This vulnerability allows local attackers to escalate privileges on affected installations of Parallels Desktop 16.1.3 (49160). An attacker must first obtain the ability to execute high-privileged code on the target guest system in order to exploit this vulnerability. The specific flaw exists within the virtio-gpu virtual device. The issue results from the lack of proper validation of user-supplied data, which can result in a memory corruption condition. An attacker can leverage this vulnerability to escalate privileges and execute arbitrary code in the context of the hypervisor. Was ZDI-CAN-13581.

An issue was discovered in net/rds/af_rds.c in the Linux kernel before 4.11. There is an out of bounds write and read in the function rds_recv_track_latency.

Trusty contains a vulnerability in all trusted applications (TAs) where the stack cookie was not randomized, which might result in stack-based buffer overflow, leading to denial of service, escalation of privileges, and information disclosure.

Out-of-bounds write in the Intel(R) Kernelflinger project may allow an authenticated user to potentially enable escalation of privilege via local access.

An issue was discovered in drivers/i2c/i2c-core-smbus.c in the Linux kernel before 4.14.15. There is an out of bounds write in the function i2c_smbus_xfer_emulated.

A flaw was found in the Linux kernel in versions before 5.9-rc6. When changing screen size, an out-of-bounds memory write can occur leading to memory corruption or a denial of service. Due to the nature of the flaw, privilege escalation cannot be fully ruled out.

IrfanView 4.53 allows a User Mode Write AV starting at WSQ!ReadWSQ+0x0000000000004359.

Possible memory corruption due to improper validation of memory address while processing user-space IOCTL for clearing Filter and Route statistics in Snapdragon Auto, Snapdragon Compute, Snapdragon Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wearables

The netfilter subsystem in the Linux kernel before 4.9 mishandles IPv6 reassembly, which allows local users to cause a denial of service (integer overflow, out-of-bounds write, and GPF) or possibly have unspecified other impact via a crafted application that makes socket, connect, and writev system calls, related to net/ipv6/netfilter/nf_conntrack_reasm.c and net/ipv6/netfilter/nf_defrag_ipv6_hooks.c.

A memory corruption issue was addressed with improved state management. This issue is fixed in Security Update 2021-005 Catalina, macOS Big Sur 11.6. A local attacker may be able to elevate their privileges.

A local attacker may be able to elevate their privileges. This issue is fixed in macOS Big Sur 11.4, Security Update 2021-003 Catalina, Security Update 2021-004 Mojave. A memory corruption issue was addressed with improved validation.

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.

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.FractionalAvgPoolGrad` is vulnerable to a heap buffer overflow. The implementation(https://github.com/tensorflow/tensorflow/blob/dcba796a28364d6d7f003f6fe733d82726dda713/tensorflow/core/kernels/fractional_avg_pool_op.cc#L216) fails to validate that the pooling sequence arguments have enough elements as required by the `out_backprop` tensor shape. 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.

IBM Security Verify Access 20.07 is vulnerable to a stack based buffer overflow, caused by improper bounds checking which could allow a local attacker to execute arbitrary code on the system with elevated privileges.

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.

FS: Buffer Overflow when enabling Long File Names in FAT_FS and calling fs_stat. Zephyr versions >= v1.14.2, >= v2.3.0 contain Stack-based Buffer Overflow (CWE-121). For more information, see https://github.com/zephyrproject-rtos/zephyr/security/advisories/GHSA-7fhv-rgxr-x56h

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.

Out of Bounds Write and Read in AMD Graphics Driver for Windows 10 in Escape 0x6002d03 may lead to escalation of privilege or denial of service.

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. 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.

Stack Buffer Overflow in AMD Graphics Driver for Windows 10 in Escape 0x15002a may lead to escalation of privilege or denial of service.

A heap overflow in LzmaUefiDecompressGetInfo function in EDK II.

A remote code execution vulnerability exists when the Windows Font Driver Host improperly handles memory.An attacker who successfully exploited the vulnerability would gain execution on a victim system.The security update addresses the vulnerability by correcting how the Windows Font Driver Host handles memory., aka 'Windows Font Driver Host Remote Code Execution Vulnerability'.

Pool/Heap Overflow in AMD Graphics Driver for Windows 10 in Escape 0x110037 may lead to escalation of privilege, information disclosure or denial of service.

An out of bounds write and read vulnerability in the AMD Graphics Driver for Windows 10 may lead to escalation of privilege or denial of service.

