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.
For the Central Licensing Server component used in ABB products ABB Ability™ System 800xA and related system extensions versions 5.1, 6.0 and 6.1, Compact HMI versions 5.1 and 6.0, Control Builder Safe 1.0, 1.1 and 2.0, Symphony Plus -S+ Operations 3.0 to 3.2 Symphony Plus -S+ Engineering 1.1 to 2.2, Composer Harmony 5.1, 6.0 and 6.1, Melody Composer 5.3, 6.1/6.2 and SPE for Melody 1.0SPx (Composer 6.3), Harmony OPC Server (HAOPC) Standalone 6.0, 6.1 and 7.0, ABB Ability™ System 800xA/ Advant® OCS Control Builder A 1.3 and 1.4, Advant® OCS AC100 OPC Server 5.1, 6.0 and 6.1, Composer CTK 6.1 and 6.2, AdvaBuild 3.7 SP1 and SP2, OPCServer for MOD 300 (non-800xA) 1.4, OPC Data Link 2.1 and 2.2, Knowledge Manager 8.0, 9.0 and 9.1, Manufacturing Operations Management 1812 and 1909, ABB AbilityTM SCADAvantage versions 5.1 to 5.6.5, a weakness in validation of input exists that allows an attacker to block license handling by sending specially crafted messages to the CLS web service.
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.
An improper input validation vulnerability in the UEM Core of BlackBerry UEM version(s) 12.13.0, 12.12.1a QF2 (and earlier), and 12.11.1 QF3 (and earlier) could allow an attacker to potentially cause a Denial of Service (DoS) of the UEM Core service.
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.
VMware ESXi (7.0 prior to ESXi70U1c-17325551), VMware Workstation (16.x prior to 16.0 and 15.x prior to 15.5.7), VMware Fusion (12.x prior to 12.0 and 11.x prior to 11.5.7) and VMware Cloud Foundation contain a denial of service vulnerability due to improper input validation in GuestInfo. A malicious actor with normal user privilege access to a virtual machine can crash the virtual machine's vmx process leading to a denial of service condition.
The tcmu-runner daemon in tcmu-runner version 1.0.5 to 1.2.0 is vulnerable to a local denial of service attack
Some ZTE products have an input verification vulnerability in the diagnostic function interface. Due to insufficient verification of some parameters input by users, an attacker with high privileges can cause process exception by repeatedly inputting illegal parameters. This affects:<ZXONE 9700 , ZXONE 8700, ZXONE 19700><V1.40.021.021CP049, V1.0P02B219_@NCPM-RELEASE_2.40R1-20200914.set>
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.
Application Firewall in Apple OS X before 10.12 allows local users to cause a denial of service via vectors involving a crafted SO_EXECPATH environment variable.
Linux kernel 2.6 and 2.4 on the IA64 architecture allows local users to cause a denial of service (kernel crash) via ptrace and the restore_sigcontext function.
cPanel before 74.0.8 allows local users to disable the ClamAV daemon (SEC-409).
The File Bookmark component in Apple OS X before 10.11.1 allows local users to cause a denial of service (application crash) via crafted bookmark metadata in a folder.
cPanel before 70.0.23 allows any user to disable Solr (SEC-371).
In affected versions of TensorFlow running an LSTM/GRU model where the LSTM/GRU layer receives an input with zero-length results in a CHECK failure when using the CUDA backend. This can result in a query-of-death vulnerability, via denial of service, if users can control the input to the layer. This is fixed in versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, and 2.4.0.
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.
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.
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.
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.
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.
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.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.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 `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.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.
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.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.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.
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.
Insufficient input validation in the firmware for Intel(R) 722 Ethernet Controllers before version 1.4.3 may allow a privileged user to potentially enable denial of service via local access.
Insufficient input validation in the firmware for the Intel(R) 700-series of Ethernet Controllers before version 7.3 may allow a privileged user to potentially enable denial of service via local access.
Improper input validation in the firmware for some Intel(R) Processors may allow an authenticated user to potentially enable denial of service via local access.
Improper input validation in the Intel(R) SGX Platform Software for Windows* may allow an authenticated user to potentially enable a denial of service via local access.
Improper input validation in some Intel(R) Ethernet E810 Adapter drivers for Linux before version 1.0.4 and before version 1.4.29.0 for Windows*, may allow an authenticated user to potentially enable a denial of service via local access.
An Ubuntu-specific modification to AccountsService in versions before 0.6.55-0ubuntu13.2, among other earlier versions, would perform unbounded read operations on user-controlled ~/.pam_environment files, allowing an infinite loop if /dev/zero is symlinked to this location.
Philips SureSigns VS4, A.07.107 and prior receives input or data, but it does not validate or incorrectly validates that the input has the properties required to process the data safely and correctly.
