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A vulnerability was found in davidmoreno onion. It has been rated as problematic. Affected by this issue is the function onion_response_flush of the file src/onion/response.c of the component Log Handler. The manipulation leads to allocation of resources. The name of the patch is de8ea938342b36c28024fd8393ebc27b8442a161. It is recommended to apply a patch to fix this issue. The identifier of this vulnerability is VDB-214028.
Auth. (subscriber+) Insecure Direct Object References (IDOR) vulnerability in Comments – wpDiscuz plugin 7.4.2 on WordPress.
InstallBuilder Qt installers built with versions previous to 22.10 try to load DLLs from the installer binary parent directory when displaying popups. This may allow an attacker to plant a malicious DLL in the installer parent directory to allow executing code with the privileges of the installer (when the popup triggers the loading of the library). Exploiting these type of vulnerabilities generally require that an attacker has access to a vulnerable machine to plant the malicious DLL.
Auth. (subscriber+) Cross-Site Scripting (XSS) vulnerability in Soledad premium theme <= 8.2.5 on WordPress.
Cross-Site Request Forgery (CSRF) vulnerability in Media Library Folders plugin <= 7.1.1 on WordPress.
TensorFlow is an open source platform for machine learning. When `tf.raw_ops.FusedResizeAndPadConv2D` is given a large tensor shape, it overflows. We have patched the issue in GitHub commit d66e1d568275e6a2947de97dca7a102a211e01ce. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.
TensorFlow is an open source platform for machine learning. When `tf.raw_ops.ImageProjectiveTransformV2` is given a large output shape, it overflows. We have patched the issue in GitHub commit 8faa6ea692985dbe6ce10e1a3168e0bd60a723ba. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.
TensorFlow is an open source platform for machine learning. `tf.keras.losses.poisson` receives a `y_pred` and `y_true` that are passed through `functor::mul` in `BinaryOp`. If the resulting dimensions overflow an `int32`, TensorFlow will crash due to a size mismatch during broadcast assignment. We have patched the issue in GitHub commit c5b30379ba87cbe774b08ac50c1f6d36df4ebb7c. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1 and 2.9.3, as these are also affected and still in supported range. However, we will not cherrypick this commit into TensorFlow 2.8.x, as it depends on Eigen behavior that changed between 2.8 and 2.9.
TensorFlow is an open source platform for machine learning. If `BCast::ToShape` is given input larger than an `int32`, it will crash, despite being supposed to handle up to an `int64`. An example can be seen in `tf.experimental.numpy.outer` by passing in large input to the input `b`. We have patched the issue in GitHub commit 8310bf8dd188ff780e7fc53245058215a05bdbe5. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.
TensorFlow is an open source platform for machine learning. The reference kernel of the `CONV_3D_TRANSPOSE` TensorFlow Lite operator wrongly increments the data_ptr when adding the bias to the result. Instead of `data_ptr += num_channels;` it should be `data_ptr += output_num_channels;` as if the number of input channels is different than the number of output channels, the wrong result will be returned and a buffer overflow will occur if num_channels > output_num_channels. An attacker can craft a model with a specific number of input channels. It is then possible to write specific values through the bias of the layer outside the bounds of the buffer. This attack only works if the reference kernel resolver is used in the interpreter. We have patched the issue in GitHub commit 72c0bdcb25305b0b36842d746cc61d72658d2941. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in ...