In the onQueueFilled function of SoftAVCDec, there is a possible out-of-bounds write due to a use after free if a bad header causes the decoder to get caught in a loop while another thread frees the memory it's accessing. This could lead to a local elevation of privilege enabling code execution as a privileged process with no additional execution privileges needed. User interaction is not needed for exploitation. Product: Android. Versions: 6.0, 6.0.1, 7.0, 7.1.1, 7.1.2, 8.0, 8.1. Android ID: A-66969349.

An elevation of privilege vulnerability in the Upstream kernel wifi driver. Product: Android. Versions: Android kernel. Android ID: A-64709938.

An elevation of privilege vulnerability in the MediaTek mtk. Product: Android. Versions: Android kernel. Android ID: A-32591194. References: M-ALPS03149184.

An elevation of privilege vulnerability in the Broadcom bcmdhd driver. Product: Android. Versions: Android kernel. Android ID: A-63374465. References: B-V2017081501.

In createFromParcel of VerifyCredentialResponse.java, there is a possible invalid parcel read due to improper input validation. This could lead to local escalation of privilege if mPayload in writeToParcel were null, with no additional execution privileges needed. User interaction is not needed for exploitation. Product: Android. Versions: 6.0.1, 7.0, 7.1.1, 7.1.2, 8.0, 8.1. Android ID: A-71714464.

In the nfc_hci_cmd_received() function of core.c, there is a possible out of bounds write due to a missing bounds check. 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: Android. Versions: Android kernel. Android ID: A-62679701.

In the enableVSyncInjections function of SurfaceFlinger, there is a possible use after free of mVSyncInjector. This could lead to a local elevation of privilege enabling code execution as a privileged process with no additional execution privileges needed. User interaction is not needed for exploitation. Product: Android. Versions: 8.0, 8.1. Android ID: A-65483324.

In the KeyStore service, there is a permissions bypass that allows access to protected resources. This could lead to local escalation of privilege with system execution privileges needed. User interaction is not needed for exploitation. Product: Android. Versions: 8.0, 8.1. Android ID: A-68217699.

A elevation of privilege vulnerability in the Upstream kernel audio driver. Product: Android. Versions: Android kernel. ID: A-64315347.

In ashmem_ioctl of ashmem.c, there is an out-of-bounds write due to insufficient locking when accessing asma. This could lead to a local elevation of privilege enabling code execution as a privileged process with no additional execution privileges needed. User interaction is not needed for exploitation. Product: Android. Versions: Android kernel. Android ID: A-66954097.

In MediaPlayerService::Client::notify of MediaPlayerService.cpp, there is a possible use after free. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation. Product: Android. Versions: 6.0, 6.0.1, 7.0, 7.1.1, 7.1.2, 8.0, 8.1. Android ID: A-70546581.

In libmediadrm, there is an out-of-bounds write due to improper input validation. This could lead to local elevation of privileges with no additional execution privileges needed. User interaction is not needed for exploitation. Product: Android. Versions: 8.0, 8.1. Android ID: A-67962232.

An elevation of privilege vulnerability in the Android media framework (libaudioservice). Product: Android. Versions: 8.0. Android ID A-65280854.

In writeToParcel and readFromParcel of OutputConfiguration.java, there is a permission bypass due to mismatched serialization. This could lead to a local escalation of privilege where the user can start an activity with system privileges, with no additional execution privileges needed. User interaction is not needed for exploitation. Product: Android. Versions: 8.0, 8.1. Android ID: A-69683251.

In the Pixel 2 bootloader, there is a missing permission check which bypasses carrier bootloader lock. This could lead to local elevation of privileges with user execution privileges needed. User interaction is not needed for exploitation. Product: Android. Versions: Android kernel. Android ID: A-71486645.

In writeToParcel and readFromParcel of PeriodicAdvertisingReport.java, there is a permission bypass due to a 64/32bit int mismatch. This could lead to a local escalation of privilege where the user can start an activity with system privileges, with no additional execution privileges needed. User interaction is not needed for exploitation. Product: Android. Versions: 8.0, 8.1. Android ID: A-69634768.

An elevation of privilege vulnerability in the Android media framework (libstagefright). Product: Android. Versions: 5.1.1, 6.0, 6.0.1, 7.0, 7.1.1, 7.1.2, 8.0. Android ID A-63666573.

An elevation of privilege vulnerability in the kernel scsi driver. Product: Android. Versions: Android kernel. Android ID A-65023233.

