TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPool3DGradGrad` is vulnerable to a heap buffer overflow. The implementation(https://github.com/tensorflow/tensorflow/blob/596c05a159b6fbb9e39ca10b3f7753b7244fa1e9/tensorflow/core/kernels/pooling_ops_3d.cc#L694-L696) does not check that the initialization of `Pool3dParameters` completes successfully. Since the constructor(https://github.com/tensorflow/tensorflow/blob/596c05a159b6fbb9e39ca10b3f7753b7244fa1e9/tensorflow/core/kernels/pooling_ops_3d.cc#L48-L88) uses `OP_REQUIRES` to validate conditions, the first assertion that fails interrupts the initialization of `params`, making it contain invalid data. In turn, this might cause a heap buffer overflow, depending on default initialized values. 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. 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.

TensorFlow is an end-to-end open source platform for machine learning. The validation in `tf.raw_ops.QuantizeAndDequantizeV2` allows invalid values for `axis` argument:. The validation(https://github.com/tensorflow/tensorflow/blob/eccb7ec454e6617738554a255d77f08e60ee0808/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L74-L77) uses `||` to mix two different conditions. If `axis_ < -1` the condition in `OP_REQUIRES` will still be true, but this value of `axis_` results in heap underflow. This allows attackers to read/write to other data on the heap. 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.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.

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.

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.

TensorFlow is an end-to-end open source platform for machine learning. An attacker can write outside the bounds of heap allocated arrays by passing invalid arguments to `tf.raw_ops.Dilation2DBackpropInput`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/afd954e65f15aea4d438d0a219136fc4a63a573d/tensorflow/core/kernels/dilation_ops.cc#L321-L322) does not validate before writing to the output array. The values for `h_out` and `w_out` are guaranteed to be in range for `out_backprop` (as they are loop indices bounded by the size of the array). However, there are no similar guarantees relating `h_in_max`/`w_in_max` and `in_backprop`. 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 libmediadrm, there is an out-of-bounds write due to improper input validation. This could lead to local elevation of privileges with no additional execution privileges needed. User interaction is not needed for exploitation. Product: Android. Versions: 8.0, 8.1. Android ID: A-67962232.

TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.AvgPool3DGrad` is vulnerable to a heap buffer overflow. The implementation(https://github.com/tensorflow/tensorflow/blob/d80ffba9702dc19d1fac74fc4b766b3fa1ee976b/tensorflow/core/kernels/pooling_ops_3d.cc#L376-L450) assumes that the `orig_input_shape` and `grad` tensors have similar first and last dimensions but does not check that this assumption is validated. 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 DisplayFtmItem in the bootloader, there is an out-of-bounds write due to reading a string without verifying that it's null-terminated. This could lead to a secure boot bypass and a local elevation of privilege enabling code execution as a privileged process with no additional execution privileges needed. User interaction is not needed for exploitation. Product: Android. Versions: Android kernel. Android ID: A-68269077.

In the onQueueFilled function of SoftAVCDec, there is a possible out-of-bounds write due to a use after free if a bad header causes the decoder to get caught in a loop while another thread frees the memory it's accessing. This could lead to a local elevation of privilege enabling code execution as a privileged process with no additional execution privileges needed. User interaction is not needed for exploitation. Product: Android. Versions: 6.0, 6.0.1, 7.0, 7.1.1, 7.1.2, 8.0, 8.1. Android ID: A-66969349.

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.

In the serialization functions of StatsLogEventWrapper.java, there is a possible out-of-bounds write due to unnecessary functionality which may be abused. This could lead to local escalation of privilege in the system process with no additional execution privileges needed. User interaction is not needed for exploitation. Product: Android. Versions: Android-9. Android ID: A-112550251

In BNEP_Write of bnep_api.cc, there is a possible out of bounds write due to an incorrect bounds check. This could lead to local escalation of privilege with User execution privileges needed. User interaction is not needed for exploitation. Product: Android Versions: Android-6.0 Android-6.0.1 Android-7.0 Android-7.1.1 Android-7.1.2 Android-8.0 Android-8.1 Android ID: A-74947856.

In HID_DevAddRecord of hidd_api.cc, there is a possible out-of-bounds write due to a missing bounds check. This could lead to local escalation of privilege in the Bluetooth service with User execution privileges needed. User interaction is not needed for exploitation. Product: Android. Versions: Android-9. Android ID: A-79946737.

In persist_set_key and other functions of cryptfs.cpp, there is a possible out-of-bounds write due to an uncaught error. 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-112731440.

