TensorFlow is an open source platform for machine learning. In affected versions the process of building the control flow graph for a TensorFlow model is vulnerable to a null pointer exception when nodes that should be paired are not. This occurs because the code assumes that the first node in the pairing (e.g., an `Enter` node) always exists when encountering the second node (e.g., an `Exit` node). When this is not the case, `parent` is `nullptr` so dereferencing it causes a crash. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.

In video decoder, there is a possible out of bounds read due to improper input validation. This could lead to local denial of service with no additional execution privileges needed

In video decoder, there is a possible improper input validation. This could lead to local denial of service with no additional execution privileges needed

In video decoder, there is a possible out of bounds write due to improper input validation. This could lead to local denial of service with no additional execution privileges needed

In video decoder, there is a possible out of bounds read due to improper input validation. This could lead to local denial of service with no additional execution privileges needed

In video decoder, there is a possible out of bounds write due to improper input validation. This could lead to local denial of service with no additional execution privileges needed

In video decoder, there is a possible out of bounds read due to improper input validation. This could lead to local denial of service with no additional execution privileges needed

In video decoder, there is a possible out of bounds write due to a missing bounds check. This could lead to local denial of service with no additional execution privileges needed

In video decoder, there is a possible out of bounds write due to a missing bounds check. This could lead to local denial of service with no additional execution privileges needed

In video decoder, there is a possible out of bounds write due to improper input validation. This could lead to local denial of service with no additional execution privileges needed

In video decoder, there is a possible out of bounds read due to improper input validation. This could lead to local denial of service with no additional execution privileges needed

TensorFlow is an end-to-end open source platform for machine learning. In affected versions providing a negative element to `num_elements` list argument of `tf.raw_ops.TensorListReserve` causes the runtime to abort the process due to reallocating a `std::vector` to have a negative number of elements. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/list_kernels.cc#L312) calls `std::vector.resize()` with the new size controlled by input given by the user, without checking that this input is valid. We have patched the issue in GitHub commit 8a6e874437670045e6c7dc6154c7412b4a2135e2. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

TensorFlow is an end-to-end open source platform for machine learning. Calling `tf.raw_ops.RaggedTensorToVariant` with arguments specifying an invalid ragged tensor results in a null pointer dereference. The implementation of `RaggedTensorToVariant` operations(https://github.com/tensorflow/tensorflow/blob/904b3926ed1c6c70380d5313d282d248a776baa1/tensorflow/core/kernels/ragged_tensor_to_variant_op.cc#L39-L40) does not validate that the ragged tensor argument is non-empty. Since `batched_ragged` contains no elements, `batched_ragged.splits` is a null vector, thus `batched_ragged.splits(0)` will result in dereferencing `nullptr`. 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.MaxPool3DGradGrad` exhibits undefined behavior by dereferencing null pointers backing attacker-supplied empty tensors. The implementation(https://github.com/tensorflow/tensorflow/blob/72fe792967e7fd25234342068806707bbc116618/tensorflow/core/kernels/pooling_ops_3d.cc#L679-L703) fails to validate that the 3 tensor inputs are not empty. If any of them is empty, then accessing the elements in the tensor results in dereferencing a null pointer. 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. An attacker can trigger a null pointer dereference in the implementation of `tf.raw_ops.SparseFillEmptyRows`. This is because of missing validation(https://github.com/tensorflow/tensorflow/blob/fdc82089d206e281c628a93771336bf87863d5e8/tensorflow/core/kernels/sparse_fill_empty_rows_op.cc#L230-L231) that was covered under a `TODO`. If the `dense_shape` tensor is empty, then `dense_shape_t.vec<>()` would cause a null pointer dereference in the implementation of the op. 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. Passing invalid arguments (e.g., discovered via fuzzing) to `tf.raw_ops.SparseCountSparseOutput` results in segfault. 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. An attacker can trigger a denial of service via a `CHECK`-fail in `tf.raw_ops.AddManySparseToTensorsMap`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/6f9896890c4c703ae0a0845394086e2e1e523299/tensorflow/core/kernels/sparse_tensors_map_ops.cc#L257) takes the values specified in `sparse_shape` as dimensions for the output shape. The `TensorShape` constructor(https://github.com/tensorflow/tensorflow/blob/6f9896890c4c703ae0a0845394086e2e1e523299/tensorflow/core/framework/tensor_shape.cc#L183-L188) uses a `CHECK` operation which triggers when `InitDims`(https://github.com/tensorflow/tensorflow/blob/6f9896890c4c703ae0a0845394086e2e1e523299/tensorflow/core/framework/tensor_shape.cc#L212-L296) returns a non-OK status. This is a legacy implementation of the constructor and operations should use `BuildTensorShapeBase` or `AddDimWithStatus` to prevent `CHECK`-failures in the presence of overflows. 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 implementations of the `Minimum` and `Maximum` TFLite operators can be used to read data outside of bounds of heap allocated objects, if any of the two input tensor arguments are empty. This is because the broadcasting implementation(https://github.com/tensorflow/tensorflow/blob/0d45ea1ca641b21b73bcf9c00e0179cda284e7e7/tensorflow/lite/kernels/internal/reference/maximum_minimum.h#L52-L56) indexes in both tensors with the same index but does not validate that the index is within 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.

