In onSkipButtonClick of FaceEnrollFoldPage.java, there is a possible way to access the file the app cannot access due to Intent Redirect GRANT_URI_PERMISSIONS Attack. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation.

In init_data of , 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 ppcfw_init_secpolicy of ppcfw.c, there is a possible permission bypass due to uninitialized data. This could lead to local escalation of privilege 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 migrateNotificationFilter of NotificationManagerService.java, there is a possible failure to persist notifications settings 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 PMRWritePMPageList of pmr.c, there is a possible out of bounds write 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.

In DevmemXIntUnreserveRange of devicemem_server.c, there is a possible arbitrary code execution 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.

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 config_gov_time_windows of tmu.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.

Out-of-bound Write vulnerability in chunk parsing implementation of libsdffextractor prior to SMR Apr-2023 Release 1 allows local attackers to execute arbitrary code.

In vdec, 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. Patch ID: ALPS08932916; Issue ID: MSV-1551.

In vdec, 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. Patch ID: ALPS08932916; Issue ID: MSV-1550.

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).

In wlan service, 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. Patch ID: ALPS08572601; Issue ID: MSV-1229.

In vdec, 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. Patch ID: ALPS09028313; Issue ID: MSV-1700.

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.

In RGXFWChangeOSidPriority of rgxfwutils.c, there is a possible arbitrary code execution due to a missing bounds check. This could lead to local escalation of privilege in the kernel with no additional execution privileges needed. User interaction is not needed for exploitation.

arch/x86/kernel/entry_64.S in the Linux kernel before 3.17.5 does not properly handle faults associated with the Stack Segment (SS) segment register, which allows local users to gain privileges by triggering an IRET instruction that leads to access to a GS Base address from the wrong space.

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 multiple methods of UserManagerService.java, there is a possible failure to persist or enforce user restrictions due to improper input validation. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is needed for exploitation.

In multiple locations, 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.

In multiple functions of ashmem-dev.cpp, there is a possible missing seal 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.

In convertYUV420Planar16ToY410 of ColorConverter.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.

In ConvertRGBToPlanarYUV of Codec2BufferUtils.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 installExistingPackageAsUser of InstallPackageHelper.java, there is a possible carrier restriction bypass 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 display, there is a possible out of bounds write due to an integer overflow. 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: ALPS10196993; Issue ID: MSV-4807.

In getConfig of SoftVideoDecoderOMXComponent.cpp, there is a possible out of bounds write due to a missing validation check. This could lead to a local non-security issue with no additional execution privileges needed. User interaction is not needed for exploitation.

In gnss driver, there is a possible out of bounds write due to an incorrect 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: ALPS09920033; Issue ID: MSV-3797.

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 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 battery, 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: ALPS10315812; Issue ID: MSV-5534.

In scp, 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: ALPS09625562; Issue ID: MSV-3027.

In smi, 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: ALPS10259774; Issue ID: MSV-5029.

In mminfra, 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: ALPS10267349; Issue ID: MSV-5033.

In display, 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: ALPS10184870; Issue ID: MSV-4729.

In Keymaster, 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-12LAndroid ID: A-173567719

In battery, 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: ALPS10315812; Issue ID: MSV-5533.

In imgsensor, 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: ALPS10089545; Issue ID: MSV-4279.

Out-of-bounds write in libsavscmn prior to Android 15 allows local attackers to execute arbitrary code.

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 kbase_jd_user_buf_pin_pages of mali_kbase_mem.c, there is a possible out of bounds write 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.Product: AndroidVersions: Android kernelAndroid ID: A-210470189References: N/A

In CellBroadcastReceiver, there is a possible path to enable specific cellular features 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-200163477

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 mgm_alloc_page of memory_group_manager.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.Product: AndroidVersions: Android kernelAndroid ID: A-201677538References: N/A

In ril service, there is a possible out of bounds write due to a missing bounds check. This could lead to local denial of service with System execution privileges needed

TensorFlow is an end-to-end open source platform for machine learning. Missing validation between arguments to `tf.raw_ops.Conv3DBackprop*` operations can result in heap buffer overflows. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/4814fafb0ca6b5ab58a09411523b2193fed23fed/tensorflow/core/kernels/conv_grad_shape_utils.cc#L94-L153) assumes that the `input`, `filter_sizes` and `out_backprop` tensors have the same shape, as they are accessed in parallel. 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. The implementation of `tf.io.decode_raw` produces incorrect results and crashes the Python interpreter when combining `fixed_length` and wider datatypes. The implementation of the padded version(https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc) is buggy due to a confusion about pointer arithmetic rules. First, the code computes(https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc#L61) the width of each output element by dividing the `fixed_length` value to the size of the type argument. The `fixed_length` argument is also used to determine the size needed for the output tensor(https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc#L63-L79). This is followed by reencoding code(https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc#L85-L94). The erroneous code is the last line above: it is moving the `out_data` pointer by `fixed_length * sizeof(T)` bytes whereas it only copied at most `fixed_length` bytes from the input. This results in parts of the input not being decoded into the output. Furthermore, because the pointer advance is far wider than desired, this quickly leads to writing to outside the bounds of the backing data. This OOB write leads to interpreter crash in the reproducer mentioned here, but more severe attacks can be mounted too, given that this gadget allows writing to periodically placed locations in memory. 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 cause a heap buffer overflow in `tf.raw_ops.SparseSplit`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/699bff5d961f0abfde8fa3f876e6d241681fbef8/tensorflow/core/util/sparse/sparse_tensor.h#L528-L530) accesses an array element based on a user controlled offset. 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.