In sec_ts_parsing_cmds of (TBD), there is a possible out of bounds write due to an incorrect bounds check. This could lead to local escalation of privilege with System execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android kernelAndroid ID: A-194499021References: N/A

In the TitanM chip, there is a possible out of bounds write due to a missing bounds check. This could lead to local escalation of privilege with System execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android kernelAndroid ID: A-202006191References: N/A

In ProtocolStkProactiveCommandAdapter::Init of protocolstkadapter.cpp, there is a possible out of bounds write due to an incorrect bounds check. This could lead to local escalation of privilege with System execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android kernelAndroid ID: A-205036834References: N/A

In SmsController, there is a possible information disclosure due to a permissions bypass. This could lead to local escalation of privilege and sending sms with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-12LAndroid ID: A-195311502

In TBD of TBD, there is a possible way to access PIN protected settings bypassing PIN confirmation due to a missing permission check. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android kernelAndroid ID: A-193438173References: N/A

In amcs_cdev_unlocked_ioctl of audiometrics.c, there is a possible out of bounds write due to improper input validation. This could lead to local escalation of privilege with System execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android kernelAndroid ID: A-206128522References: N/A

In TBD of TBD, there is a possible out of bounds write due to memory corruption. This could lead to local escalation of privilege with System execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android kernelAndroid ID: A-195726151References: N/A

In Telephony, there is a possible unauthorized modification of the PLMN SIM file due to a missing permission check. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-12LAndroid ID: A-202760015

In libstagefright, 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.Product: AndroidVersions: Android-12LAndroid ID: A-180200830

In regmap_exit of regmap.c, there is a possible use-after-free due to improper locking. This could lead to local escalation of privilege in the kernel with System execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android kernelAndroid ID: A-174049006References: N/A

In delete_protocol of main.c, there is a possible arbitrary code execution 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.Product: AndroidVersions: Android kernelAndroid ID: A-200251074References: N/A

In PermissionController, there is a possible way to delete some local files due to an unsafe PendingIntent. This could lead to local escalation of privilege with User execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-12LAndroid ID: A-194696395

In sendMessage of OneToOneChatImpl.java (? TBD), there is a possible way to send an RCS message without permissions due to a missing permission check. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android kernelAndroid ID: A-208650395References: N/A

In ion_buffer_kmap_get of ion.c, there is a possible use-after-free 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.Product: AndroidVersions: Android kernelAndroid ID: A-205573273References: Upstream kernel

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 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 it is possible to nest a `tf.map_fn` within another `tf.map_fn` call. However, if the input tensor is a `RaggedTensor` and there is no function signature provided, code assumes the output is a fully specified tensor and fills output buffer with uninitialized contents from the heap. The `t` and `z` outputs should be identical, however this is not the case. The last row of `t` contains data from the heap which can be used to leak other memory information. The bug lies in the conversion from a `Variant` tensor to a `RaggedTensor`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/ragged_tensor_from_variant_op.cc#L177-L190) does not check that all inner shapes match and this results in the additional dimensions. The same implementation can result in data loss, if input tensor is tweaked. We have patched the issue in GitHub commit 4e2565483d0ffcadc719bd44893fb7f609bb5f12. 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.

In Snapdragon (Automobile, Mobile, Wear) in version MDM9607, MSM8909W, MSM8996AU, SD 210/SD 212/SD 205, SD 425, SD 427, SD 430, SD 435, SD 450, SD 617, SD 625, SD 650/52, SD 820, SD 820A, SD 835, SDM429, SDM439, SDM632, Snapdragon_High_Med_2016, when a Trusted Application has opened the SPI/I2C interface to a particular device, it is possible for another Trusted Application to read the data on this open interface by calling the SPI/I2C read function.

In wma_ndp_end_response_event_handler(), the variable len_end_rsp is a uint32 which can be overflowed if the value of variable "event->num_ndp_end_rsp_per_ndi_list" is very large which can then lead to a heap overwrite of the heap object end_rsp in all Android releases from CAF (Android for MSM, Firefox OS for MSM, QRD Android) using the Linux Kernel.

