Multiple memory corruption issues were addressed with improved input validation. This issue is fixed in macOS Mojave 10.14.4. Processing malicious data may lead to unexpected application termination.
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, 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.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.
Improper input validation in the API for Intel(R) Graphics Driver versions before 26.20.100.7209 may allow an authenticated 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 `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.
A vulnerability in the bridge protocol data unit (BPDU) forwarding functionality of Cisco Aironet Access Points (APs) could allow an unauthenticated, adjacent attacker to cause an AP port to go into an error disabled state. The vulnerability occurs because BPDUs received from specific wireless clients are forwarded incorrectly. An attacker could exploit this vulnerability on the wireless network by sending a steady stream of crafted BPDU frames. A successful exploit could allow the attacker to cause a limited denial of service (DoS) attack because an AP port could go offline.
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.
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.
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.
Insufficient input validation in Kernel Mode module for Intel(R) Graphics Driver before version 25.20.100.6519 may allow an authenticated user to potentially enable denial of service via local access.
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.
Improper validation for loop variable received from firmware can lead to out of bound access in WLAN function while iterating through loop in Snapdragon Auto, Snapdragon Compute, Snapdragon Consumer Electronics Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Voice & Music in APQ8053, APQ8096AU, APQ8098, MDM9640, MSM8996AU, MSM8998, QCA6574AU, QCN7605, QCS405, QCS605, SDA845, SDM845, SDX20
Insufficient input validation in i40e driver for Intel(R) Ethernet 700 Series Controllers versions before 7.0 may allow an authenticated user to potentially enable a denial of service via local access.
Insufficient input validation in KMD module for Intel(R) Graphics Driver before version 10.18.14.5067 (aka 15.36.x.5067) and 10.18.10.5069 (aka 15.33.x.5069) may allow an authenticated user to potentially enable denial of service via local access.
Insufficient input validation in the Intel(R) SGX driver for Linux may allow an authenticated user to potentially enable a denial of service via local access.
Insufficient input validation in i40e driver for Intel(R) Ethernet 700 Series Controllers versions before 2.8.43 may allow an authenticated user to potentially enable a denial of service via local access.
Rising Antivirus 2008 before 20.38.20 allows local users to cause a denial of service (system crash) via an invalid pointer to the _CLIENT_ID structure in a call to the NtOpenProcess hooked System Service Descriptor Table (SSDT) function.
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.
A validation issue was addressed with improved logic. This issue affected versions prior to macOS Mojave 10.14.
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.
cPanel before 74.0.8 allows local users to disable the ClamAV daemon (SEC-409).
cPanel before 70.0.23 allows any user to disable Solr (SEC-371).
If the attacker manages to create files in the directory used to collect log files in supportutils before version 3.1-5.7.1 (e.g. with CVE-2018-19638) he can kill arbitrary processes on the local machine.
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.
Ghost Security Suite beta 1.110 does not properly validate certain parameters to System Service Descriptor Table (SSDT) function handlers, which allows local users to cause a denial of service (crash) and possibly gain privileges via the (1) NtCreateKey, (2) NtDeleteValueKey, (3) NtQueryValueKey, (4) NtSetSystemInformation, and (5) NtSetValueKey kernel SSDT hooks.
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 0x80002067.
Kaspersky Anti-Virus (KAV) and Internet Security 7.0 build 125 do not properly validate certain parameters to System Service Descriptor Table (SSDT) and Shadow SSDT function handlers, which allows local users to cause a denial of service (crash) via the (1) NtUserSendInput, (2) LoadLibraryA, (3) NtOpenProcess, (4) NtOpenThread, (5) NtTerminateProcess, (6) NtUserFindWindowEx, and (7) NtUserBuildHwndList kernel SSDT hooks in kylif.sys; the (8) NtDuplicateObject (DuplicateHandle) kernel SSDT hook; and possibly other kernel SSDT hooks. NOTE: the NtCreateSection vector is covered by CVE-2007-5043.1. NOTE: the vendor disputes that the DuplicateHandle vector is a vulnerability in their code, stating that "it is not an error in our code, but an obscure method for manipulating standard Windows routines to circumvent our self-defense mechanisms."
