In NFC, 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 and a Firmware compromise needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-11Android ID: A-122361504

In SetData of btm_ble_multi_adv.cc, there is a possible out-of-bound write due to an incorrect bounds 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-10Android ID: A-123292010

In convertHidlNanDataPathInitiatorRequestToLegacy, and convertHidlNanDataPathIndicationResponseToLegacy of hidl_struct_util.cpp, 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-10Android ID: A-143789898

In crus_afe_get_param of msm-cirrus-playback.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.Product: AndroidVersions: Android kernelAndroid ID: A-148189280

In iorap, there is a possible memory corruption due to a use after free. This could lead to local escalation of privilege and code execution with System execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-11Android ID: A-150331085

In blk_mq_queue_tag_busy_iter of blk-mq-tag.c, there is a possible use after free due to improper locking. 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-151939299

In WifiNetworkSuggestionsManager of WifiNetworkSuggestionsManager.java, there is a possible permission revocation 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-10Android ID: A-146642727

In the Audio HAL, 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-11Android ID: A-143787559

In set_outbound_iatu of abc-pcie.c, 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: Android Versions: Android kernel Android ID: A-144168326

In phNxpNciHal_send_ese_hal_cmd of phNxpNciHal_ext.cc, there is a possible out of bounds write due to a missing bounds check. This could lead to local escalation of privilege with User execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-10Android ID: A-139736386

In generatePackageInfo of PackageManagerService.java, there is a possible permissions bypass due to an incorrect permission check. This could lead to local escalation of privilege that allows instant apps access to permissions not allowed for instant apps, with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-8.1 Android-9 Android-10 Android-11 Android-8.0Android ID: A-140256621

In tzdata there is possible memory corruption due to a mismatch between allocation and deallocation functions. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation. Product: AndroidVersions: Android-10Android ID: A-113039724

In wifilogd, 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. Product: AndroidVersions: Android-10Android ID: A-113655028

In the Android kernel in the mnh driver 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.

In the Android kernel in unifi and r8180 WiFi drivers 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 Bluetooth, 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-10Android ID: A-113572342

Insufficient restrictions on what can be done with Apple Events in Google Chrome on macOS prior to 72.0.3626.81 allowed a local attacker to execute JavaScript via Apple Events.

Unprotected component vulnerability in DeviceSearchTrampoline in SecSettingsIntelligence prior to SMR Jun-2022 Release 1 allows local attackers to launch activities of SecSettingsIntelligence.

Android images for T210 provided by NVIDIA contain a vulnerability in BROM, where failure to limit access to AHB-DMA when BROM fails may allow an unprivileged attacker with physical access to cause denial of service or impact integrity and confidentiality beyond the security scope of BROM.

NVIDIA Linux distributions contain a vulnerability in nvmap ioctl, which allows any user with a local account to exploit a use-after-free condition, leading to code privilege escalation, loss of confidentiality and integrity, or denial of service.

In isPackageDeviceAdminOnAnyUser of PackageManagerService.java, there is a possible permissions bypass due to a missing permissions check. This could lead to local escalation of privilege, with no additional permissions required. User interaction is not needed for exploitation. Product: Android. Versions: Android-7.0 Android-7.1.1 Android-7.1.2 Android-8.0 Android-8.1 Android-9. Android ID: A-128599183

An issue was discovered on LG mobile devices with Android OS 8.0 and 8.1 software for the DTAG carrier. RILD in the radio layer uses an uninitialized variable. The LG ID is LVE-SMP-180013 (January 2019).

In startActivityMayWait of ActivityStarter.java, there is a possible incorrect Activity launch due to an incorrect 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-7.1.1 Android-7.1.2 Android-8.0 Android-8.1 Android-9Android ID: A-123013720

An issue was discovered on Samsung mobile devices with N(7.x), O(8.x), and P(9.0) software. There is local SQL injection in the Story Video Editor Content Provider. The Samsung ID is SVE-2019-14062 (July 2019).

An issue was discovered on Samsung mobile devices with N(7.x), O(8.x), and P(9.0) software. There is local SQL injection in the Wi-Fi history Content Provider. The Samsung ID is SVE-2019-14061 (August 2019).

An issue was discovered on Samsung mobile devices with P(9.0) software. There is a heap overflow in the knox_kap driver. The Samsung ID is SVE-2019-14857 (November 2019).

A use-after-free in binder.c allows an elevation of privilege from an application to the Linux Kernel. No user interaction is required to exploit this vulnerability, however exploitation does require either the installation of a malicious local application or a separate vulnerability in a network facing application.Product: AndroidAndroid ID: A-141720095

In execTransact of Binder.java in Android 7.1.1, 7.1.2, 8.0, 8.1, and 9, there is a possible local execution of arbitrary code in a privileged process due to a memory overwrite. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation.

An issue was discovered on Samsung mobile devices with L(5.0/5.1) and M(6.0) (with Fingerprint support) software. The check of an application's signature can be bypassed during installation. The Samsung ID is SVE-2016-5923 (June 2016).

In rw_t3t_act_handle_check_ndef_rsp of rw_t3t.cc, there is a possible out-of-bound 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. Product: Android. Versions: Android-7.0 Android-7.1.1 Android-7.1.2 Android-8.0 Android-8.1 Android-9. Android ID: A-120502559.

In create_hdr of dnssd_clientstub.c, 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: Android-9. Android ID: A-121327565.

In updateAssistMenuItems of Editor.java, there is a possible escape from the Setup Wizard due to a missing permission check. This could lead to local escalation of privilege and FRP bypass with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-8.0Android ID: A-120866126

An issue was discovered on Samsung mobile devices with JBP(4.2) and KK(4.4) (Marvell chipsets) software. The ACIPC-MSOCKET driver allows local privilege escalation via a stack-based buffer overflow. The Samsung ID is SVE-2016-5393 (April 2016).

