Buffer overflow due to improper validation of buffer size while IPA driver processing to perform read operation in Snapdragon Auto, Snapdragon Compute, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wearables in MDM9150, MDM9607, MDM9650, MSM8909W, MSM8996AU, QCS605, Qualcomm 215, SD 210/SD 212/SD 205, SD 425, SD 427, SD 430, SD 435, SD 439 / SD 429, SD 450, SD 625, SD 632, SD 636, SD 665, SD 675, SD 712 / SD 710 / SD 670, SD 730, SD 820, SD 820A, SD 835, SD 845 / SD 850, SD 855, SDA660, SDM439, SDM630, SDM660, SDX20, SDX24
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.
u'Possible buffer overflow in WIFI hal process due to usage of memcpy without checking length of destination buffer' in Snapdragon Auto, Snapdragon Compute, Snapdragon Industrial IOT, Snapdragon Mobile in QCM4290, QCS4290, QM215, QSM8350, SA6145P, SA6155, SA6155P, SA8155, SA8155P, SC8180X, SC8180XP, SDX55, SDX55M, SM4250, SM4250P, SM6115, SM6115P, SM6125, SM6250, SM6350, SM7125, SM7225, SM7250, SM7250P, SM8150, SM8150P, SM8250, SM8350, SM8350P, SXR2130, SXR2130P
TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation for `tf.raw_ops.ExperimentalDatasetToTFRecord` and `tf.raw_ops.DatasetToTFRecord` can trigger heap buffer overflow and segmentation fault. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/data/experimental/to_tf_record_op.cc#L93-L102) assumes that all records in the dataset are of string type. However, there is no check for that, and the example given above uses numeric types. We have patched the issue in GitHub commit e0b6e58c328059829c3eb968136f17aa72b6c876. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
Improper validation of input when provisioning the HDCP key can lead to memory corruption in Snapdragon Auto, Snapdragon Compute, Snapdragon Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Voice & Music, Snapdragon Wearables
Possible out of bound access due to improper validation of item size and DIAG memory pools data while switching between USB and PCIE interface in Snapdragon Auto, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wearables, Snapdragon Wired Infrastructure and Networking
Improper size validation of QXDM commands can lead to memory corruption in Snapdragon Compute, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile
TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a heap buffer overflow in Eigen implementation of `tf.raw_ops.BandedTriangularSolve`. The implementation(https://github.com/tensorflow/tensorflow/blob/eccb7ec454e6617738554a255d77f08e60ee0808/tensorflow/core/kernels/linalg/banded_triangular_solve_op.cc#L269-L278) calls `ValidateInputTensors` for input validation but fails to validate that the two tensors are not empty. Furthermore, since `OP_REQUIRES` macro only stops execution of current function after setting `ctx->status()` to a non-OK value, callers of helper functions that use `OP_REQUIRES` must check value of `ctx->status()` before continuing. This doesn't happen in this op's implementation(https://github.com/tensorflow/tensorflow/blob/eccb7ec454e6617738554a255d77f08e60ee0808/tensorflow/core/kernels/linalg/banded_triangular_solve_op.cc#L219), hence the validation that is present is also not effective. 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. 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. 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.
An improper length check in APAService prior to SMR Sep-2021 Release 1 results in stack based Buffer Overflow.
Buffer Overflow while processing IOCTL for getting peripheral endpoint information there is no proper validation for input maximum endpoint pair and its size in Snapdragon Auto, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Wearables, Snapdragon Wired Infrastructure and Networking
Buffer overflow when the audio buffer size provided by user is larger than the maximum allowable audio buffer size. in Snapdragon Auto, Snapdragon Compute, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon IoT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wearables in MDM9150, MDM9206, MDM9607, MDM9640, MDM9650, MSM8909W, MSM8996AU, QCS405, QCS605, Qualcomm 215, SD 210/SD 212/SD 205, SD 425, SD 427, SD 430, SD 435, SD 439 / SD 429, SD 450, SD 615/16/SD 415, SD 625, SD 632, SD 636, SD 665, SD 675, SD 712 / SD 710 / SD 670, SD 730, SD 820, SD 820A, SD 835, SD 845 / SD 850, SD 855, SDA660, SDM439, SDM630, SDM660, SDX20, SDX24
An issue was discovered on LG mobile devices with Android OS 9.0 software. The HAL service has a buffer overflow that leads to arbitrary code execution. The LG ID is LVE-SMP-190013 (September 2019).