An out of bounds write vulnerability in the AMD Graphics Driver for Windows 10 may lead to escalation of privileges or denial of service.

WASM3 v0.5.0 was discovered to contain a heap overflow via the component /wabt/bin/poc.wasm.

Trend Micro Home Network Security version 6.6.604 and earlier is vulnerable to an iotcl stack-based buffer overflow vulnerability which could allow an attacker to issue a specially crafted iotcl to escalate privileges on affected devices. An attacker must first obtain the ability to execute low-privileged code on the target device in order to exploit this vulnerability.

Stack Buffer Overflow in AMD Graphics Driver for Windows 10 may lead to escalation of privilege or denial of service.

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

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

An issue was discovered in the Linux kernel through 5.11.3. Certain iSCSI data structures do not have appropriate length constraints or checks, and can exceed the PAGE_SIZE value. An unprivileged user can send a Netlink message that is associated with iSCSI, and has a length up to the maximum length of a Netlink message.

Out of bound write in some Intel(R) Graphics Drivers before version 26.20.100.8336 may allow a privileged user to potentially enable escalation of privilege via local access.

Heap overflow in the BMC firmware for some Intel(R) Server Boards, Server Systems and Compute Modules before version 2.47 may allow an authenticated user to potentially enable escalation of privilege via local access.

In all versions of FactoryTalk View SE, after bypassing memory corruption mechanisms found in the operating system, a local, authenticated attacker may corrupt the associated memory space allowing for arbitrary code execution. Rockwell Automation recommends applying patch 1126290. Before installing this patch, the patch rollup dated 06 Apr 2020 or later MUST be applied. 1066644 – Patch Roll-up for CPR9 SRx.

An issue was found in Linux kernel before 5.5.4. The mwifiex_cmd_append_vsie_tlv() function in drivers/net/wireless/marvell/mwifiex/scan.c allows local users to gain privileges or cause a denial of service because of an incorrect memcpy and buffer overflow, aka CID-b70261a288ea.

A stack-based buffer overflow vulnerability exists in the command-line-parsing HandleFileArg functionality of AT&T Labs’ Xmill 0.7. Within the function HandleFileArg the argument filepattern is under control of the user who passes it in from the command line. filepattern is passed directly to strcpy copying the path provided by the user into a static sized buffer without any length checks resulting in a stack-buffer overflow. An attacker can provide malicious input to trigger these vulnerabilities.

A heap out-of-bounds write affecting Linux since v2.6.19-rc1 was discovered in net/netfilter/x_tables.c. This allows an attacker to gain privileges or cause a DoS (via heap memory corruption) through user name space

Within the function HandleFileArg the argument filepattern is under control of the user who passes it in from the command line. filepattern is passed directly to memcpy copying the path provided by the user into a staticly sized buffer without any length checks resulting in a stack-buffer overflow.

A stack-based buffer overflow vulnerability exists in the command-line-parsing HandleFileArg functionality of AT&T Labs' Xmill 0.7. Within the function HandleFileArg the argument filepattern is under control of the user who passes it in from the command line. filepattern is passed directly to strcpy copying the path provided by the user into a staticly sized buffer without any length checks resulting in a stack-buffer overflow. An attacker can provide malicious input to trigger this vulnerability.

Memory corruption issues in Intel(R) WIFI Drivers before version 21.40 may allow a privileged user to potentially enable escalation of privilege, denial of service, and information disclosure via local access.

There is a Memory Buffer Improper Operation Limit vulnerability in Huawei Smartphone. Successful exploitation of this vulnerability may cause exceptions in image processing.

Memory corruption issues in Intel(R) PROSet/Wireless WiFi Software extension DLL before version 21.40 may allow an authenticated user to potentially enable escalation of privilege, information disclosure and a denial of service via local access.

Stack-based buffer overflow in the gps_tracker function in airodump-ng.c in Aircrack-ng before 1.2 RC 1 allows local users to execute arbitrary code or gain privileges via unspecified vectors.

A heap buffer overflow flaw was found in IPsec ESP transformation code in net/ipv4/esp4.c and net/ipv6/esp6.c. This flaw allows a local attacker with a normal user privilege to overwrite kernel heap objects and may cause a local privilege escalation threat.

Stack out-of-bounds write occurs while setting up a cipher device if the provided IV length exceeds the max limit value 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