Skia, as used in Google Chrome before 16.0.912.77, does not perform all required initialization of values, which allows remote attackers to cause a denial of service or possibly have unspecified other impact via unknown vectors.

Use after free in WebUI in Google Chrome on Chrome OS prior to 104.0.5112.79 allowed a remote attacker who convinced a user to engage in specific user interactions to potentially exploit heap corruption via specific UI interactions.

In all android releases(Android for MSM, Firefox OS for MSM, QRD Android) from CAF using the linux kernel, while processing fastboot flash command, memory leak or unexpected behavior may occur due to processing of unintialized data buffers.

TensorFlow is an end-to-end open source platform for machine learning. Incomplete validation in `SparseReshape` results in a denial of service based on a `CHECK`-failure. The implementation(https://github.com/tensorflow/tensorflow/blob/e87b51ce05c3eb172065a6ea5f48415854223285/tensorflow/core/kernels/sparse_reshape_op.cc#L40) has no validation that the input arguments 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 and TensorFlow 2.3.3, as these are the only affected versions.

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. Incomplete validation in `SparseAdd` results in allowing attackers to exploit undefined behavior (dereferencing null pointers) as well as write outside of bounds of heap allocated data. The implementation(https://github.com/tensorflow/tensorflow/blob/656e7673b14acd7835dc778867f84916c6d1cac2/tensorflow/core/kernels/sparse_add_op.cc) has a large set of validation for the two sparse tensor inputs (6 tensors in total), but does not validate that the tensors are not empty or that the second dimension of `*_indices` matches the size of corresponding `*_shape`. This allows attackers to send tensor triples that represent invalid sparse tensors to abuse code assumptions that are not protected by validation. 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.

In the Titan-M chip firmware, there is a possible disclosure of stack memory due to uninitialized data. This could lead to local information disclosure with System execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android kernelAndroid ID: A-175117199

In memory management driver, there is a possible information disclosure due to uninitialized data. This could lead to local information disclosure with no additional execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS05403499; Issue ID: ALPS05385714.

In the Titan M chip firmware, there is a possible disclosure of stack memory due to uninitialized data. This could lead to local information disclosure with System execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android kernelAndroid ID: A-175117965

Trusted Computing Group (TCG) Trusted Platform Module Library Family 2.0 Library Specification Revisions 1.38 through 1.59 has Incorrect Access Control during a non-orderly TPM shut-down that uses USE_DA_USED. Improper initialization of this shut-down may result in susceptibility to a dictionary attack.