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The webservices in Proofpoint Enterprise Protection (PPS/POD) contain a vulnerability that allows for an anonymous user to execute remote code through 'eval injection'. Exploitation requires network access to the webservices API, but such access is a non-standard configuration. This affects all versions 8.20.0 and below.

A flaw was found in Moodle in versions 3.11 to 3.11.3, 3.10 to 3.10.7, 3.9 to 3.9.10 and earlier unsupported versions. The "delete related badge" functionality did not include the necessary token check to prevent a CSRF risk.

A flaw was found in Moodle in versions 3.11 to 3.11.4, 3.10 to 3.10.8, 3.9 to 3.9.11 and earlier unsupported versions. The "delete badge alignment" functionality did not include the necessary token check to prevent a CSRF risk.

When connecting to Amazon Workspaces, the SHA256 presented by AWS connection provisioner is not fully verified by Zero Clients. The issue could be exploited by an adversary that places a MITM (Man in the Middle) between a zero client and AWS session provisioner in the network. This issue is only applicable when connecting to an Amazon Workspace from a PCoIP Zero Client.

### Impact Some resources are missing a check for inactive (not yet activated or disabled) users in XWiki, including the REST service: so a disabled user can enable themselves using a REST call. On the same way some resources handler created by extensions are not protected by default: so an inactive users could perform actions for such extensions. This issue exists since at least version 1.1 of XWiki for instance configured with the email activation required for new users. Now it's more critical for newer versions (>= 11.3RC1) since we provided the capability to disable user without deleting them, and we encouraged using that feature. ### Patches This issue has been patched in XWiki 14.3RC1 and XWiki 13.10.5. ### Workarounds There is no workaround for this other than upgrading XWiki. ### References * https://jira.xwiki.org/browse/XWIKI-19559 ### For more information If you have any questions or comments about this advisory: * Open an issue in [Jira XWiki.org](https://jira.x...

IBM Robotic Process Automation 21.0.0 through 21.0.7.8 could disclose sensitive information from access to RPA scripts, workflows and related data. IBM X-Force ID: 261606.

IBM Security Directory Suite VA 8.0.1 specifies permissions for a security-critical resource in a way that allows that resource to be read or modified by unintended actors. IBM X-Force ID: 228571.

### Impact The [`AvgPoolOp`](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/avgpooling_op.cc#L56-L98) function takes an argument `ksize` that must be positive but is not checked. A negative `ksize` can trigger a `CHECK` failure and crash the program. ```python import tensorflow as tf import numpy as np value = np.ones([1, 1, 1, 1]) ksize = [1, 1e20, 1, 1] strides = [1, 1, 1, 1] padding = 'SAME' data_format = 'NHWC' tf.raw_ops.AvgPool(value=value, ksize=ksize, strides=strides, padding=padding, data_format=data_format) ``` ### Patches We have patched the issue in GitHub commit [3a6ac52664c6c095aa2b114e742b0aa17fdce78f](https://github.com/tensorflow/tensorflow/commit/3a6ac52664c6c095aa2b114e742b0aa17fdce78f). 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. ### For more ...

### Impact When `DrawBoundingBoxes` receives an input `boxes` that is not of dtype `float`, it gives a `CHECK` fail that can trigger a denial of service attack. ```python import tensorflow as tf import numpy as np arg_0=tf.constant(value=np.random.random(size=(1, 3, 2, 3)), shape=(1, 3, 2, 3), dtype=tf.half) arg_1=tf.constant(value=np.random.random(size=(1, 2, 4)), shape=(1, 2, 4), dtype=tf.float32) arg_2='' tf.raw_ops.DrawBoundingBoxes(images=arg_0, boxes=arg_1, name=arg_2) ``` ### Patches We have patched the issue in GitHub commit [da0d65cdc1270038e72157ba35bf74b85d9bda11](https://github.com/tensorflow/tensorflow/commit/da0d65cdc1270038e72157ba35bf74b85d9bda11). 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. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY...

### Impact When `RandomPoissonV2` receives large input shape and rates, it gives a `CHECK` fail that can trigger a denial of service attack. ```python import tensorflow as tf arg_0=tf.random.uniform(shape=(4,), dtype=tf.int32, maxval=65536) arg_1=tf.random.uniform(shape=(4, 4, 4, 4, 4), dtype=tf.float32, maxval=None) arg_2=0 arg_3=0 arg_4=tf.int32 arg_5=None tf.raw_ops.RandomPoissonV2(shape=arg_0, rate=arg_1, seed=arg_2, seed2=arg_3, dtype=arg_4, name=arg_5) ``` ### Patches We have patched the issue in GitHub commit [552bfced6ce4809db5f3ca305f60ff80dd40c5a3](https://github.com/tensorflow/tensorflow/commit/552bfced6ce4809db5f3ca305f60ff80dd40c5a3). 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. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/maste...