An elevation of privilege vulnerability in the kernel edl. Product: Android. Versions: Android kernel. Android ID A-63100473.

In DisplayFtmItem in the bootloader, there is an out-of-bounds write due to reading a string without verifying that it's null-terminated. This could lead to a secure boot bypass and a local elevation of privilege enabling code execution as a privileged process with no additional execution privileges needed. User interaction is not needed for exploitation. Product: Android. Versions: Android kernel. Android ID: A-68269077.

TensorFlow is an end-to-end open source platform for machine learning. In affected versions when running shape functions, some functions (such as `MutableHashTableShape`) produce extra output information in the form of a `ShapeAndType` struct. The shapes embedded in this struct are owned by an inference context that is cleaned up almost immediately; if the upstream code attempts to access this shape information, it can trigger a segfault. `ShapeRefiner` is mitigating this for normal output shapes by cloning them (and thus putting the newly created shape under ownership of an inference context that will not die), but we were not doing the same for shapes and types. This commit fixes that by doing similar logic on output shapes and types. We have patched the issue in GitHub commit ee119d4a498979525046fba1c3dd3f13a039fbb1. 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. In affected versions an attacker can generate undefined behavior via a reference binding to nullptr in `BoostedTreesCalculateBestGainsPerFeature` and similar attack can occur in `BoostedTreesCalculateBestFeatureSplitV2`. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/stats_ops.cc) does not validate the input values. We have patched the issue in GitHub commit 9c87c32c710d0b5b53dc6fd3bfde4046e1f7a5ad and in commit 429f009d2b2c09028647dd4bb7b3f6f414bbaad7. 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. In affected versions TensorFlow and Keras can be tricked to perform arbitrary code execution when deserializing a Keras model from YAML format. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/python/keras/saving/model_config.py#L66-L104) uses `yaml.unsafe_load` which can perform arbitrary code execution on the input. Given that YAML format support requires a significant amount of work, we have removed it for now. We have patched the issue in GitHub commit 23d6383eb6c14084a8fc3bdf164043b974818012. 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. In affected versions the implementation for `tf.raw_ops.ExperimentalDatasetToTFRecord` and `tf.raw_ops.DatasetToTFRecord` can trigger heap buffer overflow and segmentation fault. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/data/experimental/to_tf_record_op.cc#L93-L102) assumes that all records in the dataset are of string type. However, there is no check for that, and the example given above uses numeric types. We have patched the issue in GitHub commit e0b6e58c328059829c3eb968136f17aa72b6c876. 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. In affected versions the implementation for `tf.raw_ops.BoostedTreesCreateEnsemble` can result in a use after free error if an attacker supplies specially crafted arguments. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/boosted_trees/resource_ops.cc#L55) uses a reference counted resource and decrements the refcount if the initialization fails, as it should. However, when the code was written, the resource was represented as a naked pointer but later refactoring has changed it to be a smart pointer. Thus, when the pointer leaves the scope, a subsequent `free`-ing of the resource occurs, but this fails to take into account that the refcount has already reached 0, thus the resource has been already freed. During this double-free process, members of the resource object are accessed for cleanup but they are invalid as the entire resource has been freed. We have patched the issue in GitHub commit 5ecec9c6fbdbc6be03295685190a45e7eee726ab. 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. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in `tf.raw_ops.RaggedTensorToVariant`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/ragged_tensor_to_variant_op.cc#L129) has an incomplete validation of the splits values, missing the case when the argument would be empty. We have patched the issue in GitHub commit be7a4de6adfbd303ce08be4332554dff70362612. 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. In affected versions the implementation of SVDF in TFLite is [vulnerable to a null pointer error](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/svdf.cc#L300-L313). The [`GetVariableInput` function](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/kernel_util.cc#L115-L119) can return a null pointer but `GetTensorData` assumes that the argument is always a valid tensor. Furthermore, because `GetVariableInput` calls [`GetMutableInput`](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/kernel_util.cc#L82-L90) which might return `nullptr`, the `tensor->is_variable` expression can also trigger a null pointer exception. We have patched the issue in GitHub commit 5b048e87e4e55990dae6b547add4dae59f4e1c76. 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. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in `tf.raw_ops.Map*` and `tf.raw_ops.OrderedMap*` operations. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/map_stage_op.cc#L222-L248) has a check in place to ensure that `indices` is in ascending order, but does not check that `indices` is not empty. We have patched the issue in GitHub commit 532f5c5a547126c634fefd43bbad1dc6417678ac. 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.

