In all android releases (Android for MSM, Firefox OS for MSM, QRD Android) from CAF using the linux kernel, when WLAN FW has not filled the vdev id correctly in stats events then WLAN host driver tries to access interface array without proper bound check which can lead to invalid memory access and as a side effect kernel panic or page fault.

In the broadcast definition in AndroidManifest.xml, there is a possible way to set the A2DP bluetooth device connection state 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-12Android ID: A-196858999

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 wifi_item_edit_content of styles.xml , there is a possible FRP bypass due to Missing check for FRP state. 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) 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).

In all android releases(Android for MSM, Firefox OS for MSM, QRD Android) from CAF using the linux kernel, Heap memory was accessed after it was freed

In all android releases(Android for MSM, Firefox OS for MSM, QRD Android) from CAF using the linux kernel, a partition name-check variable is not reset for every iteration which may cause improper termination in the META image.

In all android releases(Android for MSM, Firefox OS for MSM, QRD Android) from CAF using the linux kernel, there is a security concern with default privileged access to ADB and debug-fs.

In all android releases(Android for MSM, Firefox OS for MSM, QRD Android) from CAF using the linux kernel, improper access control can lead to device node and executable to be run from /data/ which presents a potential issue.

In all android releases (Android for MSM, Firefox OS for MSM, QRD Android) from CAF using the linux kernel, possibility of invalid memory access while processing driver command in WLAN function.

In all android releases(Android for MSM, Firefox OS for MSM, QRD Android) from CAF using the linux kernel, improper access control can lead to device node and executable to be run from /systemrw/ which presents a potential security.

In all android releases(Android for MSM, Firefox OS for MSM, QRD Android) from CAF using the linux kernel, Null pointer dereference vulnerability may occur due to missing NULL assignment in NAT module of freed pointer.

In all android releases(Android for MSM, Firefox OS for MSM, QRD Android) from CAF using the linux kernel, Exposing the hashed content in /etc/passwd may lead to security issue.

In all android releases(Android for MSM, Firefox OS for MSM, QRD Android) from CAF using the linux kernel, Use-after-free issue in heap while loading audio effects config in audio effects factory.

In all android releases(Android for MSM, Firefox OS for MSM, QRD Android) from CAF using the linux kernel, improper access control can lead to device node and executable to be run from /cache/ which presents a potential issue.

In all android releases (Android for MSM, Firefox OS for MSM, QRD Android) from CAF using the linux kernel, while calling IPA_IOC_MDFY_RT_RULE IPA IOCTL, header entry is not checked before use. If IPA_IOC_MDFY_RT_RULE IOCTL called for header entries formerly deleted, a Use after free condition will occur.

An issue was discovered on Samsung mobile devices with Q(10.0) (Exynos990 chipsets) software. The S3K250AF Secure Element CC EAL 5+ chip allows attackers to execute arbitrary code and obtain sensitive information via a buffer overflow. The Samsung ID is SVE-2020-18632 (November 2020).

In all android releases (Android for MSM, Firefox OS for MSM, QRD Android) from CAF using the linux kernel, buffer overflow may occur when payload size is extremely large.

There exists an insecure default user permission in Google Cloud Migrate to containers from version 1.1.0 to 1.2.2 Windows installs. A local "m2cuser" was greated with administrator privileges. This posed a security risk if the "analyze" or "generate" commands were interrupted or skipping the action to delete the local user “m2cuser”. We recommend upgrading to 1.2.3 or beyond

In multiple locations, there is a possible way to hijack the Launcher app 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 multiple locations, there is a possible way to overlay the installation confirmation dialog due to a tapjacking/overlay attack. 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 way that avdtp and avctp channels could be unencrypted due to a logic error in the code. This could lead to local escalation of privilege with User execution privileges needed. User interaction is not needed for exploitation.

TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPoolGradWithArgmax` can cause reads outside of bounds of heap allocated data if attacker supplies specially crafted inputs. The implementation(https://github.com/tensorflow/tensorflow/blob/31bd5026304677faa8a0b77602c6154171b9aec1/tensorflow/core/kernels/image/draw_bounding_box_op.cc#L116-L130) assumes that the last element of `boxes` input is 4, as required by [the op](https://www.tensorflow.org/api_docs/python/tf/raw_ops/DrawBoundingBoxesV2). Since this is not checked attackers passing values less than 4 can write outside of bounds of heap allocated objects and cause memory corruption. If the last dimension in `boxes` is less than 4, accesses similar to `tboxes(b, bb, 3)` will access data outside of bounds. Further during code execution there are also writes to these indices. 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 getLockTaskLaunchMode of ActivityRecord.java, there is a possible way for any app to start in Lock Task Mode due to a permissions bypass. 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-158833495

Tunnelblick 3.3beta20 and earlier relies on argv[0] to determine the name of an appropriate (1) kernel module pathname or (2) executable file pathname, which allows local users to gain privileges via an execl system call.