TensorFlow is an end-to-end open source platform for machine learning. The fix for CVE-2020-15209(https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15209) missed the case when the target shape of `Reshape` operator is given by the elements of a 1-D tensor. As such, the fix for the vulnerability(https://github.com/tensorflow/tensorflow/blob/9c1dc920d8ffb4893d6c9d27d1f039607b326743/tensorflow/lite/core/subgraph.cc#L1062-L1074) allowed passing a null-buffer-backed tensor with a 1D shape. 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 by providing an invalid `permutation` to `tf.raw_ops.SparseMatrixSparseCholesky`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/080f1d9e257589f78b3ffb75debf584168aa6062/tensorflow/core/kernels/sparse/sparse_cholesky_op.cc#L85-L86) fails to properly validate the input arguments. Although `ValidateInputs` is called and there are checks in the body of this function, the code proceeds to the next line in `ValidateInputs` since `OP_REQUIRES`(https://github.com/tensorflow/tensorflow/blob/080f1d9e257589f78b3ffb75debf584168aa6062/tensorflow/core/framework/op_requires.h#L41-L48) is a macro that only exits the current function. Thus, the first validation condition that fails in `ValidateInputs` will cause an early return from that function. However, the caller will continue execution from the next line. The fix is to either explicitly check `context->status()` or to convert `ValidateInputs` to return a `Status`. 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.MaxPoolGrad` is vulnerable to a heap buffer overflow. The implementation(https://github.com/tensorflow/tensorflow/blob/ab1e644b48c82cb71493f4362b4dd38f4577a1cf/tensorflow/core/kernels/maxpooling_op.cc#L194-L203) fails to validate that indices used to access elements of input/output arrays are valid. Whereas accesses to `input_backprop_flat` are guarded by `FastBoundsCheck`, the indexing in `out_backprop_flat` can result in OOB access. 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 division by 0 in `tf.raw_ops.Conv2DBackpropInput`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/b40060c9f697b044e3107917c797ba052f4506ab/tensorflow/core/kernels/conv_grad_input_ops.h#L625-L655) does a division by a quantity that is controlled by the caller. 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 `Prepare` step of the `SpaceToDepth` TFLite operator does not check for 0 before division(https://github.com/tensorflow/tensorflow/blob/5f7975d09eac0f10ed8a17dbb6f5964977725adc/tensorflow/lite/kernels/space_to_depth.cc#L63-L67). An attacker can craft a model such that `params->block_size` would be zero. 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 TFLite computation for size of output after padding, `ComputeOutSize`(https://github.com/tensorflow/tensorflow/blob/0c9692ae7b1671c983569e5d3de5565843d500cf/tensorflow/lite/kernels/padding.h#L43-L55), does not check that the `stride` argument is not 0 before doing the division. Users can craft special models such that `ComputeOutSize` is called with `stride` set to 0. 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. An attacker can cause a heap buffer overflow to occur in `Conv2DBackpropFilter`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/1b0296c3b8dd9bd948f924aa8cd62f87dbb7c3da/tensorflow/core/kernels/conv_grad_filter_ops.cc#L495-L497) computes the size of the filter tensor but does not validate that it matches the number of elements in `filter_sizes`. Later, when reading/writing to this buffer, code uses the value computed here, instead of the number of elements in the tensor. 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 write outside the bounds of heap allocated arrays by passing invalid arguments to `tf.raw_ops.Dilation2DBackpropInput`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/afd954e65f15aea4d438d0a219136fc4a63a573d/tensorflow/core/kernels/dilation_ops.cc#L321-L322) does not validate before writing to the output array. The values for `h_out` and `w_out` are guaranteed to be in range for `out_backprop` (as they are loop indices bounded by the size of the array). However, there are no similar guarantees relating `h_in_max`/`w_in_max` and `in_backprop`. 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.

Improper sanitization of incoming intent in Samsung Contacts prior to SMR JUN-2021 Release 1 allows local attackers to copy or overwrite arbitrary files with Samsung Contacts privilege.

The Security Team discovered an integer overflow bug that allows an attacker with code execution to issue memory cache invalidation operations on pages that they don’t own, allowing them to control kernel memory from userspace. We recommend upgrading to kernel version 4.1 or beyond.

NVIDIA SHIELD TV, all versions prior to 8.2.2, contains a vulnerability in the implementation of the RPMB command status, in which an attacker can write to the Write Protect Configuration Block, which may lead to denial of service or escalation of privileges.

In enqueueNotificationInternal of NotificationManagerService.java, there is a possible way to run a foreground service without showing a notification due to improper input validation. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-10 Android-11Android ID: A-191981182

In setClientStateLocked of SurfaceFlinger.cpp, there is a possible out of bounds write 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-12Android ID: A-193034683

Inappropriate implementation in installer in Google Chrome prior to 80.0.3987.87 allowed a local attacker to execute arbitrary code via a crafted registry entry.

Unquoted Windows search path vulnerability in the GoogleChromeDistribution::DoPostUninstallOperations function in installer/util/google_chrome_distribution.cc in the uninstall-survey feature in Google Chrome before 40.0.2214.91 allows local users to gain privileges via a Trojan horse program in the %SYSTEMDRIVE% directory, as demonstrated by program.exe, a different vulnerability than CVE-2015-1205.

An issue was discovered on Samsung mobile devices with P(9.0) and Q(10.0) (Exynos 980, 9820, and 9830 chipsets) software. The NPU driver allows attackers to execute arbitrary code because of unintended write and read operations on memory. The Samsung ID is SVE-2020-18610 (November 2020).