In phasecheckserver, there is a possible out of bounds read due to a missing bounds check. This could lead to local denial of service with no additional execution privileges needed

In telecom service, there is a possible missing permission check. This could lead to local denial of service with no additional execution privileges needed

In camera service, there is a possible out of bounds read due to a missing bounds check. This could lead to local denial of service with no additional execution privileges needed

In video service, there is a possible out of bounds read due to a incorrect bounds check. This could lead to local denial of service with no additional execution privileges needed

In video service, there is a possible out of bounds read due to a missing bounds check. This could lead to local denial of service with no additional execution privileges needed

In faceid service, there is a possible out of bounds write due to a missing bounds check. This could lead to local denial of service with no additional execution privileges

In LocaleList of LocaleList.java, there is a possible forced reboot due to an uncaught exception. This could lead to local denial of service requiring factory reset to restore with User execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-11 Android-8.0 Android-8.1 Android-9 Android-10Android ID: A-152410253

In the Accessibility service, there is a possible permission bypass due to an unsafe PendingIntent. This could lead to local information disclosure with User execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-11Android ID: A-154913130

In SoundRecorder service, there is a possible missing permission check. This could lead to local information disclosure with no additional execution privileges

In uvc_scan_chain_forward of uvc_driver.c, there is a possible linked list corruption due to an unusual root cause. This could lead to local escalation of privilege in the kernel with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android kernelAndroid ID: A-111893654References: Upstream kernel

In CellBroadcastReceiver's intent handlers, there is a possible denial of service due to a missing permission check. This could lead to local denial of service of emergency alerts with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-8.0 Android-8.1 Android-9 Android-10 Android-11Android ID: A-162741784

In the settings app, there is a possible app crash due to improper input validation. This could lead to local denial of service of the Settings app with User execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-10Android ID: A-136005061

In the System UI, there is a possible system crash due to an uncaught exception. This could lead to local permanent denial of service with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-11Android ID: A-33646131

In generateCrop of WallpaperManagerService.java, there is a possible sysui crash due to image exceeding maximum texture size. This could lead to local denial of service with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-8.0 Android-8.1 Android-9 Android-10Android ID: A-120847476

In forceReplaceShortcutInner of ShortcutPackage.java, there is a possible way to register unlimited packages due to a missing bounds check. This could lead to local denial of service which results in a boot loop with no additional execution privileges needed. User interaction is not needed for exploitation.

In FM service , there is a possible missing params check. This could lead to local denial of service in FM service .

In contacts service, there is a possible missing permission check. This could lead to local denial of service with no additional execution privileges.

In TeleService, there is a possible system crash due to improper input validation. This could lead to local denial of service with no additional execution privileges needed

In wifi service, there is a possible out of bounds write due to a missing bounds check. This could lead to local denial of service with no additional execution privileges needed

In telephony service, there is a possible missing permission check. This could lead to local denial of service with no additional execution privileges.

In vowifiservice, there is a possible missing permission check.This could lead to local denial of service with no additional execution privileges

In wcn bsp driver, there is a possible out of bounds write due to a missing bounds check.This could lead to local denial of service with no additional execution privileges

In vowifiservice, there is a possible missing permission check.This could lead to local denial of service with no additional execution privileges

In vowifiservice, there is a possible missing permission check.This could lead to local denial of service with no additional execution privileges

In vowifiservice, there is a possible missing permission check.This could lead to local denial of service with no additional execution privileges

In vowifiservice, there is a possible missing permission check.This could lead to local denial of service with no additional execution privileges

In vowifiservice, there is a possible missing permission check.This could lead to local denial of service with no additional execution privileges

An issue was discovered on LG mobile devices with Android OS software before 2020-06-01. Local users can cause a denial of service because checking of the userdata partition is mishandled. The LG ID is LVE-SMP-200014 (June 2020).

In FM service , there is a possible missing params check. This could lead to local denial of service in FM service .

In telephony service, there is a possible missing permission check. This could lead to local denial of service with no additional execution privileges.

In telephony service, there is a possible missing permission check. This could lead to local denial of service with no additional execution privileges.

In telephony service, there is a possible missing permission check. This could lead to local denial of service with no additional execution privileges.