An input validation vulnerability exists in Juniper Networks Junos OS, allowing an attacker to crash the srxpfe process, causing a Denial of Service (DoS) through the use of specific maintenance commands. The srxpfe process restarts automatically, but continuous execution of the commands could lead to an extended Denial of Service condition. This issue only affects the SRX1500, SRX4100, SRX4200, NFX150, NFX250, and vSRX-based platforms. No other products or platforms are affected by this vulnerability. This issue affects Juniper Networks Junos OS: 15.1X49 versions prior to 15.1X49-D220 on SRX1500, SRX4100, SRX4200, vSRX; 17.4 versions prior to 17.4R3-S3 on SRX1500, SRX4100, SRX4200, vSRX; 18.1 versions prior to 18.1R3-S11 on SRX1500, SRX4100, SRX4200, vSRX, NFX150; 18.2 versions prior to 18.2R3-S5 on SRX1500, SRX4100, SRX4200, vSRX, NFX150, NFX250; 18.3 versions prior to 18.3R2-S4, 18.3R3-S3 on SRX1500, SRX4100, SRX4200, vSRX, NFX150, NFX250; 18.4 versions prior to 18.4R2-S5, 18.4R3-S4 on SRX1500, SRX4100, SRX4200, vSRX, NFX150, NFX250; 19.1 versions prior to 19.1R3-S2 on SRX1500, SRX4100, SRX4200, vSRX, NFX150, NFX250; 19.2 versions prior to 19.2R1-S5, 19.2R3 on SRX1500, SRX4100, SRX4200, vSRX, NFX150, NFX250. This issue does not affect Junos OS 19.3 or any subsequent version.
Memory corruption in IntLixCrashDumpDmesg, IntLixTaskFetchCmdLine, IntLixFileReadDentry and IntLixFileGetPath due to insufficient guest-data input validation may lead to denial of service conditions.
Remote Denial of Service in LwM2M do_write_op_tlv. Zephyr versions >= 1.14.2, >= 2.2.0 contain Improper Input Validation (CWE-20), Loop with Unreachable Exit Condition ('Infinite Loop') (CWE-835). For more information, see https://github.com/zephyrproject-rtos/zephyr/security/advisories/GHSA-g9mg-fj58-6fqh
Improper input validation in some Intel(R) Graphics Drivers for Windows* before version 26.20.100.7212 and before Linux kernel version 5.5 may allow a privileged user to potentially enable a denial of service via local access.
AMD Graphics Driver for Windows 10, amdfender.sys may improperly handle input validation on InputBuffer which may result in a denial of service (DoS).
Improper input validation in some Intel(R) Thunderbolt(TM) controllers may allow an authenticated user to potentially enable denial of service via local access.
A Denial Of Service vulnerability exists when Connected User Experiences and Telemetry Service fails to validate certain function values.An attacker who successfully exploited this vulnerability could deny dependent security feature functionality.To exploit this vulnerability, an attacker would have to log on to an affected system and run a specially crafted application.The security update addresses the vulnerability by correcting how the Connected User Experiences and Telemetry Service validates certain function values., aka 'Connected User Experiences and Telemetry Service Denial of Service Vulnerability'. This CVE ID is unique from CVE-2020-1123.
Improper input validation in Intel(R) Graphics Drivers before version 26.20.100.7212 may allow an authenticated user to enable denial of service via local access.
In the settings app, there is a possible app crash due to improper input validation. This could lead to local denial of service of the Settings app with User execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-10Android ID: A-136005061
Data corruption vulnerability in firmware in Intel Solid-State Drive Consumer, Professional, Embedded, Data Center affected firmware versions LSBG200, LSF031C, LSF036C, LBF010C, LSBG100, LSF031C, LSF036C, LBF010C, LSF031P, LSF036P, LBF010P, LSF031P, LSF036P, LBF010P, LSMG200, LSF031E, LSF036E, LSMG100, LSF031E, LSF036E, LSDG200, LSF031D, LSF036D allows local users to cause a denial of service via unspecified vectors.
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.
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 end-to-end open source platform for machine learning. In affected versions an attacker can trigger a denial of service via a `CHECK`-fail in `tf.raw_ops.MapStage`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/map_stage_op.cc#L513) does not check that the `key` input is a valid non-empty tensor. We have patched the issue in GitHub commit d7de67733925de196ec8863a33445b73f9562d1d. 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.
The KVM subsystem in the Linux kernel through 4.13.3 allows guest OS users to cause a denial of service (assertion failure, and hypervisor hang or crash) via an out-of bounds guest_irq value, related to arch/x86/kvm/vmx.c and virt/kvm/eventfd.c.