An improper input validation in SMC_SRPMB_WSM handler of RPMB ldfw prior to SMR Feb-2022 Release 1 allows arbitrary memory write and code execution.

In all android releases (Android for MSM, Firefox OS for MSM, QRD Android) from CAF using the linux kernel, a buffer over-read can occur In the WMA NDP event handler functions due to lack of validation of input value event_info which is received from FW.

In all android releases(Android for MSM, Firefox OS for MSM, QRD Android) from CAF using the linux kernel, improper input validation can lead to an improper access to already freed up dci client entries while closing dci client.

In Dex2oat of dex2oat.cc, there is a possible way to inject bytecode into an app 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-9 Android-10 Android-11Android ID: A-178055795

In Android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, improper input validation for vent->vdev_id in wma_action_frame_filter_mac_event_handler(), which is received from firmware, leads to arbitrary code execution.

NVIDIA libnvomx contains a possible out of bounds write due to a improper input validation which could lead to local escalation of privilege. This issue is rated as high. Product: Android. Version: N/A. Android: A-66969318. Reference: N-CVE-2017-6281.

In getAppSize of InstalldNativeService.cpp, there is a possible out of bounds read 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-12LAndroid ID: A-220733817

In ccci, there is a possible out of bounds read due to a missing bounds check. This could lead to local information disclosure with System execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS06108658; Issue ID: ALPS06108658.

In skb_headlen of /include/linux/skbuff.h, there is a possible out of bounds read 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.Product: AndroidVersions: Android kernelAndroid ID: A-153881554

In readArgumentList of zygote.java in Android 10, there is a possible command injection 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 multiple functions of URI.java, there is a possible escalation of privilege due to missing validation in the parceling of URI information. This could lead to a local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-10Android ID: A-124526860

In all android releases (Android for MSM, Firefox OS for MSM, QRD Android) from CAF using the linux kernel, while processing a gpt update, an out of bounds memory access may potentially occur.

In Android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, in the function wma_ndp_end_indication_event_handler(), there is no input validation check on a event_info value coming from firmware, which can cause an integer overflow and then leads to potential heap overwrite.

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. A specially crafted TFLite model could trigger an OOB read on heap in the TFLite implementation of `Split_V`(https://github.com/tensorflow/tensorflow/blob/c59c37e7b2d563967da813fa50fe20b21f4da683/tensorflow/lite/kernels/split_v.cc#L99). If `axis_value` is not a value between 0 and `NumDimensions(input)`, then the `SizeOfDimension` function(https://github.com/tensorflow/tensorflow/blob/102b211d892f3abc14f845a72047809b39cc65ab/tensorflow/lite/kernels/kernel_util.h#L148-L150) will access data outside the bounds of the tensor shape 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.

TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.FusedBatchNorm` is vulnerable to a heap buffer overflow. If the tensors are empty, the same implementation can trigger undefined behavior by dereferencing null pointers. The implementation(https://github.com/tensorflow/tensorflow/blob/57d86e0db5d1365f19adcce848dfc1bf89fdd4c7/tensorflow/core/kernels/fused_batch_norm_op.cc) fails to validate that `scale`, `offset`, `mean` and `variance` (the last two only when required) all have the same number of elements as the number of channels of `x`. This results in heap out of bounds reads when the buffers backing these tensors are indexed past their boundary. If the tensors are empty, the validation mentioned in the above paragraph would also trigger and prevent the undefined behavior. 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.

An improper validation vulnerability in FilterProvider prior to SMR Dec-2021 Release 1 allows attackers to write arbitrary files via a path traversal vulnerability.

An improper input validation vulnerability in LDFW prior to SMR Dec-2021 Release 1 allows attackers to perform arbitrary code execution.

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.

An improper validation vulnerability in telephony prior to SMR Dec-2021 Release 1 allows attackers to launch certain activities.

Improper input validation vulnerability in HDCP prior to SMR Nov-2021 Release 1 allows attackers to arbitrary code execution.

In android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, possible buffer overflow or information leak in the functions "sme_set_ft_ies" and "csr_roam_issue_ft_preauth_req" due to incorrect initialization of WEXT callbacks and lack of the checks for buffer size.

