TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger undefined behavior by binding to null pointer in `tf.raw_ops.ParameterizedTruncatedNormal`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/3f6fe4dfef6f57e768260b48166c27d148f3015f/tensorflow/core/kernels/parameterized_truncated_normal_op.cc#L630) does not validate input arguments before accessing the first element of `shape`. If `shape` argument is empty, then `shape_tensor.flat<T>()` is an empty array. 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 AIBinder_Class constructor of ibinder.cpp, there is a possible arbitrary code execution due to uninitialized data. This could lead to local escalation of privilege if a process were using libbinder_ndk in a vulnerable way with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-11 Android-10Android ID: A-161812320

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.RaggedTensorToSparse`. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/ragged_tensor_to_sparse_kernel.cc#L30) has an incomplete validation of the splits values: it does not check that they are in increasing order. We have patched the issue in GitHub commit 1071f554dbd09f7e101324d366eec5f4fe5a3ece. 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 open source platform for machine learning. In affected versions the shape inference code for `tf.ragged.cross` has an undefined behavior due to binding a reference to `nullptr`. 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.

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 an attacker can cause undefined behavior via binding a reference to null pointer in `tf.raw_ops.SparseFillEmptyRows`. The shape inference [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/ops/sparse_ops.cc#L608-L634) does not validate that the input arguments are not empty tensors. We have patched the issue in GitHub commit 578e634b4f1c1c684d4b4294f9e5281b2133b3ed. 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 open source platform for machine learning. In affeced versions during execution, `EinsumHelper::ParseEquation()` is supposed to set the flags in `input_has_ellipsis` vector and `*output_has_ellipsis` boolean to indicate whether there is ellipsis in the corresponding inputs and output. However, the code only changes these flags to `true` and never assigns `false`. This results in unitialized variable access if callers assume that `EinsumHelper::ParseEquation()` always sets these flags. 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.

TensorFlow is an open source platform for machine learning. In affected versions the code for boosted trees in TensorFlow is still missing validation. As a result, attackers can trigger denial of service (via dereferencing `nullptr`s or via `CHECK`-failures) as well as abuse undefined behavior (binding references to `nullptr`s). An attacker can also read and write from heap buffers, depending on the API that gets used and the arguments that are passed to the call. Given that the boosted trees implementation in TensorFlow is unmaintained, it is recommend to no longer use these APIs. We will deprecate TensorFlow's boosted trees APIs in subsequent releases. 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.

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.UnicodeEncode`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/unicode_ops.cc#L533-L539) reads the first dimension of the `input_splits` tensor before validating that this tensor is not empty. We have patched the issue in GitHub commit 2e0ee46f1a47675152d3d865797a18358881d7a6. 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.

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 open source platform for machine learning. In affected versions the code for sparse matrix multiplication is vulnerable to undefined behavior via binding a reference to `nullptr`. This occurs whenever the dimensions of `a` or `b` are 0 or less. In the case on one of these is 0, an empty output tensor should be allocated (to conserve the invariant that output tensors are always allocated when the operation is successful) but nothing should be written to it (that is, we should return early from the kernel implementation). Otherwise, attempts to write to this empty tensor would result in heap OOB access. 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.

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.

In lwis_process_transactions_in_queue of lwis_transaction.c, there is a possible use after free due to a use after free. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation.

there is a possible escalation of privilege due to an unusual root cause. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation.

In the KGSL driver in all Android releases from CAF (Android for MSM, Firefox OS for MSM, QRD Android) using the Linux Kernel, a Use After Free condition can occur when printing information about sparse memory allocations

In Qualcomm Android for MSM, Firefox OS for MSM, and QRD Android with all Android releases from CAF using the Linux kernel before security patch level 2018-04-05, a buffer overflow vulnerability exists in WLAN while processing the HTT_T2H_MSG_TYPE_PEER_MAP or HTT_T2H_MSG_TYPE_PEER_UNMAP messages.

Buffer overflow can occur due to improper input validation in multiple WMA event handler functions in all Android releases from CAF (Android for MSM, Firefox OS for MSM, QRD Android) using the Linux Kernel.

In prepare_response of lwis_periodic_io.c, there is a possible out of bounds write due to an integer overflow. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation.

In a firmware memory dump feature in all Android releases from CAF using the Linux kernel (Android for MSM, Firefox OS for MSM, QRD Android), a Use After Free condition can occur.

In all android releases (Android for MSM, Firefox OS for MSM, QRD Android) from CAF using the linux kernel, while relocating kernel images with a specially crafted boot image, an out of bounds access can occur.

In init_data of , there is a possible out of bounds write due to a missing bounds check. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation.

In the FastRPC driver in Android releases from CAF using the linux kernel (Android for MSM, Firefox OS for MSM, QRD Android) before security patch level 2018-06-05, a Use After Free condition can occur when mapping on the remote processor fails.

In Qualcomm Android for MSM, Firefox OS for MSM, and QRD Android with all Android releases from CAF using the Linux kernel before security patch level 2018-04-05, in __wlan_hdd_cfg80211_vendor_scan(), a buffer overwrite can potentially occur.

In policy_check of fvp.c, there is a possible out of bounds write due to a missing bounds check. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation.

While processing a DSP buffer in an audio driver's event handler, an index of a buffer is not checked before accessing the buffer in all Android releases from CAF (Android for MSM, Firefox OS for MSM, QRD Android) using the Linux Kernel.

improper validation of array index in WiFi driver function sapInterferenceRssiCount() leads to array out-of-bounds access in all Android releases from CAF (Android for MSM, Firefox OS for MSM, QRD Android) using the Linux Kernel.

In Android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, a Double Free vulnerability exists in Audio Driver while opening a sound compression device.

In the cpuidle driver in all Android releases(Android for MSM, Firefox OS for MSM, QRD Android) from CAF using the Linux kernel, the list_for_each macro was not used correctly which could lead to an untrusted pointer dereference.

In the ADSP RPC driver in Android releases from CAF using the linux kernel (Android for MSM, Firefox OS for MSM, QRD Android) before security patch level 2018-06-05, an arbitrary kernel write can occur.

In strncpy of strncpy.c, there is a possible out of bounds write due to a missing bounds check. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation.

In ppcfw_init_secpolicy of ppcfw.c, there is a possible permission bypass due to uninitialized data. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation.

In config_gov_time_windows of tmu.c, there is a possible out of bounds write due to a missing bounds check. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation.

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

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

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

In firewall service, there is a missing permission check. This could lead to local escalation of privilege with system execution privileges needed.

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

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

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

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

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

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

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

An issue was discovered on Samsung mobile devices with N(7.x) software. Dex Station allows App Pinning bypass and lock-screen bypass via the "Use screen lock type to unpin" option. The Samsung ID is SVE-2017-11106 (February 2018).

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

Use after free in Page Info UI in Google Chrome prior to 92.0.4515.131 allowed a remote attacker to potentially exploit heap corruption via physical access to the device.

Improper input validation for some Intel Unison software may allow an authenticated user to potentially enable escalation of privilege via local access.

An issue was discovered on Samsung mobile devices with N(7.1) and O(8.x) software. A fake charger can execute critical functions in the locked state. The Samsung ID is SVE-2016-6341 (August 2018).

Inappropriate implementation in the ChromeOS Readiness Tool installer on Windows prior to 1.0.2.0 loosens DCOM access rights on two objects allowing an attacker to potentially bypass discretionary access controls.