In Android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, while updating a firmware image, data is read from flash into RAM without checking that the data fits into allotted RAM size.
During listener modified response processing, a buffer overrun occurs due to lack of buffer size verification when updating message buffer with physical address information in Snapdragon Auto, Snapdragon Compute, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon IoT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wearables in APQ8009, APQ8017, APQ8053, APQ8096AU, APQ8098, MDM9206, MDM9207C, MDM9607, MDM9640, MDM9650, MSM8905, MSM8909W, MSM8917, MSM8953, MSM8996AU, Nicobar, QCM2150, QCS405, QCS605, QM215, Rennell, SA6155P, Saipan, SC8180X, SDA660, SDA845, SDM429, SDM429W, SDM439, SDM450, SDM632, SDM670, SDM710, SDM845, SDX20, SDX24, SDX55, SM6150, SM7150, SM8150, SM8250, SXR1130, SXR2130
Kernel memory error in debug module due to improper check of user data length before copying into memory in Snapdragon Auto, Snapdragon Consumer Electronics Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile in APQ8096AU, APQ8098, MSM8996AU, QCN7605, SDM439, SDX24, SM8150
Lack of input validation for data received from user space can lead to OOB access in WLAN in Snapdragon Auto, Snapdragon Consumer Electronics Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon IoT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wearables in MDM9150, MDM9206, MDM9607, MDM9640, MDM9650, MSM8909W, MSM8996AU, QCA6174A, QCA6574AU, QCA9377, QCA9379, SD 210/SD 212/SD 205, SD 425, SD 430, SD 600, SD 615/16/SD 415, SD 625, SD 632, SD 650/52, SD 820A, SDX20
Buffer overflow can occur in wlan module if supported rates or extended rates element length is greater than max rate set length in Snapdragon Auto, Snapdragon Compute, Snapdragon Consumer Electronics Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Voice & Music in APQ8017, APQ8053, APQ8096AU, MDM9206, MDM9207C, MDM9607, MDM9650, MSM8905, MSM8996AU, Nicobar, QCA6174A, QCA6574AU, QCA9377, QCA9379, QCN7605, QCS405, QCS605, SDA845, SDM670, SDM710, SDM845, SDX20, SM6150, SM8150, SM8250, SXR2130
Lack of checking a variable received from driver and populating in Firmware data structure leads to buffer overflow in Snapdragon Auto, Snapdragon Compute, Snapdragon Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wearables in MSM8909W, MSM8996AU, QCS605, Qualcomm 215, SD 210/SD 212/SD 205, SD 425, SD 427, SD 430, SD 435, SD 439 / SD 429, SD 450, SD 625, SD 632, SD 636, SD 665, SD 675, SD 712 / SD 710 / SD 670, SD 730, SD 820, SD 820A, SD 835, SD 845 / SD 850, SD 855, SD 8CX, SDA660, SDM439, SDM630, SDM660, Snapdragon_High_Med_2016, SXR1130
Buffer overflow scenario if the client sends more than 5 io_vec requests to the server in Snapdragon Auto, Snapdragon Compute, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon IoT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wearables in MDM9150, MDM9206, MDM9607, MDM9640, MDM9650, MSM8909W, MSM8996AU, QCS405, QCS605, Qualcomm 215, SD 210/SD 212/SD 205, SD 425, SD 427, SD 430, SD 435, SD 439 / SD 429, SD 450, SD 615/16/SD 415, SD 625, SD 632, SD 636, SD 665, SD 675, SD 712 / SD 710 / SD 670, SD 730, SD 820, SD 820A, SD 835, SD 845 / SD 850, SD 855, SDA660, SDM439, SDM630, SDM660, SDX20, SDX24
Buffer overflow occurs while processing an subsample data length out of range due to lack of user input validation in Snapdragon Auto, Snapdragon Compute, Snapdragon Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wired Infrastructure and Networking in APQ8009, APQ8098, Kamorta, MDM9150, MDM9205, MDM9206, MDM9607, MDM9650, MSM8905, MSM8909, MSM8998, Nicobar, QCS404, QCS405, QCS605, Rennell, SA415M, SC7180, SC8180X, SDA845, SDM670, SDM710, SDM845, SDM850, SDX24, SDX55, SM6150, SM7150, SM8150, SM8250, SXR1130, SXR2130