Improper access control on secure display buffers in snapdragon automobile, snapdragon mobile and snapdragon wear in versions MDM9206, MDM9607, MDM9650, MSM8996AU, SD 210/SD 212/SD 205, SD 820, SD 820A, SD 835, SDA660

In a device, with screen size 1440x2560, the check of contiguous buffer will overflow on certain buffer size resulting in an Integer Overflow or Wraparound in System UI in Snapdragon Automobile, Snapdragon Mobile in version MDM9635M, SD 400, SD 410/12, SD 425, SD 427, SD 430, SD 435, SD 450, SD 615/16/SD 415, SD 617, SD 625, SD 650/52, SD 800, SD 810, SD 820, SD 820A, SD 835, SDM630, SDM636, SDM660, Snapdragon_High_Med_2016.

When a 3rd party TEE has been loaded it is possible for the non-secure world to create a secure monitor call which will give it access to privileged functions meant to only be accessible from the TEE in Snapdragon Automobile, Snapdragon Mobile and Snapdragon Wear in versions IPQ8074, MDM9206, MDM9607, MDM9635M, MDM9650, MDM9655, MSM8996AU, SD 210/SD 212/SD 205, SD 410/12, SD 425, SD 427, SD 430, SD 435, SD 439 / SD 429, SD 450, SD 625, SD 632, SD 636, SD 650/52, SD 810, SD 820, SD 820A, SD 835, SDA660, SDM439, SDM630, SDM660, SDX24, Snapdragon_High_Med_2016.

In Android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, potential buffer overflow can happen when processing UTF event in wma_process_utf_event().

Lack of Input Validation in SDMX API can lead to NULL pointer access in Snapdragon Automobile, Snapdragon Mobile and Snapdragon Wear in versions MDM9206, MDM9607, MDM9650, MSM8996AU, SD 210/SD 212/SD 205, SD 410/12, SD 425, SD 430, SD 450, SD 615/16/SD 415, SD 617, SD 625, SD 650/52, SD 810, SD 820, SD 820A, SD 835, SD 845, SD 850, SDA660 .

Possible buffer overflows and array out of bounds accesses 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 while flashing images.

While accessing SafeSwitch services, third party can manipulate a given device and perform unauthorized operation due to lack of checking of same state transitions in Snapdragon Automobile, Snapdragon Mobile in version MSM8996AU, SD 410/12, SD 617, SD 650/52, SD 810, SD 820, SD 820A

In Android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, improper input validation for num_vdev_mac_entries in wma_pdev_hw_mode_transition_evt_handler(), which is received from firmware, leads to potential buffer overflow.

In Android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, improper input validation for p2p_noa_info in wma_send_bcn_buf_ll() which is received from firmware leads to potential buffer overflow.

XPU Master privilege escalation is possible due to improper access control of unused configuration xPU ports where unused configuration ports are open in Snapdragon Automobile, Snapdragon Mobile, Snapdragon Wear in version MDM9607, MDM9635M, MDM9640, MDM9645, MDM9650, MDM9655, MSM8909W, MSM8996AU, SD 210/SD 212/SD 205, SD 410/12, SD 425, SD 427, SD 430, SD 435, SD 450, SD 615/16/SD 415, SD 625, SD 650/52, SD 810, SD 820, SD 820A, SD 835, SDA660, SDM429, SDM439, SDM630, SDM632, SDM636, SDM660, Snapdragon_High_Med_2016.

A crafted binder request can cause an arbitrary unmap in MediaServer 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, improper input validation for nlo_event in wma_nlo_match_evt_handler(), which is received from firmware, leads to potential out of bound memory access.

In Android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, improper input validation for wmi_event->num_vdev_mac_entries in wma_pdev_set_hw_mode_resp_evt_handler(), which is received from firmware, leads to potential buffer overflow.

Insufficient memory allocation in boot due to incorrect size being passed could result in out of bounds access in Small Cell SoC, Snapdragon Automobile, Snapdragon Mobile and Snapdragon Wear in version FSM9055, MDM9206, MDM9607, MDM9640, MDM9650, MSM8909W, MSM8996AU, SD 210/SD 212/SD 205, SD 425, SD 430, SD 450, SD 615/16/SD 415, SD 617, SD 625, SD 650/52, SD 810, SD 820, SD 820A, SD 835, SDA660 and SDX20

QSEE unload attempt on a 3rd party TEE without previously loading results in a data abort in snapdragon automobile and snapdragon mobile in versions MSM8996AU, SD 410/12, SD 425, SD 427, SD 430, SD 435, SD 439 / SD 429, SD 450, SD 615/16/SD 415, SD 625, SD 632, SD 636, SD 650/52, SD 712 / SD 710 / SD 670, SD 810, SD 820, SD 820A, SD 835, SDA660, SDM439, SDM630, SDM660, SDX24, Snapdragon_High_Med_2016, SXR1130.

