A Denial Of Service vulnerability exists when Connected User Experiences and Telemetry Service fails to validate certain function values, aka "Connected User Experiences and Telemetry Service Denial of Service Vulnerability." This affects Windows Server 2016, Windows 10, Windows Server 2019, Windows 10 Servers.
Remote Desktop in Windows XP SP1 does not verify the "Force shutdown from a remote system" setting, which allows remote attackers to shut down the system by executing TSShutdn.exe.
A component of the HarmonyOS has a Improper Input Validation vulnerability. Local attackers may exploit this vulnerability to cause out-of-bounds write.
In Vectura Perfect Privacy VPN Manager v1.10.10 and v1.10.11, when resetting the network data via the software client, with a running VPN connection, a critical error occurs which leads to a "FrmAdvancedProtection" crash. Although the mechanism malfunctions and an error occurs during the runtime with the stack trace being issued, the software process is not properly terminated. The software client is still attempting to maintain the connection even though the network connection information is being reset live. In that insecure mode, the "FrmAdvancedProtection" component crashes, but the process continues to run with different errors and process corruptions. This local corruption vulnerability can be exploited by local attackers.
A Denial of Service due to Improper Input Validation vulnerability in the Management Console component of BlackBerry UEM version(s) 12.13.1 QF2 and earlier and 12.12.1a QF6 and earlier could allow an attacker to potentially to prevent any new user connections.
PCManFM 1.2.5 insecurely uses /tmp for a socket file, allowing a local user to cause a denial of service (application unavailability).
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.
The PV domain builder in Xen 4.2 and earlier does not validate the size of the kernel or ramdisk (1) before or (2) after decompression, which allows local guest administrators to cause a denial of service (domain 0 memory consumption) via a crafted (a) kernel or (b) ramdisk.
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.
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>
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.
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.
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).
Improper Validation of Specified Index, Position, or Offset in Input 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.
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.
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.
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.
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.
In the Linux Kernel before version 4.15.8, 4.14.25, 4.9.87, 4.4.121, 4.1.51, and 3.2.102, an error in the "_sctp_make_chunk()" function (net/sctp/sm_make_chunk.c) when handling SCTP packets length can be exploited to cause a kernel crash.
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 end-to-end open source platform for machine learning. In affected versions the shape inference code for `tf.raw_ops.Dequantize` has a vulnerability that could trigger a denial of service via a segfault if an attacker provides invalid arguments. The shape inference [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/ops/array_ops.cc#L2999-L3014) uses `axis` to select between two different values for `minmax_rank` which is then used to retrieve tensor dimensions. However, code assumes that `axis` can be either `-1` or a value greater than `-1`, with no validation for the other values. We have patched the issue in GitHub commit da857cfa0fde8f79ad0afdbc94e88b5d4bbec764. 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.
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.
IBM Cloud Orchestrator could allow a local authenticated attacker to cause the server to slow down for a short period of time by using a specially crafted and malformed URL.
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.
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.
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.
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.
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 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.
This issue was addressed with improved checks. This issue affected versions prior to iOS 12, macOS Mojave 10.14, tvOS 12, watchOS 5.
An exploitable denial-of-service vulnerability exists in the helper service of Clean My Mac X, version 4.04, due to improper input validation. A user with local access can use this vulnerability to terminate a privileged helper application. An attacker would need local access to the machine for a successful exploit.
An exploitable local denial-of-service vulnerability exists in the privileged helper tool of GOG Galaxy's Games, version 1.2.47 for macOS. An attacker can send malicious data to the root-listening service, causing the application to terminate and become unavailable.
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.
Cisco IOS before 12.2(33)SXI allows local users to cause a denial of service (device reboot).
The cleanup_journal_tail function in the Journaling Block Device (JBD) functionality in the Linux kernel 2.6 allows local users to cause a denial of service (assertion error and kernel oops) via an ext3 or ext4 image with an "invalid log first block value."
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.
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.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, 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.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 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.
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.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.
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.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.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.