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Heap buffer overflow in Browser History in Google Chrome prior to 112.0.5615.49 allowed a remote attacker who convinced a user to engage in specific UI interaction to potentially exploit heap corruption via a crafted HTML page. (Chromium security severity: Medium)Show less

Use after free in Networking APIs in Google Chrome prior to 112.0.5615.49 allowed a remote attacker who convinced a user to engage in specific UI interaction to potentially exploit heap corruption via a crafted HTML page. (Chromium security severity: Medium)Show less

Inappropriate implementation in Extensions in Google Chrome prior to 112.0.5615.49 allowed an attacker who convinced a user to install a malicious extension to bypass file access restrictions via a crafted HTML page. (Chromium security severity: Medium)Show less

Use after free in Frames in Google Chrome prior to 112.0.5615.49 allowed a remote attacker who convinced a user to engage in specific UI interaction to potentially exploit heap corruption via a crafted HTML page. (Chromium security severity: High)Show less

Heap buffer overflow in Visuals in Google Chrome prior to 112.0.5615.49 allowed a remote attacker who had compromised the renderer process to potentially exploit heap corruption via a crafted HTML page. (Chromium security severity: High)Show less

TensorFlow is an Open Source Machine Learning Framework. In versions prior to 2.11.1 a malicious invalid input crashes a tensorflow model (Check Failed) and can be used to trigger a denial of service attack. A proof of concept can be constructed with the `Convolution3DTranspose` function. This Convolution3DTranspose layer is a very common API in modern neural networks. The ML models containing such vulnerable components could be deployed in ML applications or as cloud services. This failure could be potentially used to trigger a denial of service attack on ML cloud services. An attacker must have privilege to provide input to a `Convolution3DTranspose` call. This issue has been patched and users are advised to upgrade to version 2.11.1. There are no known workarounds for this vulnerability.Show less

TensorFlow is an end-to-end open source platform for machine learning. Constructing a tflite model with a paramater `filter_input_channel` of less than 1 gives a FPE. This issue has been patched in version 2.12. TensorFlow will also cherrypick the fix commit on TensorFlow 2.11.1. Show less

TensorFlow is an open source machine learning platform. Prior to versions 2.12.0 and 2.11.1, `nn_ops.fractional_avg_pool_v2` and `nn_ops.fractional_max_pool_v2` require the first and fourth elements of their parameter `pooling_ratio` to be equal to 1.0, as pooling on batch and channel dimensions is not supported. A fix is included in TensorFlow 2.12.0 and 2.11.1.Show less

TensorFlow is an open source machine learning platform. When running versions prior to 2.12.0 and 2.11.1 with XLA, `tf.raw_ops.ParallelConcat` segfaults with a nullptr dereference when given a parameter `shape` with rank that is not greater than zero. A fix is available in TensorFlow 2.12.0 and 2.11.1.Show less

TensorFlow is an open source machine learning platform. When running versions prior to 2.12.0 and 2.11.1 with XLA, `tf.raw_ops.Bincount` segfaults when given a parameter `weights` that is neither the same shape as parameter `arr` nor a length-0 tensor. A fix is included in TensorFlow 2.12.0 and 2.11.1.Show less

TensorFlow is an open source platform for machine learning. Versions prior to 2.12.0 and 2.11.1 have a Floating Point Exception in TensorListSplit with XLA. A fix is included in TensorFlow version 2.12.0 and version 2.11.1. Show less

TensorFlow is an open source platform for machine learning. The function `tf.raw_ops.LookupTableImportV2` cannot handle scalars in the `values` parameter and gives an NPE. A fix is included in TensorFlow version 2.12.0 and version 2.11.1. Show less