PYSEC-2020-138

In Tensorflow before version 2.4.0, an attacker can pass an invalid axis value to tf.quantization.quantizeanddequantize. This results in accessing a dimension outside the rank of the input tensor in the C++ kernel implementation. However, dimsize only does a DCHECK to validate the argument and th...

PYSEC-2020-331

In Tensorflow before version 2.4.0, when the boxes argument of tf.image.cropandresize 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 segmentation fault. The issue is...

PYSEC-2020-138

In Tensorflow before version 2.4.0, an attacker can pass an invalid axis value to tf.quantization.quantizeanddequantize. This results in accessing a dimension outside the rank of the input tensor in the C++ kernel implementation. However, dimsize only does a DCHECK to validate the argument and th...

PYSEC-2020-330

In Tensorflow before version 2.4.0, an attacker can pass an invalid axis value to tf.quantization.quantizeanddequantize. This results in accessing a dimension outside the rank of the input tensor in the C++ kernel implementation. However, dimsize only does a DCHECK to validate the argument and th...

PYSEC-2020-331

In Tensorflow before version 2.4.0, when the boxes argument of tf.image.cropandresize 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 segmentation fault. The issue is...

PYSEC-2020-139

In Tensorflow before version 2.4.0, when the boxes argument of tf.image.cropandresize 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 segmentation fault. The issue is...

CVE-2020-15266

In Tensorflow before version 2.4.0, when the boxes argument of tf.image.cropandresize 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 segmentation fault. The issue is...

CVE-2020-15266

In TensorFlow, CVE-2020-15266 affects the tf.image.crop_and_resize path: when boxes contains a very large value in versions before 2.4.0, the CPU kernel reads it as a C++ NaN and causes undefined behavior leading to a segmentation fault. The issue is fixed in commit eccb7ec454e6617738554a255d77f0...

CVE-2020-15266 Undefined behavior in Tensorflow

In Tensorflow before version 2.4.0, when the boxes argument of tf.image.cropandresize 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 segmentation fault. The issue is...

CVE-2020-15265

TensorFlow before 2.4.0 is affected by CVE-2020-15265: passing an invalid axis to tf.quantization.quantize_and_dequantize can trigger a segfault due to a DCHECK in dim_size, potentially crashing the C++ kernel. The issue is patched in commit eccb7ec454e6617738554a255d77f08e60ee0808 and TensorFlow...

CVE-2020-15265

In Tensorflow before version 2.4.0, an attacker can pass an invalid axis value to tf.quantization.quantizeanddequantize. This results in accessing a dimension outside the rank of the input tensor in the C++ kernel implementation. However, dimsize only does a DCHECK to validate the argument and th...

CVE-2020-15265 Segfault in Tensorflow

In Tensorflow before version 2.4.0, an attacker can pass an invalid axis value to tf.quantization.quantizeanddequantize. This results in accessing a dimension outside the rank of the input tensor in the C++ kernel implementation. However, dimsize only does a DCHECK to validate the argument and th...

PT-2020-14325 · Google · Tensorflow

Name of the Vulnerable Software and Affected Versions: TensorFlow versions prior to 2.4.0 Description: The issue allows an attacker to pass an invalid axis value to tf.quantization.quantize and dequantize, resulting in accessing a dimension outside the rank of the input tensor in the C++ kernel...

PT-2020-14326 · Google · Tensorflow

Name of the Vulnerable Software and Affected Versions: TensorFlow versions prior to 2.4.0 Description: The issue arises when the boxes argument of tf.image.crop and resize has a very large value, causing the CPU kernel implementation to receive it as a C++ nan floating point value. This leads to...

Unspecified Vulnerability in Google Tensorflow SparseFillEmptyRowsGrad

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 stems from an incomplete validation of the shape of i...

Unspecified Vulnerability in Google Tensorflow (CNVD-2020-57075)

Google TensorFlow is a suite of end-to-end open source platforms for machine learning from Google USA. A security vulnerability exists in Tensorflow versions prior to 2.2.1, 2.3.1, which can be exploited by an attacker to cause memory leakage issues...

Denial Of Service (DoS)

tensorflow is vulnerable to denial of service. The RaggedCountSparseOutput implementation does not validate that the input arguments form a valid ragged tensor, allowing an attacker to exploit the vulnerability to cause an application crash via a segmentation fault from a heap-based buffer overfl...

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...

Denial Of Service (DoS)

tensorflow is vulnerable to denial of service. An attacker can force a node to have, as input, a tensor backed by a nullptr buffer via a malicious TFLite model, eventually converting the tensors to be one of read-write via a null pointer dereference...

Denial Of Service (DoS)

tensorflow is vulnerable to denial of service. Changing of the SavedModel protocol buffer and altering the name of required keys result in segfaults and data corruption while loading the model. This allows an attacker to cause a denial of service in products using the tensorflow-serving or other...