In onCreate of HandleApiCalls.java, there is a possible permission bypass due to a confused deputy. This could lead to local escalation of privilege that allows an app to set or dismiss the alarm with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-11Android ID: A-150612638

TensorFlow is an end-to-end open source platform for machine learning. A specially crafted TFLite model could trigger an OOB write on heap in the TFLite implementation of `ArgMin`/`ArgMax`(https://github.com/tensorflow/tensorflow/blob/102b211d892f3abc14f845a72047809b39cc65ab/tensorflow/lite/kernels/arg_min_max.cc#L52-L59). If `axis_value` is not a value between 0 and `NumDimensions(input)`, then the condition in the `if` is never true, so code writes past the last valid element of `output_dims->data`. 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.

Tunnelblick 3.3beta20 and earlier relies on a test for specific ownership and permissions to determine whether a program can be safely executed, which allows local users to bypass intended access restrictions and gain privileges via a (1) user-mountable image or (2) network share.

In android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, in a qbt1000 ioctl handler, an incorrect buffer size check has an integer overflow vulnerability potentially leading to a buffer overflow.

In all android releases(Android for MSM, Firefox OS for MSM, QRD Android) from CAF using the linux kernel, There is no synchronization between msm_vb2 buffer operations which can lead to use after free.

In Android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, while flashing a meta image, an integer overflow can occur, if user-defined image offset and size values are too large.

In restartWrite of Parcel.cpp, there is a possible memory corruption 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-11Android ID: A-157066561

In all Android releases from CAF using the Linux kernel, while processing a voice SVC request which is nonstandard by specifying a payload size that will overflow its own declared size, an out of bounds memory copy occurs.

In function msm_pcm_playback_close() in all Android releases from CAF using the Linux kernel, prtd is assigned substream->runtime->private_data. Later, prtd is freed. However, prtd is not sanitized and set to NULL, resulting in a dangling pointer. There are other functions that access the same memory (substream->runtime->private_data) with a NULL check, such as msm_pcm_volume_ctl_put(), which means this freed memory could be used.

In wl_notify_gscan_event of wl_cfgscan.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.

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 cameraisp, there is a possible out of bounds write due to a missing bounds check. This could lead to local escalation of privilege if a malicious actor has already obtained the System privilege. User interaction is not needed for exploitation. Patch ID: ALPS10351676; Issue ID: MSV-5733.

In imgsys, there is a possible out of bounds write due to a missing bounds check. This could lead to local escalation of privilege if a malicious actor has already obtained the System privilege. User interaction is not needed for exploitation. Patch ID: ALPS10363246; Issue ID: MSV-5779.

In Android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, the qbt1000 driver implements an alternative channel for usermode applications to talk to QSEE applications.

In Android before the 2018-06-05 security patch level, NVIDIA TLK TrustZone contains a possible out of bounds write due to an integer overflow which could lead to local escalation of privilege with no additional execution privileges needed. User interaction not needed for exploitation. This issue is rated as high. Version: N/A. Android: A-69559414. Reference: N-CVE-2017-6290.

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.

NVIDIA libnvmmlite_audio.so contains an elevation of privilege vulnerability when running in media server which may cause an out of bounds write and could lead to local code execution in a privileged process. This issue is rated as high. Product: Android. Version: N/A. Android: A-65023166. Reference: N-CVE-2017-6279.

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.

NVIDIA libnvmmlite_audio.so contains an elevation of privilege vulnerability when running in media server which may cause an out of bounds write and could lead to local code execution in a privileged process. This issue is rated as high. Product: Android. Version: N/A. Android: A-38027496. Reference: N-CVE-2017-6258.

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 shape inference code for the `Cudnn*` operations in TensorFlow can be tricked into accessing invalid memory, via a heap buffer overflow. This occurs because the ranks of the `input`, `input_h` and `input_c` parameters are not validated, but code assumes they have certain values. 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 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 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.

NVIDIA libnvomx contains a possible out of bounds write due to a missing bounds check which could lead to local escalation of privilege. This issue is rated as high. Product: Android. Version: N/A. Android: A-64893247. Reference: N-CVE-2017-6286.