Possible out of bound write due to lack of boundary check for the maximum size of buffer when sending a DCI packet to remote process in Snapdragon Auto, Snapdragon Compute, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wearables, Snapdragon Wired Infrastructure and Networking
Device misbehavior may be observed when incorrect offset, length or number of buffers is passed by user space in Snapdragon Auto, Snapdragon Compute, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wearables in APQ8053, MDM9206, MDM9207C, MDM9607, MSM8909W, MSM8917, MSM8953, Nicobar, QCM2150, QCS405, QCS605, QM215, Saipan, SC8180X, SDA845, SDM429, SDM429W, SDM439, SDM450, SDM632, SDX24, SDX55, SM6150, SM7150, SM8150, SM8250, SXR1130, SXR2130
u'Buffer overflow seen as the destination buffer size is lesser than the source buffer size in video application' in Snapdragon Compute, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wearables in Bitra, MSM8909W, QCM2150, QCS405, QCS605, Saipan, SC8180X, SDA845, SDM429W, SDX24, SDX55, SM6150, SM7150, SM8150, SM8250, SXR2130
Possible buffer overflow due to lack of offset length check while updating the buffer value in Snapdragon Auto, Snapdragon Compute, Snapdragon Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wearables
u'Stack out of bound issue occurs when making query to DSP capabilities due to wrong assumption was made on determining the buffer size for the DSP attributes' in Snapdragon Auto, Snapdragon Compute, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wearables in Bitra, Kamorta, Rennell, SC7180, SDM845, SM6150, SM7150, SM8150, SM8250, SXR2130
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).
Snapshot of IB can lead to invalid address access due to missing check for size in the related function in Snapdragon Auto, Snapdragon Compute, Snapdragon Consumer Electronics Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wearables in APQ8017, APQ8053, APQ8096AU, APQ8098, MDM9206, MDM9207C, MDM9607, MDM9650, MSM8909, MSM8909W, MSM8917, MSM8920, MSM8937, MSM8940, MSM8953, MSM8996AU, Nicobar, QCN7605, QCS405, QCS605, QM215, SA6155P, SDA660, SDA845, SDM429, SDM439, SDM450, SDM630, SDM632, SDM636, SDM660, SDM670, SDM710, SDM845, SDX20, SDX24, SM6150, SM7150, SM8150, SM8250, SXR2130
Buffer overflow can occur due to usage of wrong datatype and missing length check before copying into buffer in Snapdragon Auto, Snapdragon Compute, Snapdragon Consumer Electronics Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wearables in APQ8017, APQ8053, APQ8096AU, APQ8098, MDM9206, MDM9207C, MDM9607, MDM9640, MDM9650, MSM8909, MSM8909W, MSM8917, MSM8920, MSM8937, MSM8940, MSM8953, MSM8996AU, MSM8998, Nicobar, QCN7605, QCS405, QCS605, QM215, SDA660, SDA845, SDM429, SDM439, SDM450, SDM630, SDM632, SDM636, SDM660, SDM670, SDM710, SDM845, SDX20, SDX24, SM6150, SM7150, SM8150
ADSP can be compromised since it`s a general-purpose CPU processing untrusted data in Snapdragon Auto, Snapdragon Compute, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon IoT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wearables, Snapdragon Wired Infrastructure and Networking in IPQ4019, IPQ8064, IPQ8074, MDM9150, MDM9206, MDM9607, MDM9640, MDM9650, MSM8909W, MSM8996AU, QCS405, QCS605, Qualcomm 215, SD 210/SD 212/SD 205, SD 425, SD 427, SD 430, SD 435, SD 439 / SD 429, SD 450, SD 615/16/SD 415, SD 625, SD 632, SD 636, SD 665, SD 675, SD 712 / SD 710 / SD 670, SD 730, SD 820, SD 820A, SD 835, SD 845 / SD 850, SD 855, SDA660, SDM439, SDM630, SDM660, SDX20, SDX24
Missing length check before copying the data from kernel space to userspace through the copy function can lead to buffer overflow in some cases in Snapdragon Auto, Snapdragon Compute, Snapdragon Consumer Electronics Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wearables in APQ8009, APQ8053, APQ8096AU, MSM8909W, MSM8917, MSM8953, Nicobar, QCN7605, QCS405, QCS605, QM215, Rennell, Saipan, SC8180X, SDA845, SDM429, SDM429W, SDM439, SDM450, SDM632, SDM670, SDM710, SDM845, SDX24, SDX55, SM6150, SM7150, SM8150, SM8250, SXR1130, SXR2130
