The tgbvpn.sys driver in TheGreenBow IPSec VPN Client 4.61.003 allows local users to cause a denial of service (NULL pointer dereference and system crash) via a crafted request to the 0x80000034 IOCTL, probably involving an input or output buffer size of 0.

An issue was discovered in STOPzilla AntiMalware 6.5.2.59. The driver file szkg64.sys contains a Denial of Service vulnerability due to not validating the output buffer address value from IOCtl 0x8000204F.

The /etc/profile.d/60alias.sh script in the Mandriva bash package for Bash 2.05b, 3.0, 3.2, 3.2.48, and 4.0 enables the --show-control-chars option in LS_OPTIONS, which allows local users to send escape sequences to terminal emulators, or hide the existence of a file, via a crafted filename.

IBM DataPower Gateway 7.1.0.0 through 7.1.0.19, 7.2.0.0 through 7.2.0.16, 7.5.0.0 through 7.5.0.10, 7.5.1.0 through 7.5.1.9, 7.5.2.0 through 7.5.2.9, and 7.6.0.0 through 7.6.0.2 and IBM MQ Appliance 8.0.0.0 through 8.0.0.8 and 9.0.1 through 9.0.5 could allow a local user to cause a denial of service through unknown vectors. IBM X-Force ID: 144724.

Insufficient input validation in Intel(R) Driver & Support Assistant version 19.3.12.3 and before may allow a privileged user to potentially enable denial of service via local access.

dbus 1.3.0 before 1.6.22 and 1.8.x before 1.8.6, when running on Linux 2.6.37-rc4 or later, allows local users to cause a denial of service (system-bus disconnect of other services or applications) by sending a message containing a file descriptor, then exceeding the maximum recursion depth before the initial message is forwarded.

An issue was discovered in STOPzilla AntiMalware 6.5.2.59. The driver file szkg64.sys contains a Denial of Service vulnerability due to not validating the output buffer address value from IOCtl 0x8000204B.

LaunchServices in Apple OS X before 10.10.3 allows local users to cause a denial of service (Finder crash) via crafted localization data.

An issue was discovered in STOPzilla AntiMalware 6.5.2.59. The driver file szkg64.sys contains a Denial of Service vulnerability due to not validating the output buffer address value from IOCtl 0x8000205B.

An issue was discovered in STOPzilla AntiMalware 6.5.2.59. The driver file szkg64.sys contains a Denial of Service vulnerability due to not validating the output buffer address value from IOCtl 0x80002043.

Insufficient Input validation in the subsystem for Intel(R) CSME before versions 12.0.45,13.0.10 and 14.0.10 may allow a privileged user to potentially enable denial of service via local access.

vetmonnt.sys in CA Internet Security Suite r3, vetmonnt.sys before 9.0.0.184 in Internet Security Suite r4, and vetmonnt.sys before 10.0.0.217 in Internet Security Suite r5 do not properly verify IOCTL calls, which allows local users to cause a denial of service (system crash) via a crafted call.

client/mount.cifs.c in mount.cifs in smbfs in Samba 3.4.5 and earlier does not verify that the (1) device name and (2) mountpoint strings are composed of valid characters, which allows local users to cause a denial of service (mtab corruption) via a crafted string.

Triangle MicroWorks SCADA Data Gateway before 3.00.0635 allows physically proximate attackers to cause a denial of service (excessive data processing) via a crafted DNP request over a serial line.

mm/filemap.c in the Linux kernel before 2.6.25 allows local users to cause a denial of service (infinite loop) via a writev system call that triggers an iovec of zero length, followed by a page fault for an iovec of nonzero length.

A flaw was found in NetworkManager in versions before 1.30.0. Setting match.path and activating a profile crashes NetworkManager. The highest threat from this vulnerability is to system availability.

Insufficient input validation in Kernel Mode Driver in Intel(R) Graphics Driver for Windows* before versions 10.18.x.5059 (aka 15.33.x.5059), 10.18.x.5057 (aka 15.36.x.5057), 20.19.x.5063 (aka 15.40.x.5063) 21.20.x.5064 (aka 15.45.x.5064) and 24.20.100.6373 potentially enables a privileged user to cause a denial of service via local access.

NVIDIA vGPU manager contains a vulnerability in the vGPU plugin, in which input data is not validated, which may lead to unexpected consumption of resources, which in turn may lead to denial of service. This affects vGPU version 8.x (prior to 8.6) and version 11.0 (prior to 11.3).

Insufficient input validation in Intel(R) Server Platform Services HECI subsystem before version SPS_E5_04.00.04.393.0 may allow privileged user to potentially cause a denial of service via local access.

Improper input validation in firmware of some Solidigm DC Products may allow an attacker with local access to cause a Denial of Service

NVIDIA GPU Display Driver for Windows and Linux, all versions, contains a vulnerability in the kernel mode layer (nvlddmkm.sys) handler for DxgkDdiEscape or IOCTL in which improper validation of a user pointer may lead to denial of service.

