TensorFlow is an end-to-end open source platform for machine learning. The implementation of `MatrixDiag*` operations(https://github.com/tensorflow/tensorflow/blob/4c4f420e68f1cfaf8f4b6e8e3eb857e9e4c3ff33/tensorflow/core/kernels/linalg/matrix_diag_op.cc#L195-L197) does not validate that the tensor arguments are non-empty. 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. If the `splits` argument of `RaggedBincount` does not specify a valid `SparseTensor`(https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor), then an attacker can trigger a heap buffer overflow. This will cause a read from outside the bounds of the `splits` tensor buffer in the implementation of the `RaggedBincount` op(https://github.com/tensorflow/tensorflow/blob/8b677d79167799f71c42fd3fa074476e0295413a/tensorflow/core/kernels/bincount_op.cc#L430-L433). Before the `for` loop, `batch_idx` is set to 0. The user controls the `splits` array, making it contain only one element, 0. Thus, the code in the `while` loop would increment `batch_idx` and then try to read `splits(1)`, which is outside of bounds. 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 also affected.

TensorFlow is an end-to-end open source platform for machine learning. If the `splits` argument of `RaggedBincount` does not specify a valid `SparseTensor`(https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor), then an attacker can trigger a heap buffer overflow. This will cause a read from outside the bounds of the `splits` tensor buffer in the implementation of the `RaggedBincount` op(https://github.com/tensorflow/tensorflow/blob/8b677d79167799f71c42fd3fa074476e0295413a/tensorflow/core/kernels/bincount_op.cc#L430-L446). Before the `for` loop, `batch_idx` is set to 0. The attacker sets `splits(0)` to be 7, hence the `while` loop does not execute and `batch_idx` remains 0. This then results in writing to `out(-1, bin)`, which is before the heap allocated buffer for the output 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 also affected.

In multiple functions of ShortcutService.java, there is a possible persistent DOS due to resource exhaustion. This could lead to local denial of service with no additional execution privileges needed. User interaction is not needed for exploitation.

TensorFlow is an end-to-end open source platform for machine learning. The API of `tf.raw_ops.SparseCross` allows combinations which would result in a `CHECK`-failure and denial of service. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/3d782b7d47b1bf2ed32bd4a246d6d6cadc4c903d/tensorflow/core/kernels/sparse_cross_op.cc#L114-L116) is tricked to consider a tensor of type `tstring` which in fact contains integral elements. Fixing the type confusion by preventing mixing `DT_STRING` and `DT_INT64` types solves this issue. 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 cause a heap buffer overflow in `QuantizedReshape` by passing in invalid thresholds for the quantization. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/a324ac84e573fba362a5e53d4e74d5de6729933e/tensorflow/core/kernels/quantized_reshape_op.cc#L38-L55) assumes that the 2 arguments are always valid scalars and tries to access the numeric value directly. However, if any of these tensors is empty, then `.flat<T>()` is an empty buffer and accessing the element at position 0 results in overflow. 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 endCallForSubscriber of PhoneInterfaceManager.java, there is a possible way to prevent access to emergency services due to a logic error in the code. This could lead to a local denial of service with no additional execution privileges needed. User interaction is not needed for exploitation.

Calling of non-existent provider in Samsung Members prior to version 2.4.81.13 (in Android O(8.1) and below) and 3.8.00.13 (in Android P(9.0) and above) allows unauthorized actions including denial of service attack by hijacking the provider.

In multiple functions of AppOpsService.java, there is a possible way to saturate the content of /data/system/appops_accesses.xml due to resource exhaustion. This could lead to local denial of service with no additional execution privileges needed. User interaction is not needed for exploitation.

Nullptr dereference when a null char is present in a proto symbol. The symbol is parsed incorrectly, leading to an unchecked call into the proto file's name during generation of the resulting error message. Since the symbol is incorrectly parsed, the file is nullptr. We recommend upgrading to version 3.15.0 or greater.

In SystemSettingsValidators, there is a possible permanent denial of service due to missing bounds checks on UI settings. This could lead to local denial of service with User execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-10 Android-11Android ID: A-156260178

In memory management driver, there is a possible system crash due to a missing bounds check. This could lead to local denial of service with no additional execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS05403499; Issue ID: ALPS05381065.

In memory management driver, there is a possible system crash due to a missing bounds check. This could lead to local denial of service with no additional execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS05403499; Issue ID: ALPS05381071.

In memory management driver, 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. User interaction is not needed for exploitation. Patch ID: ALPS05403499; Issue ID: ALPS05336702.

In addSubInfo of SubscriptionController.java, there is a possible way to force the user to make a factory reset due to a logic error in the code. This could lead to local denial of service with System execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-12Android ID: A-197327688

In memory management driver, there is a possible system crash due to a missing bounds check. This could lead to local denial of service with no additional execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS05403499; Issue ID: ALPS05393787.

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 telecom service, there is a possible missing permission 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 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 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 validate of WifiConfigurationUtil.java , there is a possible persistent denial of service due to resource exhaustion. This could lead to local denial of service with no additional execution privileges needed. User interaction is not needed for exploitation.

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

In flv extractor, there is a possible missing verification incorrect input. This could lead to local denial of service with no additional execution privileges needed

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

An issue was discovered on LG mobile devices with Android OS 7.0, 7.1, 7.2, 8.0, 8.1, and 9.0 software. A TrustZone trusted application can crash via crafted input. The LG ID is LVE-SMP-190003 (May 2019).

In multiple functions of SnoozeHelper.java, there is a possible persistent denial of service due to resource exhaustion. This could lead to local denial of service with no additional execution privileges needed. User interaction is not needed for exploitation.

In multiple functions of SnoozeHelper.java, there is a possible way to cause a boot loop due to resource exhaustion. This could lead to local denial of service with no additional execution privileges needed. User interaction is not needed for exploitation.

An issue was discovered on LG mobile devices with Android OS 7.0, 7.1, 7.2, 8.0, and 8.1 software. A TZ trusted application can crash via crafted input. The LG ID is LVE-SMP-190005 (July 2019).

In ril service, there is a possible out of bounds write due to a missing bounds check. This could lead to local denial of service with System execution privileges needed

In ril service, there is a possible out of bounds write due to a missing bounds check. This could lead to local denial of service with System execution privileges needed

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

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 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 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 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

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, there is a potential for segfault / denial of service in TensorFlow by calling `tf.compat.v1.*` ops which don't yet have support for quantized types, which was added after migration to TensorFlow 2.x. In these scenarios, since the kernel is missing, a `nullptr` value is passed to `ParseDimensionValue` for the `py_value` argument. Then, this is dereferenced, resulting in segfault. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

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 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