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IBM AIX 7.1, 7.2, 7.3, and VIOS 3.1 could allow a non-privileged local user to exploit a vulnerability in the AIX kernel to obtain root privileges. IBM X-Force ID: 230502.

Check Point ZoneAlarm before version 15.8.200.19118 allows a local actor to escalate privileges during the upgrade process.

Jenkins Benchmark Evaluator Plugin 1.0.1 and earlier does not perform a permission check in a method implementing form validation. This allows attackers with Overall/Read permission to connect to an attacker-specified URL and to check for the existence of directories, `.csv`, and `.ycsb` files on the Jenkins controller file system. Additionally, this form validation method does not require POST requests, resulting in a cross-site request forgery (CSRF) vulnerability.

IBM Spectrum Protect Plus Container Backup and Restore (10.1.5 through 10.1.10.2 for Kubernetes and 10.1.7 through 10.1.10.2 for Red Hat OpenShift) could allow a remote attacker to bypass IBM Spectrum Protect Plus role based access control restrictions, caused by improper disclosure of session information. By retrieving the logs of a container an attacker could exploit this vulnerability to bypass login security of the IBM Spectrum Protect Plus server and gain unauthorized access based on the permissions of the IBM Spectrum Protect Plus user to the vulnerable Spectrum Protect Plus server software. IBM X-Force ID: 225340.

### Impact The implementation of `Conv2DBackpropInput` requires `input_sizes` to be 4-dimensional. Otherwise, it gives a `CHECK` failure which can be used to trigger a denial of service attack: ```python import tensorflow as tf strides = [1, 1, 1, 1] padding = "SAME" use_cudnn_on_gpu = True explicit_paddings = [] data_format = "NHWC" dilations = [1, 1, 1, 1] input_sizes = tf.constant([65534,65534], shape=[2], dtype=tf.int32) filter = tf.constant(0.159749106, shape=[3,3,2,2], dtype=tf.float32) out_backprop = tf.constant(0, shape=[], dtype=tf.float32) tf.raw_ops.Conv2DBackpropInput(input_sizes=input_sizes, filter=filter, out_backprop=out_backprop, strides=strides, padding=padding, use_cudnn_on_gpu=use_cudnn_on_gpu, explicit_paddings=explicit_paddings, data_format=data_format, dilations=dilations) ``` ### Patches We have patched the issue in GitHub commit [50156d547b9a1da0144d7babe665cf690305b33c](https://github.com/tensorflow/tensorflow/commit/50156d547b9a1da0144d7babe665cf690305b33c)....

An information disclosure in the web interface of Brocade Fabric OS versions before Brocade Fabric OS v9.2.0 and v9.1.1c, could allow a remote unauthenticated attacker to get technical details about the web interface.

C-MOR Video Surveillance versions 5.2401 and 6.00PL01 stores sensitive information, such as credentials, in clear text.

C-MOR Video Surveillance version 5.2401 suffers from an improper access control privilege escalation vulnerability that allows for a lower privileged user to access administrative functions.

TensorFlow is an open source platform for machine learning. The implementation of SobolSampleOp is vulnerable to a denial of service via CHECK-failure (assertion failure) caused by assuming `input(0)`, `input(1)`, and `input(2)` to be scalar. This issue has been patched in GitHub commit c65c67f88ad770662e8f191269a907bf2b94b1bf. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

IBM QRadar Network Security 5.4.0 and 5.5.0 contains hard-coded credentials, such as a password or cryptographic key, which it uses for its own inbound authentication, outbound communication to external components, or encryption of internal data. IBM X-Force ID: 174337.