Buffer overflow in the mp_override_legacy_irq() function in arch/x86/kernel/acpi/boot.c in the Linux kernel through 3.2 allows local users to gain privileges via a crafted ACPI table.

Possible buffer overflow due to lack of validation for the length of NAI string read from EFS in Snapdragon Auto, Snapdragon Compute, Snapdragon Connectivity, Snapdragon Mobile

Memory corruption in BT controller due to improper length check while processing vendor specific commands in Snapdragon Compute, Snapdragon Connectivity, Snapdragon Consumer Electronics Connectivity, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Wired Infrastructure and Networking

Improper buffer initialization on the backend driver can lead to buffer overflow in Snapdragon Auto

Possible buffer overflow due to lack of input IB amount validation while processing the user command in Snapdragon Auto

In HCL Notes version 9 previous to release 9.0.1 FixPack 10 Interim Fix 8, version 10 previous to release 10.0.1 FixPack 6 and version 11 previous to 11.0.1 FixPack 1, a vulnerability in the input parameter handling of the Notes Client could potentially be exploited by an attacker resulting in a buffer overflow. This could enable an attacker to crash HCL Notes or execute attacker-controlled code on the client.

Buffer Overflow vulnerability in Dvidelabs flatcc v.0.6.0 allows local attacker to execute arbitrary code via the fltacc execution of the error_ref_sym function.

A buffer overflow vulnerability in the USBH_ParseEPDesc() function of STMicroelectronics STM32Cube Middleware v1.8.0 and below allows attackers to execute arbitrary code.

A potential buffer overflow in the software drivers for certain HP LaserJet products and Samsung product printers could lead to an escalation of privilege.

A buffer overflow was addressed with improved bounds checking. This issue is fixed in macOS Monterey 12.1, Security Update 2021-008 Catalina, macOS Big Sur 11.6.2. An application may be able to execute arbitrary code with kernel privileges.

Memory corruption in TZ Secure OS while Tunnel Invoke Manager initialization.

A vulnerability has been identified in SIMATIC PCS 7 V8.2 and earlier (All versions), SIMATIC PCS 7 V9.0 (All versions < V9.0 SP3), SIMATIC PDM (All versions < V9.2), SIMATIC STEP 7 V5.X (All versions < V5.6 SP2 HF3), SINAMICS STARTER (containing STEP 7 OEM version) (All versions < V5.4 HF2). The affected software contains a buffer overflow vulnerability while handling certain files that could allow a local attacker to trigger a denial-of-service condition or potentially lead to remote code execution.

A buffer overflow vulnerability in McAfee Data Loss Prevention (DLP) Endpoint for Windows prior to 11.6.200 allows a local attacker to execute arbitrary code with elevated privileges through placing carefully constructed Ami Pro (.sam) files onto the local system and triggering a DLP Endpoint scan through accessing a file. This is caused by the destination buffer being of fixed size and incorrect checks being made on the source size.

Memory corruption in HLOS while running kernel address sanitizers (syzkaller) on tmecom with DEBUG_FS enabled.

Improper validation of maximum size of data write to EFS file can lead to memory corruption in Snapdragon Auto, Snapdragon Compute, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wearables

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 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.

Possible buffer overflow while printing the HARQ memory partition detail due to improper validation of buffer size in Snapdragon Auto, Snapdragon Compute, Snapdragon Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile

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

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.

Possible buffer overflow due to lack of buffer length check when segmented WMI command is received in Snapdragon Auto, Snapdragon Compute, Snapdragon Connectivity, Snapdragon Consumer Electronics Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wired Infrastructure and Networking

Possible heap Memory Corruption Issue due to lack of input validation when sending HWTC IQ Capture command in Snapdragon Auto, Snapdragon Compute, Snapdragon Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wearables

Improper size validation of QXDM commands can lead to memory corruption in Snapdragon Compute, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile

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

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.

Memory corruption while processing the IOCTL FM HCI WRITE request.

A potential local buffer overflow vulnerability has been identified in HPE FlexNetwork 5130 EL Switch Series version: Prior to 5130_EI_7.10.R3507P02. HPE has made the following software update to resolve the vulnerability in HPE FlexNetwork 5130 EL Switch Series version 5130_EL_7.10.R3507P02.

Memory corruption while copying the sound model data from user to kernel buffer during sound model register.

Memory corruption while querying module parameters from Listen Sound model client in kernel from user space.

Memory corruption while copying a keyblob`s material when the key material`s size is not accurately checked.