Denial Of Service (DoS)

tensorflow is vulnerable to denial of service. The vulnerability exists due to the lack of validation of the value of axis and an out-of-bound access allowing an attacker to crash the system via the implementation of Dequantize...

CVE-2022-21726

Tensorflow is an Open Source Machine Learning Framework. The implementation of Dequantize does not fully validate the value of axis and can result in heap OOB accesses. The axis argument can be -1 the default value for the optional argument or any other positive value at most the number of...

Integer overflow

Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for Dequantize is vulnerable to an integer overflow weakness. The axis argument can be -1 the default value for the optional argument or any other positive value at most the number of dimensions of the...

PYSEC-2022-106

Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for Dequantize is vulnerable to an integer overflow weakness. The axis argument can be -1 the default value for the optional argument or any other positive value at most the number of dimensions of the...

PYSEC-2022-105

Tensorflow is an Open Source Machine Learning Framework. The implementation of Dequantize does not fully validate the value of axis and can result in heap OOB accesses. The axis argument can be -1 the default value for the optional argument or any other positive value at most the number of...

PYSEC-2022-50

Tensorflow is an Open Source Machine Learning Framework. The implementation of Dequantize does not fully validate the value of axis and can result in heap OOB accesses. The axis argument can be -1 the default value for the optional argument or any other positive value at most the number of...

PYSEC-2022-51

Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for Dequantize is vulnerable to an integer overflow weakness. The axis argument can be -1 the default value for the optional argument or any other positive value at most the number of dimensions of the...

PYSEC-2022-50

Tensorflow is an Open Source Machine Learning Framework. The implementation of Dequantize does not fully validate the value of axis and can result in heap OOB accesses. The axis argument can be -1 the default value for the optional argument or any other positive value at most the number of...

PYSEC-2022-51

Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for Dequantize is vulnerable to an integer overflow weakness. The axis argument can be -1 the default value for the optional argument or any other positive value at most the number of dimensions of the...

PYSEC-2022-105

Tensorflow is an Open Source Machine Learning Framework. The implementation of Dequantize does not fully validate the value of axis and can result in heap OOB accesses. The axis argument can be -1 the default value for the optional argument or any other positive value at most the number of...

PYSEC-2022-106

Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for Dequantize is vulnerable to an integer overflow weakness. The axis argument can be -1 the default value for the optional argument or any other positive value at most the number of dimensions of the...

Design/Logic Flaw

Tensorflow is an Open Source Machine Learning Framework. The implementation of Dequantize does not fully validate the value of axis and can result in heap OOB accesses. The axis argument can be -1 the default value for the optional argument or any other positive value at most the number of...

CVE-2022-21727

Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for Dequantize is vulnerable to an integer overflow weakness. The axis argument can be -1 the default value for the optional argument or any other positive value at most the number of dimensions of the...

CVE-2022-21727 Integer overflow in Tensorflow

Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for Dequantize is vulnerable to an integer overflow weakness. The axis argument can be -1 the default value for the optional argument or any other positive value at most the number of dimensions of the...

CVE-2022-21726

Tensorflow is an Open Source Machine Learning Framework. The implementation of Dequantize does not fully validate the value of axis and can result in heap OOB accesses. The axis argument can be -1 the default value for the optional argument or any other positive value at most the number of...

CVE-2022-21726 Out of bounds read in Tensorflow

Tensorflow is an Open Source Machine Learning Framework. The implementation of Dequantize does not fully validate the value of axis and can result in heap OOB accesses. The axis argument can be -1 the default value for the optional argument or any other positive value at most the number of...

CVE-2022-21726 Out of bounds read in Tensorflow

Tensorflow is an Open Source Machine Learning Framework. The implementation of Dequantize does not fully validate the value of axis and can result in heap OOB accesses. The axis argument can be -1 the default value for the optional argument or any other positive value at most the number of...

CVE-2022-21726

TensorFlow CVE-2022-21726 affects the Dequantize path, where axis validation is insufficient and can cause heap-out-of-bounds reads. The issue arises when axis is -1 (default) or any large positive value not checked against input dimensions, reading past the dimensions array. A fix is planned for...

Google TensorFlow 缓冲区错误漏洞

Google TensorFlow is an end-to-end open source platform for machine learning from Google Google. Google Tensorflow has a buffer overflow vulnerability that stems from the fact that Dequantize's implementation does not fully validate the value of axis, which can be exploited by an attacker to caus...

PT-2022-15066 · Google · Tensorflow

Name of the Vulnerable Software and Affected Versions: TensorFlow versions prior to 2.8.0 TensorFlow versions 2.7.1 and earlier TensorFlow versions 2.6.3 and earlier TensorFlow versions 2.5.3 and earlier Description: The implementation of shape inference for Dequantize is vulnerable to an integer...