Possible buffer overflow in msm_adsp_stream_callback_put due to lack of input validation of user-provided data that leads to integer overflow in all Android releases(Android for MSM, Firefox OS for MSM, QRD Android) from CAF using the Linux kernel.

TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation for `tf.raw_ops.FractionalAvgPoolGrad` can be tricked into accessing data outside of bounds of heap allocated buffers. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/fractional_avg_pool_op.cc#L205) does not validate that the input tensor is non-empty. Thus, code constructs an empty `EigenDoubleMatrixMap` and then accesses this buffer with indices that are outside of the empty area. We have patched the issue in GitHub commit 0f931751fb20f565c4e94aa6df58d54a003cdb30. 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. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in all operations of type `tf.raw_ops.MatrixDiagV*`. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/linalg/matrix_diag_op.cc) has incomplete validation that the value of `k` is a valid tensor. We have check that this value is either a scalar or a vector, but there is no check for the number of elements. If this is an empty tensor, then code that accesses the first element of the tensor is wrong. We have patched the issue in GitHub commit f2a673bd34f0d64b8e40a551ac78989d16daad09. 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.

In Android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, the Athdiag procfs entry does not have a proper address sanity check which may potentially lead to the use of an out-of-range pointer offset.

In Android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, while updating a firmware image, data is read from flash into RAM without checking that the data fits into allotted RAM size.

In android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, camera application triggers "user-memory-access" issue as the Camera CPP module Linux driver directly accesses the application provided buffer, which resides in user space. An unchecked userspace value (ioctl_ptr->len) is used to copy contents to a kernel buffer which can lead to kernel buffer overflow.

In Android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, in the HDMI video driver function hdmi_edid_sysfs_rda_res_info(), userspace can perform an arbitrary write into kernel memory.

In Android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, while doing sha and cipher operations, a userspace buffer is directly accessed in kernel space potentially leading to a page fault.

In Android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, setting the HMAC key by different threads during SHA operations may potentially lead to a buffer overflow.

In android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, possible buffer overflow or information leak in the functions "sme_set_ft_ies" and "csr_roam_issue_ft_preauth_req" due to incorrect initialization of WEXT callbacks and lack of the checks for buffer size.

In Android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, in compatibility mode, flash_data from 64-bit userspace may cause disclosure of kernel memory or a fault due to using a userspace-provided address.

In android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, array access out of bounds may occur in the camera driver in the kernel

In android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, when processing a specially crafted QCA_NL80211_VENDOR_SUBCMD_ENCRYPTION_TEST cfg80211 vendor command a stack-based buffer overflow can occur.

TensorFlow is an end-to-end open source platform for machine learning. When restoring tensors via raw APIs, if the tensor name is not provided, TensorFlow can be tricked into dereferencing a null pointer. Alternatively, attackers can read memory outside the bounds of heap allocated data by providing some tensor names but not enough for a successful restoration. The [implementation](https://github.com/tensorflow/tensorflow/blob/47a06f40411a69c99f381495f490536972152ac0/tensorflow/core/kernels/save_restore_tensor.cc#L158-L159) retrieves the tensor list corresponding to the `tensor_name` user controlled input and immediately retrieves the tensor at the restoration index (controlled via `preferred_shard` argument). This occurs without validating that the provided list has enough values. If the list is empty this results in dereferencing a null pointer (undefined behavior). If, however, the list has some elements, if the restoration index is outside the bounds this results in heap OOB read. We have patched the issue in GitHub commit 9e82dce6e6bd1f36a57e08fa85af213e2b2f2622. 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.

In Android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, the fd allocated during the get_metadata was not closed even though the buffer allocated to the fd was freed. This resulted in a failure during exit sequence.

In android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, an integer overflow leading to a buffer overflow due to improper bound checking in msm_audio_effects_virtualizer_handler, file msm-audio-effects-q6-v2.c

In android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, a double free can occur when kmalloc fails to allocate memory for pointers resp/req in the service-locator driver function service_locator_send_msg().

In android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, while processing the boot image header, range checks can be bypassed by supplying different versions of the header at the time of check and use.

In android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, while flashing a specially crafted UBI image, it is possible to corrupt memory, or access uninitialized memory.

In Android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, while processing a user supplied sparse image, a buffer overflow vulnerability could occur if the sparse header block size is equal to 4294967296.

In Android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, while calculating CRC for GPT header fields with partition entries greater than 16384 buffer overflow occurs.

In Android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, ImsService and the IQtiImsExt AIDL APIs are not subject to access control.