While playing HEVC content using HD DMB in Snapdragon Automobile and Snapdragon Mobile in version MSM8996AU, SD 450, SD 625, SD 820, SD 820A, SD 835, an uninitialized variable can be used leading to a kernel fault.

Buffer over-read vulnerabilities in an older version of ASN.1 parser in Snapdragon Mobile in versions SD 600.

In Android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, improper controls in MSM CORE leads to use memory after it is freed in msm_core_ioctl().

Double memory free while closing TEE SE API Session management in Snapdragon Mobile in version SD 425, SD 430, SD 450, SD 625, SD 650/52, SD 820.

TensorFlow is an end-to-end open source platform for machine learning. In affected versions due to incomplete validation in MKL implementation of requantization, an attacker can trigger undefined behavior via binding a reference to a null pointer or can access data outside the bounds of heap allocated arrays. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/mkl/mkl_requantization_range_per_channel_op.cc) does not validate the dimensions of the `input` tensor. A similar issue occurs in `MklRequantizePerChannelOp`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/mkl/mkl_requantize_per_channel_op.cc) does not perform full validation for all the input arguments. We have patched the issue in GitHub commit 9e62869465573cb2d9b5053f1fa02a81fce21d69 and in the Github commit 203214568f5bc237603dbab6e1fd389f1572f5c9. 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, potential buffer overflow can happen when processing AOA measurement event from WIGIG firmware in wil_aoa_evt_meas().

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 the code for `tf.raw_ops.SaveV2` does not properly validate the inputs and an attacker can trigger a null pointer dereference. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/save_restore_v2_ops.cc) uses `ValidateInputs` to check that the input arguments are valid. This validation would have caught the illegal state represented by the reproducer above. However, the validation uses `OP_REQUIRES` which translates to setting the `Status` object of the current `OpKernelContext` to an error status, followed by an empty `return` statement which just terminates the execution of the function it is present in. However, this does not mean that the kernel execution is finalized: instead, execution continues from the next line in `Compute` that follows the call to `ValidateInputs`. This is equivalent to lacking the validation. We have patched the issue in GitHub commit 9728c60e136912a12d99ca56e106b7cce7af5986. 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 binary cwise operations that don't require broadcasting (e.g., gradients of binary cwise operations). The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/cwise_ops_common.h#L264) assumes that the two inputs have exactly the same number of elements but does not check that. Hence, when the eigen functor executes it triggers heap OOB reads and undefined behavior due to binding to nullptr. We have patched the issue in GitHub commit 93f428fd1768df147171ed674fee1fc5ab8309ec. 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.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.

While processing the sensors registry configuration file, if inputs are not validated a buffer overflow will occur in Snapdragon Automobile, Snapdragon Mobile, Snapdragon Wear in version MMDM9206, MDM9607, MDM9650, MSM8909W, MSM8996AU, SD 210/SD 212/SD 205, SD 425, SD 430, SD 450, SD 600, SD 615/16/SD 415, SD 617, SD 625, SD 650/52, SD 800, SD 810, SD 820, SD 820A, SD 835, SDA660, SDX20.

In Android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, improper input validation for vdev_map in wma_tbttoffset_update_event_handler(), which is received from firmware, leads to potential buffer overwrite and out of bounds memory read.

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.MatrixSetDiagV*`. 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 ff8894044dfae5568ecbf2ed514c1a37dc394f1b. 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.

Secure application can access QSEE kernel memory through Ontario kernel driver in Snapdragon Automobile, Snapdragon Mobile and Snapdragon Wear in versions MDM9206, MDM9607, MDM9650, MSM8996AU, SD 210/SD 212/SD 205, SD 425, SD 430, SD 450, SD 625, SD 820, SD 820A, SD 835, SD 845, SD 850, SDA660, SDA845, SDX24, SXR1130.