Vulnerabilities
Vulnerable Software
Google:  >> Tensorflow  Security Vulnerabilities
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 `tf.raw_ops.SparseConcat`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/b432a38fe0e1b4b904a6c222cbce794c39703e87/tensorflow/core/kernels/sparse_concat_op.cc#L76) takes the values specified in `shapes[0]` as dimensions for the output shape. The `TensorShape` constructor(https://github.com/tensorflow/tensorflow/blob/6f9896890c4c703ae0a0845394086e2e1e523299/tensorflow/core/framework/tensor_shape.cc#L183-L188) uses a `CHECK` operation which triggers when `InitDims`(https://github.com/tensorflow/tensorflow/blob/6f9896890c4c703ae0a0845394086e2e1e523299/tensorflow/core/framework/tensor_shape.cc#L212-L296) returns a non-OK status. This is a legacy implementation of the constructor and operations should use `BuildTensorShapeBase` or `AddDimWithStatus` to prevent `CHECK`-failures in the presence of overflows. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
CVSS Score
2.5
EPSS Score
0.0
Published
2021-05-14
TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a heap buffer overflow in `QuantizedMul` by passing in invalid thresholds for the quantization. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/87cf4d3ea9949051e50ca3f071fc909538a51cd0/tensorflow/core/kernels/quantized_mul_op.cc#L287-L290) assumes that the 4 arguments are always valid scalars and tries to access the numeric value directly. However, if any of these tensors is empty, then `.flat<T>()` is an empty buffer and accessing the element at position 0 results in overflow. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
CVSS Score
2.5
EPSS Score
0.0
Published
2021-05-14
TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a heap buffer overflow in `QuantizedReshape` by passing in invalid thresholds for the quantization. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/a324ac84e573fba362a5e53d4e74d5de6729933e/tensorflow/core/kernels/quantized_reshape_op.cc#L38-L55) assumes that the 2 arguments are always valid scalars and tries to access the numeric value directly. However, if any of these tensors is empty, then `.flat<T>()` is an empty buffer and accessing the element at position 0 results in overflow. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
CVSS Score
2.5
EPSS Score
0.0
Published
2021-05-14
TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a heap buffer overflow in `QuantizedResizeBilinear` by passing in invalid thresholds for the quantization. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/50711818d2e61ccce012591eeb4fdf93a8496726/tensorflow/core/kernels/quantized_resize_bilinear_op.cc#L705-L706) assumes that the 2 arguments are always valid scalars and tries to access the numeric value directly. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
CVSS Score
2.5
EPSS Score
0.0
Published
2021-05-14
TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a division by zero to occur in `Conv2DBackpropFilter`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/1b0296c3b8dd9bd948f924aa8cd62f87dbb7c3da/tensorflow/core/kernels/conv_grad_filter_ops.cc#L513-L522) computes a divisor based on user provided data (i.e., the shape of the tensors given as arguments). If all shapes are empty then `work_unit_size` is 0. Since there is no check for this case before division, this results in a runtime exception, with potential to be abused for a denial of service. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
CVSS Score
2.5
EPSS Score
0.0
Published
2021-05-14
TensorFlow is an end-to-end open source platform for machine learning. Calling `tf.raw_ops.ImmutableConst`(https://www.tensorflow.org/api_docs/python/tf/raw_ops/ImmutableConst) with a `dtype` of `tf.resource` or `tf.variant` results in a segfault in the implementation as code assumes that the tensor contents are pure scalars. We have patched the issue in 4f663d4b8f0bec1b48da6fa091a7d29609980fa4 and will release TensorFlow 2.5.0 containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved. If using `tf.raw_ops.ImmutableConst` in code, you can prevent the segfault by inserting a filter for the `dtype` argument.
CVSS Score
2.5
EPSS Score
0.0
Published
2021-05-14
TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a heap buffer overflow to occur in `Conv2DBackpropFilter`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/1b0296c3b8dd9bd948f924aa8cd62f87dbb7c3da/tensorflow/core/kernels/conv_grad_filter_ops.cc#L495-L497) computes the size of the filter tensor but does not validate that it matches the number of elements in `filter_sizes`. Later, when reading/writing to this buffer, code uses the value computed here, instead of the number of elements in the tensor. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
CVSS Score
2.5
EPSS Score
0.0
Published
2021-05-14
TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a dereference of a null pointer in `tf.raw_ops.StringNGrams`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/1cdd4da14282210cc759e468d9781741ac7d01bf/tensorflow/core/kernels/string_ngrams_op.cc#L67-L74) does not fully validate the `data_splits` argument. This would result in `ngrams_data`(https://github.com/tensorflow/tensorflow/blob/1cdd4da14282210cc759e468d9781741ac7d01bf/tensorflow/core/kernels/string_ngrams_op.cc#L106-L110) to be a null pointer when the output would be computed to have 0 or negative size. Later writes to the output tensor would then cause a null pointer dereference. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
CVSS Score
2.5
EPSS Score
0.0
Published
2021-05-14
TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a heap buffer overflow by passing crafted inputs to `tf.raw_ops.StringNGrams`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/1cdd4da14282210cc759e468d9781741ac7d01bf/tensorflow/core/kernels/string_ngrams_op.cc#L171-L185) fails to consider corner cases where input would be split in such a way that the generated tokens should only contain padding elements. If input is such that `num_tokens` is 0, then, for `data_start_index=0` (when left padding is present), the marked line would result in reading `data[-1]`. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
CVSS Score
2.5
EPSS Score
0.0
Published
2021-05-14
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 `tf.raw_ops.CTCGreedyDecoder`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/1615440b17b364b875eb06f43d087381f1460a65/tensorflow/core/kernels/ctc_decoder_ops.cc#L37-L50) has a `CHECK_LT` inserted to validate some invariants. When this condition is false, the program aborts, instead of returning a valid error to the user. This abnormal termination can be weaponized in denial of service attacks. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
CVSS Score
2.5
EPSS Score
0.0
Published
2021-05-14


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