In finalize of AssetManager.java, there is possible memory corruption due to a double 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-8.0 Android-8.1 Android-9 Android-10Android ID: A-144028297

In HidRawSensor::batch of HidRawSensor.cpp, there is a possible out of bounds write due to an unexpected switch fallthrough. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-8.0 Android-8.1 Android-9 Android-10Android ID: A-144040966

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 gps, 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. Patch ID: ALPS07573237; Issue ID: ALPS07573237.

In wl_update_hidden_ap_ie() of wl_cfgscan.c, there is a possible out of bounds write 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.

In setUpdatableDriverPath of GpuService.cpp, there is a possible memory corruption 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-11Android ID: A-162383705

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

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

In growData of Parcel.cpp, there is a possible out of bounds 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.

In noteAtomLogged of StatsdStats.cpp, 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-10 Android-11 Android-9Android ID: A-187957589

In sound_trigger_event_alloc of platform.h, there is a possible out of bounds write due to a heap buffer 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-167663878

In memory management driver, 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 SoCAndroid ID: A-183464866

In iaxxx_calc_i2s_div of iaxxx-codec.c, there is a possible hardware port write with user controlled data 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-180950209

In parseExclusiveStateAnnotation of LogEvent.cpp, there is a possible out of bounds write due to a heap buffer 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-11Android ID: A-174488848

In mm_GetMobileIdIndexForNsUpdate of mm_GmmPduCodec.c, there is a possible out of bounds 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.

In DevmemValidateFlags of devicemem_server.c , there is a possible out of bounds write due to memory corruption. 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 P(9.0) (Exynos chipsets) software. The Wi-Fi kernel drivers have a stack overflow. The Samsung IDs are SVE-2019-14965, SVE-2019-14966, SVE-2019-14968, SVE-2019-14969, SVE-2019-14970, SVE-2019-14980, SVE-2019-14981, SVE-2019-14982, SVE-2019-14983, SVE-2019-14984, SVE-2019-15122, SVE-2019-15123 (November 2019).

In load_logging_config of qmi_vs_service.cc, there is a possible out of bounds write due to a heap buffer 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-9 Android-10Android ID: A-139148442

In String16 of String16.cpp, there is a possible out of bounds write due to an integer overflow. This could lead to local escalation of privilege in an unprivileged process with no additional execution privileges needed. User interaction is not needed for exploitation.

Heap-based buffer overflow in the wcnss_wlan_write function in drivers/net/wireless/wcnss/wcnss_wlan.c in the wcnss_wlan device driver for the Linux kernel 3.x, as used in Qualcomm Innovation Center (QuIC) Android contributions for MSM devices and other products, allows attackers to cause a denial of service or possibly have unspecified other impact by writing to /dev/wcnss_wlan with an unexpected amount of data.

In Exynos_parsing_user_data_registered_itu_t_t35 of VendorVideoAPI.cpp, there is a possible out of bounds 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.

In prepare_response_locked of lwis_transaction.c, there is a possible out of bounds write 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.

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 _PMRLogicalOffsetToPhysicalOffset of the PowerVR kernel driver, 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 SoCAndroid ID: A-246824784

An issue was discovered on LG mobile devices with Android OS 10 software. When a dual-screen configuration is supported, the device does not lock upon disconnection of a call with the cover closed. The LG ID is LVE-SMP-200027 (December 2020).

In DevmemIntChangeSparse2 of devicemem_server.c, there is a possible way to achieve arbitrary code execution 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.

The vold volume manager daemon on Android 3.0 and 2.x before 2.3.4 trusts messages that are received from a PF_NETLINK socket, which allows local users to execute arbitrary code and gain root privileges via a negative index that bypasses a maximum-only signed integer check in the DirectVolume::handlePartitionAdded method, which triggers memory corruption, as demonstrated by Gingerbreak.

In mayAdminGrantPermission of AdminRestrictedPermissionsUtils.java, there is a possible way to access the microphone 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.

In multiple locations, there is a possible permission bypass due to a confused deputy. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is needed for exploitation.

In scheme of Uri.java, there is a possible way to craft a malformed Uri object 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.

A local attacker, as a different local user, may be able to send a HTTP request to 127.0.0.1:10000 after the user (typically a developer) manually invoked the ./tools/run-dev-server script. It is recommended to upgrade to any version beyond 24.2

In setTransactionState of SurfaceFlinger.cpp, there is a possible way to change protected display attributes due to a logic error in the code. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation.

In bindAndGetCallIdentification of CallScreeningServiceHelper.java, there is a possible way to maintain a while-in-use permission in the background due to a permissions bypass. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is needed for exploitation.

Invalid memory access in Sentencepiece versions less than 0.2.1 when using a vulnerable model file, which is not created in the normal training procedure.

An issue was discovered on LG mobile devices with Android OS 8.0, 8.1, 9.0, and 10 software. There is a WebView SSL error-handler vulnerability. The LG ID is LVE-SMP-200026 (December 2020).

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

PendingIntent hijacking vulnerability in Weather application prior to SMR Mar-2022 Release 1 allows local attackers to perform unauthorized action without permission via hijacking the PendingIntent.

In readArguments of CallSubjectDialog.java, there is a possible way to trick the user to call the wrong phone number 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-11 Android-12 Android-12LAndroid ID: A-218341397

In multiple locations, there is a possible permissions bypass due to a missing null check. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation.

In DevmemXIntMapPages of devicemem_server.c, there is a possible use-after-free due to a logic error in the code. This could lead to local escalation of privilege in the kernel with no additional execution privileges needed. User interaction is not needed for exploitation.

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 an attacker can trigger undefined behavior, integer overflows, segfaults and `CHECK`-fail crashes if they can change saved checkpoints from outside of TensorFlow. This is because the checkpoints loading infrastructure is missing validation for invalid file formats. The fixes will be included in TensorFlow 2.7.0. We will also cherrypick these commits 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.

In multiple functions of AppOpsService.java, there is a possible way for unprivileged apps to read their own restrictRead app-op states due to a logic error in the code. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation.

TensorFlow is an open source platform for machine learning. In affected versions TensorFlow's Grappler optimizer has a use of unitialized variable. If the `train_nodes` vector (obtained from the saved model that gets optimized) does not contain a `Dequeue` node, then `dequeue_node` is left unitialized. 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 several TensorFlow operations are missing validation for the shapes of the tensor arguments involved in the call. Depending on the API, this can result in undefined behavior and segfault or `CHECK`-fail related crashes but in some scenarios writes and reads from heap populated arrays are also possible. We have discovered these issues internally via tooling while working on improving/testing GPU op determinism. As such, we don't have reproducers and there will be multiple fixes for these issues. These fixes will be included in TensorFlow 2.7.0. We will also cherrypick these commits 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 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.

In addPreferencesForType of AccountTypePreferenceLoader.java, there is a possible way to disable apps for other users due to a confused deputy. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation.

In setTransactionState of SurfaceFlinger.cpp, there is a possible way to perform tapjacking due to a logic error in the code. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation.

TensorFlow is an open source platform for machine learning. In affected versions TensorFlow's `saved_model_cli` tool is vulnerable to a code injection as it calls `eval` on user supplied strings. This can be used by attackers to run arbitrary code on the plaform where the CLI tool runs. However, given that the tool is always run manually, the impact of this is not severe. We have patched this by adding a `safe` flag which defaults to `True` and an explicit warning for users. 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.