In hid_debug_events_read of drivers/hid/hid-debug.c, 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: Android Versions: Android kernel Android ID: A-71361580.

In BTA_HdRegisterApp of bta_hd_api.cc, there is a possible out-of-bound 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: Android. Versions: Android-9. Android ID: A-113111784

In all android releases (Android for MSM, Firefox OS for MSM, QRD Android) from CAF using the linux kernel, improper check In the WMA API for the inputs received from the firmware and then fills the same to the host structure will lead to OOB write.

In all android releases (Android for MSM, Firefox OS for MSM, QRD Android) from CAF using the linux kernel, lack of check on input received to calculate the buffer length can lead to out of bound write to kernel stack.

In Android for MSM, Firefox OS for MSM, and QRD Android with all Android releases from CAF using the Linux kernel while trying to find out total number of partition via a non zero check, there could be possibility where the 'TotalPart' could cross 'GptHeader->MaxPtCnt' and which could result in OOB write in patching GPT.

In all android releases (Android for MSM, Firefox OS for MSM, QRD Android) from CAF using the linux kernel, while processing a message from firmware in WLAN handler, a buffer overwrite can occur.

In all android releases(Android for MSM, Firefox OS for MSM, QRD Android) from CAF using the linux kernel, there is a potential heap overflow and memory corruption due to improper error handling in SOC infrastructure.

In WLAN driver, 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: ALPS06807363; Issue ID: ALPS06807363.

In prepare_io_entry and prepare_response of lwis_ioctl.c and 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 System execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android kernelAndroid ID: A-205995773References: N/A

An improper length check in APAService prior to SMR Sep-2021 Release 1 results in stack based Buffer Overflow.

In WLAN driver, 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: ALPS06704526; Issue ID: ALPS06704526.

In WLAN driver, 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: ALPS06704526; Issue ID: ALPS06704482.

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.

An improper boundary check in secure_log of LDFW and BL31 prior to SMR Dec-2021 Release 1 allows arbitrary memory write and code execution.

A possible stack-based buffer overflow vulnerability in Widevine trustlet prior to SMR Oct-2021 Release 1 allows arbitrary code execution.

An improper input validation vulnerability in NPU firmware prior to SMR MAY-2021 Release 1 allows arbitrary memory write and code execution.

A possible out of bounds write vulnerability in NPU driver prior to SMR JUN-2021 Release 1 allows arbitrary memory write.

A possible buffer overflow vulnerability in NPU driver prior to SMR JUN-2021 Release 1 allows arbitrary memory write and code execution.

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 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.

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.

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.

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.

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.

An issue was discovered on Samsung mobile devices with P(9.0) and Q(10.0) software. There is a stack overflow in the kperfmon driver. The Samsung ID is SVE-2019-15876 (January 2020).

In SetScanResponseData of ble_advertiser_hci_interface.cc, there is a possible out-of-bound 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: Android. Versions: Android-8.0 Android-8.1 Android-9. Android ID: A-121145627.

In ashmem_ioctl of ashmem.c, there is an out-of-bounds write due to insufficient locking when accessing asma. This could lead to a local elevation of privilege enabling code execution as a privileged process with no additional execution privileges needed. User interaction is not needed for exploitation. Product: Android. Versions: Android kernel. Android ID: A-66954097.

In the nfc_hci_cmd_received() function of core.c, there is a possible out of bounds write 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. Product: Android. Versions: Android kernel. Android ID: A-62679701.

In CameraDeviceClient::submitRequestList of CameraDeviceClient.cpp, there is an out-of-bounds write if metadataSize is too small. This could lead to a local elevation of privilege enabling code execution as a privileged process with no additional execution privileges needed. User interaction is not needed for exploitation. Product: Android. Versions: 5.1.1, 6.0, 6.0.1, 7.0, 7.1.1, 7.1.2, 8.0, 8.1. Android ID: A-67782345.

An elevation of privilege vulnerability in the kernel v4l2 video driver. Product: Android. Versions: Android kernel. Android ID A-34624167.

In l2tp_session_delete and related functions of l2tp_core.c, there is possible memory corruption due to a use after free. This could lead to local escalation of privilege with System execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android kernelAndroid ID: A-152735806

In the Android kernel in the vl53L0 driver there is a possible out of bounds write due to a permissions bypass. This could lead to local escalation of privilege due to a set_fs() call without restoring the previous limit with System execution privileges needed. User interaction is not needed for exploitation.

In the Android kernel in Pixel C USB monitor driver there is a possible OOB 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.

In phNxpNciHal_write_ext of phNxpNciHal_ext.cc, 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-10Android ID: A-139733543