CWE-125

When drawing text onto a canvas with WebRender disabled, an out of bounds read could occur. *This bug only affects Firefox on Windows. Other operating systems are unaffected.*. This vulnerability affects Firefox < 89.0.1.

TensorFlow is an end-to-end open source platform for machine learning. Incomplete validation in `tf.raw_ops.CTCLoss` allows an attacker to trigger an OOB read from heap. The fix will be included in TensorFlow 2.5.0. We will also cherrypick these commits on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

TensorFlow is an end-to-end open source platform for machine learning. An attacker can access data outside of bounds of heap allocated array in `tf.raw_ops.UnicodeEncode`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/472c1f12ad9063405737679d4f6bd43094e1d36d/tensorflow/core/kernels/unicode_ops.cc) assumes that the `input_value`/`input_splits` pair specify a valid sparse tensor. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPoolGradWithArgmax` can cause reads outside of bounds of heap allocated data if attacker supplies specially crafted inputs. The implementation(https://github.com/tensorflow/tensorflow/blob/ac328eaa3870491ababc147822cd04e91a790643/tensorflow/core/kernels/requantization_range_op.cc#L49-L50) assumes that the `input_min` and `input_max` tensors have at least one element, as it accesses the first element in two arrays. If the tensors are empty, `.flat()` is an empty object, backed by an empty array. Hence, accesing even the 0th element is a read outside the bounds. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPoolGradWithArgmax` can cause reads outside of bounds of heap allocated data if attacker supplies specially crafted inputs. The implementation(https://github.com/tensorflow/tensorflow/blob/ef0c008ee84bad91ec6725ddc42091e19a30cf0e/tensorflow/core/kernels/maxpooling_op.cc#L1016-L1017) uses the same value to index in two different arrays but there is no guarantee that the sizes are identical. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

TensorFlow is an end-to-end open source platform for machine learning. Due to lack of validation in `tf.raw_ops.Dequantize`, an attacker can trigger a read from outside of bounds of heap allocated data. The implementation(https://github.com/tensorflow/tensorflow/blob/26003593aa94b1742f34dc22ce88a1e17776a67d/tensorflow/core/kernels/dequantize_op.cc#L106-L131) accesses the `min_range` and `max_range` tensors in parallel but fails to check that they have the same shape. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.