4.0fixed 2.4.0
In Tensorflow before version 2.4.0, when the `boxes` argument of `tf.image.crop_and_resize` has a very large value, the CPU kernel implementation receives it as a C++ `nan` floating point value. Attempting to operate on this is undefined behavior which later produces a segmentati
- affected < 2.4.0fixed 2.4.0
In Tensorflow before version 2.4.0, an attacker can pass an invalid `axis` value to `tf.quantization.quantize_and_dequantize`. This results in accessing a dimension outside the rank of the input tensor in the C++ kernel implementation. However, dim_size only does a DCHECK to vali
- affected >= 2.2.0, < 2.2.1fixed 2.2.1
In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger a write out bounds / segmentation fault if the segment ids are not sorted. Code assumes that the segment ids are in increasing order, using the last element of the tensor holding them to dete
- affected >= 2.2.0, < 2.2.1fixed 2.2.1
In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger a denial of service by causing an out of memory allocation in the implementation of segment sum. Since code uses the last element of the tensor holding them to determine the dimensionality of
- affected >= 2.2.0, < 2.2.1fixed 2.2.1
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 `segment_ids_data` can alter `output_index` and then write
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