u'Possible buffer overflow in WIFI hal process due to copying data without checking the buffer length' in Snapdragon Auto, Snapdragon Compute, Snapdragon Industrial IOT, Snapdragon Mobile in QCM4290, QCS4290, QM215, QSM8350, SA6145P, SA6155, SA6155P, SA8155, SA8155P, SC8180X, SC8180XP, SDX55, SDX55M, SM4250, SM4250P, SM6115, SM6115P, SM6125, SM6250, SM6350, SM7125, SM7225, SM7250, SM7250P, SM8150, SM8150P, SM8250, SM8350, SM8350P, SXR2130, SXR2130P
u'Possible out of bound array write in rxdco cal utility due to lack of array bound check' in Snapdragon Compute, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile in MSM8998, QCS605, SDA845, SDM630, SDM636, SDM660, SDM670, SDM710, SDM845, SDM850, SXR1130
An issue was discovered on Samsung mobile devices with P(9.0) (Exynos chipsets) software. The S.LSI Wi-Fi drivers have a buffer overflow. The Samsung ID is SVE-2020-16906 (May 2020).
An improper boundary check in RPMB ldfw prior to SMR Feb-2022 Release 1 allows arbitrary memory write and code execution.
u'A buffer overflow could occur if the API is improperly used due to UIE init does not contain a buffer size a param' in Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Wired Infrastructure and Networking in Agatti, Kamorta, QCS404, QCS605, SDA845, SDM670, SDM710, SDM845, SXR1130
u'Possible buffer overflow in MHI driver due to lack of input parameter validation of EOT events received from MHI device side' in Snapdragon Auto, Snapdragon Compute, Snapdragon Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wearables, Snapdragon Wired Infrastructure and Networking in Agatti, APQ8009, Bitra, IPQ4019, IPQ5018, IPQ6018, IPQ8064, IPQ8074, Kamorta, MDM9607, MSM8917, MSM8953, Nicobar, QCA6390, QCM2150, QCS404, QCS405, QCS605, QM215, QRB5165, Rennell, SA415M, SA515M, SA6155P, SA8155P, Saipan, SC8180X, SDM429, SDM429W, SDM439, SDM450, SDM632, SDM710, SDM845, SDX55, SM6150, SM7150, SM8150, SM8250, SXR2130
TensorFlow is an open source platform for machine learning. In affected versions the shape inference function for `Transpose` is vulnerable to a heap buffer overflow. This occurs whenever `perm` contains negative elements. The shape inference function does not validate that the indices in `perm` are all valid. 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. 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.
A possible stack-based buffer overflow vulnerability in Widevine trustlet prior to SMR Oct-2021 Release 1 allows arbitrary code execution.
A possible buffer overflow vulnerability in NPU driver prior to SMR JUN-2021 Release 1 allows arbitrary memory write and code execution.
In IoT Devices SDK, there is an implementation of calloc() that doesn't have a length check. An attacker could pass in memory objects larger than the buffer and wrap around to have a smaller buffer than required, allowing the attacker access to the other parts of the heap. We recommend upgrading the Google Cloud IoT Device SDK for Embedded C used to 1.0.3 or greater.
Possible buffer overflow due to lack of length check of source and destination buffer before copying in Snapdragon Auto, Snapdragon Compute, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Voice & Music
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.
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.
Improper authorization involving a fuse in TrustZone in snapdragon automobile, snapdragon mobile and snapdragon wear in versions MDM9206, MDM9607, MSM8996AU, SD 210/SD 212/SD 205, SD 410/12, SD 425, SD 427, SD 430, SD 435, SD 439 / SD 429, SD 450, SD 615/16/SD 415, SD 625, SD 632, SD 636, SD 650/52, SD 810, SD 820, SD 820A, SD 835, SDA660, SDM439, SDM630, SDM660, SDX24, Snapdragon_High_Med_2016.
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.