Insufficient input validation in User Mode Driver in Intel(R) Graphics Driver for Windows* before versions 10.18.x.5059 (aka 15.33.x.5059), 10.18.x.5057 (aka 15.36.x.5057), 20.19.x.5063 (aka 15.40.x.5063) 21.20.x.5064 (aka 15.45.x.5064) and 24.20.100.6373 potentially enables an unprivileged user to cause a denial of service via local access.

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, certain TFLite models that were created using TFLite model converter would crash when loaded in the TFLite interpreter. The culprit is that during quantization the scale of values could be greater than 1 but code was always assuming sub-unit scaling. Thus, since code was calling `QuantizeMultiplierSmallerThanOneExp`, the `TFLITE_CHECK_LT` assertion would trigger and abort the process. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.TensorSummaryV2` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.LSTMBlockCell` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. The code does not validate the ranks of any of the arguments to this API call. This results in `CHECK`-failures when the elements of the tensor are accessed. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

Improper input validation in the Intel(R) SPS versions before SPS_E5_04.04.04.023.0, SPS_E5_04.04.03.228.0 or SPS_SoC-A_05.00.03.098.0 may allow a privileged user to potentially enable denial of service via local access.

An issue was discovered in Alps Pointing-device Driver 10.1.101.207. ApMsgFwd.exe allows the current user to map and write to the "ApMsgFwd File Mapping Object" section. ApMsgFwd.exe uses the data written to this section as arguments to functions. This causes a denial of service condition when invalid pointers are written to the mapped section. This driver has been used with Dell, ThinkPad, and VAIO devices.

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.SparseTensorToCSRSparseMatrix` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. The code assumes `dense_shape` is a vector and `indices` is a matrix (as part of requirements for sparse tensors) but there is no validation for this. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.DeleteSessionTensor` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.UnsortedSegmentJoin` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. The code assumes `num_segments` is a scalar but there is no validation for this before accessing its value. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

Improper input validation in firmware for some Intel(R) PROSet/Wireless Wi-Fi in multiple operating systems and some Killer(TM) Wi-Fi in Windows 10 and 11 may allow a privileged user to potentially enable denial of service via local access.

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.QuantizedConv2D` does not fully validate the input arguments. In this case, references get bound to `nullptr` for each argument that is empty. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.ragged.constant` does not fully validate the input arguments. This results in a denial of service by consuming all available memory. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

A validation issue was addressed with improved input sanitization. This issue is fixed in iOS 13.5 and iPadOS 13.5, macOS Catalina 10.15.5. A USB device may be able to cause a denial of service.

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.histogram_fixed_width` is vulnerable to a crash when the values array contain `Not a Number` (`NaN`) elements. The implementation assumes that all floating point operations are defined and then converts a floating point result to an integer index. If `values` contains `NaN` then the result of the division is still `NaN` and the cast to `int32` would result in a crash. This only occurs on the CPU implementation. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.LoadAndRemapMatrix does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. The code assumes `initializing_values` is a vector but there is no validation for this before accessing its value. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.GetSessionTensor` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.Conv3DBackpropFilterV2` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. The code does not validate that the `filter_sizes` argument is a vector. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

Improper input validation in a subsystem for some Intel Server Boards, Server Systems and Compute Modules before version 1.59 may allow an authenticated user to potentially enable denial of service via local access.

The kernel_wait4 function in kernel/exit.c in the Linux kernel before 4.13, when an unspecified architecture and compiler is used, might allow local users to cause a denial of service by triggering an attempted use of the -INT_MIN value.

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.SparseTensorDenseAdd` does not fully validate the input arguments. In this case, a reference gets bound to a `nullptr` during kernel execution. This is undefined behavior. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, multiple TensorFlow operations misbehave in eager mode when the resource handle provided to them is invalid. In graph mode, it would have been impossible to perform these API calls, but migration to TF 2.x eager mode opened up this vulnerability. If the resource handle is empty, then a reference is bound to a null pointer inside TensorFlow codebase (various codepaths). This is undefined behavior. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.StagePeek` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. The code assumes `index` is a scalar but there is no validation for this before accessing its value. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the `tf.compat.v1.signal.rfft2d` and `tf.compat.v1.signal.rfft3d` lack input validation and under certain condition can result in crashes (due to `CHECK`-failures). Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.QuantizeAndDequantizeV4Grad` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

NVIDIA Virtual GPU Manager contains a vulnerability in the vGPU plugin, in which an input data size is not validated, which may lead to tampering or denial of service. This affects vGPU version 8.x (prior to 8.5), version 10.x (prior to 10.4) and version 11.0.

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.UnsortedSegmentJoin` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. The code assumes `num_segments` is a positive scalar but there is no validation. Since this value is used to allocate the output tensor, a negative value would result in a `CHECK`-failure (assertion failure), as per TFSA-2021-198. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

NVIDIA GPU Display Driver for Windows contains a vulnerability in the kernel mode layer (nvlddmkm.sys) handler for DxgkDdiEscape, where improper input validation can cause denial of service.