In android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, while flashing UBI image, size is not validated for being smaller than minimum header size causing unintialized data access vulnerability.

In createFromParcel of VerifyCredentialResponse.java, there is a possible invalid parcel read due to improper input validation. This could lead to local escalation of privilege if mPayload in writeToParcel were null, with no additional execution privileges needed. User interaction is not needed for exploitation. Product: Android. Versions: 6.0.1, 7.0, 7.1.1, 7.1.2, 8.0, 8.1. Android ID: A-71714464.

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 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 Android before the 2018-06-05 security patch level, NVIDIA TLZ TrustZone contains a possible out of bounds write due to integer overflow which could lead to local escalation of privilege in the TrustZone with no additional execution privileges needed. User interaction is not needed for exploitation. This issue is rated as high. Version: N/A. Android: A-69480285. Reference: N-CVE-2017-6292.

In Android before the 2018-06-05 security patch level, NVIDIA Tegra X1 TZ contains a possible out of bounds write due to missing bounds check which could lead to escalation of privilege from the kernel to the TZ. User interaction is not needed for exploitation. This issue is rated as high. Version: N/A. Android: A-69316825. Reference: N-CVE-2017-6294.

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.

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.

NVIDIA Tegra kernel driver contains a vulnerability in NVMAP where an attacker has the ability to write an arbitrary value to an arbitrary location which may lead to an escalation of privileges. This issue is rated as high.

In Android before the 2018-05-05 security patch level, NVIDIA Tegra X1 TZ contains a vulnerability in Widevine TA where the software writes data past the end, or before the beginning, of the intended buffer, which may lead to escalation of Privileges. This issue is rated as high. Android: A-69377364. Reference: N-CVE-2017-6293.

NVIDIA driver contains a vulnerability where it is possible a use after free malfunction can occur due to improper usage of the list_for_each kernel macro which could enable unauthorized code execution and possibly lead to elevation of privileges. This issue is rated as high. Product: Android. Version: N/A. Android ID: A-38046353. References: N-CVE-2017-6263.

VMware AirWatch Launcher for Android prior to 3.2.2 contains a vulnerability that could allow an escalation of privilege from the launcher UI context menu to native UI functionality and privilege. Successful exploitation of this issue could result in an escalation of privilege.

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, while IPA WAN-driver is processing multiple requests from modem/user-space module, the global variable "num_q6_rule" does not have a mutex lock and thus can be accessed and modified by multiple threads.

NVIDIA Shield TV Experience prior to v8.0, NVIDIA Tegra bootloader contains a vulnerability in nvtboot where the Trusted OS image is improperly authenticated, which may lead to code execution, denial of service, escalation of privileges, and information disclosure, code execution, denial of service, or escalation of privileges

In OatFileAssistant::GenerateOatFile of oat_file_assistant.cc, there is a possible file corruption issue due to an insecure default value. 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-130821293.

NVIDIA Shield TV Experience prior to v8.0, contains a vulnerability in the NVIDIA Games App where it improperly exports an Activity but does not properly restrict which applications can launch the Activity, which may lead to code execution or denial of service.

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.

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.

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.

In msm_isp_prepare_v4l2_buf in Android for MSM, Firefox OS for MSM, and QRD Android before 2017-02-12, an array out of bounds can occur.

NVIDIA Shield TV Experience prior to v8.0, contains a vulnerability in the custom NVIDIA API used in the mount system service where user data could be overridden, which may lead to code execution, denial of service, or information disclosure.

In Android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, improper buffer length calculation in wma_roam_scan_filter() leads to buffer overflow.

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 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.

In all Qualcomm products with Android releases from CAF using the Linux kernel, the IL client may free a buffer OMX Video Encoder Component and then subsequently access the already freed buffer.

In all Qualcomm products with Android releases from CAF using the Linux kernel, multiple values received from firmware are not properly validated in wma_get_ll_stats_ext_buf() and are used to allocate the sizes of buffers and may be vulnerable to integer overflow leading to buffer overflow.

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().

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.