Google TensorFlow buffer overflow vulnerability (CNVD-2022-11509)

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...

CVE-2022-23410

AXIS IP Utility before 4.18.0 allows for remote code execution and local privilege escalation by the means of DLL hijacking. IPUtility.exe would attempt to load DLLs from its current working directory which could allow for remote code execution if a compromised DLL would be placed in the same...

CVE-2022-23410

AXIS IP Utility before 4.18.0 allows for remote code execution and local privilege escalation by the means of DLL hijacking. IPUtility.exe would attempt to load DLLs from its current working directory which could allow for remote code execution if a compromised DLL would be placed in the same...

CVE-2022-23410

AXIS IP Utility before 4.18.0 allows for remote code execution and local privilege escalation by the means of DLL hijacking. IPUtility.exe would attempt to load DLLs from its current working directory which could allow for remote code execution if a compromised DLL would be placed in the same...

Remote code execution

AXIS IP Utility before 4.18.0 allows for remote code execution and local privilege escalation by the means of DLL hijacking. IPUtility.exe would attempt to load DLLs from its current working directory which could allow for remote code execution if a compromised DLL would be placed in the same...

CVE-2022-23410

AXIS IP Utility prior to 4.18.0 is affected by a DLL hijacking issue that enables remote code execution and local privilege escalation. IPUtility.exe loads DLLs from its current working directory, so placing a compromised DLL in that folder could trigger exploitation. Affected version range: befo...

CVE-2022-23410

AXIS IP Utility before 4.18.0 allows for remote code execution and local privilege escalation by the means of DLL hijacking. IPUtility.exe would attempt to load DLLs from its current working directory which could allow for remote code execution if a compromised DLL would be placed in the same...

PT-2022-15982 · Axis · Axis Ip Utility

Name of the Vulnerable Software and Affected Versions: AXIS IP Utility versions prior to 4.18.0 Description: The issue allows for remote code execution and local privilege escalation through DLL hijacking. IPUtility.exe attempts to load DLLs from its current working directory, which could allow f...

AXIS IP Utility 代码问题漏洞

Axis Ip Utility is used by Axis of Sweden to help set the Ip address of Axis network video products. AXIS IP Utility has a code issue vulnerability that stems from AXIS IP Utility allowing remote code execution and local privilege escalation via DLL hijacking...

GHSA-43Q8-3FV7-PR5X Improper Validation of Integrity Check Value in TensorFlow

Impact The implementation of tf.sparse.split does not fully validate the input arguments. Hence, a malicious user can trigger a denial of service via a segfault or a heap OOB read: python import tensorflow as tf data = tf.random.uniform1, 32, 32, dtype=tf.float32 axis = 1, 2 x =...

GHSA-C6FH-56W7-FVJW Integer overflow in Tensorflow

Impact The implementation of shape inference for Dequantize is vulnerable to an integer overflow weakness: python import tensorflow as tf input = tf.constant1,1,dtype=tf.qint32 @tf.function def test: y = tf.rawops.Dequantize input=input, minrange=1.0, maxrange=10.0, mode='MINCOMBINED',...

Out of bounds read in Tensorflow

Impact The implementation of Dequantize does not fully validate the value of axis and can result in heap OOB accesses: python import tensorflow as tf @tf.function def test: y = tf.rawops.Dequantize input=tf.constant1,1,dtype=tf.qint32, minrange=1.0, maxrange=10.0, mode='MINCOMBINED',...

GHSA-23HM-7W47-XW72 Out of bounds read in Tensorflow

Impact The implementation of Dequantize does not fully validate the value of axis and can result in heap OOB accesses: python import tensorflow as tf @tf.function def test: y = tf.rawops.Dequantize input=tf.constant1,1,dtype=tf.qint32, minrange=1.0, maxrange=10.0, mode='MINCOMBINED',...

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...

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...

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-2022-50

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-2022-105

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-2022-51

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...