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.
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.
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) 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.
Insufficient write protection in firmware for Intel(R) Optane(TM) SSD DC P4800X before version E2010435 may allow a privileged user to potentially enable a denial of service via local access.
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.
Firmware update routine in bootloader for Intel(R) Optane(TM) SSD DC P4800X before version E2010435 may allow a privileged user to potentially enable a denial of service via local access.
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.
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.
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.
Input validation error in Intel MinnowBoard 3 Firmware versions prior to 0.65 allow local attacker to cause denial of service via UEFI APIs.
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.
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.
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.
Huawei AR120-S V200R006C10, V200R007C00, V200R008C20, V200R008C30, AR1200 V200R006C10, V200R006C13, V200R007C00, V200R007C01, V200R007C02, V200R008C20, V200R008C30, AR1200-S V200R006C10, V200R007C00, V200R008C20, V200R008C30, AR150 V200R006C10, V200R007C00, V200R007C01, V200R007C02, V200R008C20, V200R008C30, AR150-S V200R006C10, V200R007C00, V200R008C20, V200R008C30, AR160 V200R006C10, V200R006C12, V200R007C00, V200R007C01, V200R007C02, V200R008C20, V200R008C30, AR200 V200R006C10, V200R007C00, V200R007C01, V200R008C20, V200R008C30, AR200-S V200R006C10, V200R007C00, V200R008C20, V200R008C30, AR2200 V200R006C10, V200R006C13, V200R006C16, V200R007C00, V200R007C01, V200R007C02, V200R008C20, V200R008C30, AR2200-S V200R006C10, V200R007C00, V200R008C20, V200R008C30, AR3200 V200R006C10, V200R006C11, V200R007C00, V200R007C01, V200R007C02, V200R008C00, V200R008C10, V200R008C20, V200R008C30, AR3600 V200R006C10, V200R007C00, V200R007C01, V200R008C20, AR510 V200R006C10, V200R006C12, V200R006C13, V200R006C15, V200R006C16, V200R006C17, V200R007C00, V200R008C20, V200R008C30, DP300 V500R002C00, MAX PRESENCE V100R001C00, NetEngine16EX V200R006C10, V200R007C00, V200R008C20, V200R008C30, RP200 V500R002C00, V600R006C00, SRG1300 V200R006C10, V200R007C00, V200R007C02, V200R008C20, V200R008C30, SRG2300 V200R006C10, V200R007C00, V200R007C02, V200R008C20, V200R008C30, SRG3300 V200R006C10, V200R007C00, V200R008C20, V200R008C30, TE30 V100R001C02, V100R001C10, V500R002C00, V600R006C00, TE40 V500R002C00, V600R006C00, TE50 V500R002C00, V600R006C00, TE60 V100R001C01, V100R001C10, V500R002C00, V600R006C00, TP3106 V100R002C00, TP3206 V100R002C00, V100R002C10 have a denial of service vulnerability in the specific module. An authenticated, local attacker may craft a specific XML file to the affected products. Due to improper handling of input, successful exploit will cause some service abnormal.
PEM module of DP300 V500R002C00; IPS Module V500R001C00; V500R001C30; NGFW Module V500R001C00; V500R002C00; NIP6300 V500R001C00; V500R001C30; NIP6600 V500R001C00; V500R001C30; RP200 V500R002C00; V600R006C00; S12700 V200R007C00; V200R007C01; V200R008C00; V200R009C00; V200R010C00; S1700 V200R006C10; V200R009C00; V200R010C00; S2700 V200R006C10; V200R007C00; V200R008C00; V200R009C00; V200R010C00; S5700 V200R006C00; V200R007C00; V200R008C00; V200R009C00; V200R010C00; S6700 V200R008C00; V200R009C00; V200R010C00; S7700 V200R007C00; V200R008C00; V200R009C00; V200R010C00; S9700 V200R007C00; V200R007C01; V200R008C00; V200R009C00; V200R010C00; Secospace USG6300 V500R001C00; V500R001C30; Secospace USG6500 V500R001C00; V500R001C30; Secospace USG6600 V500R001C00; V500R001C30S; TE30 V100R001C02; V100R001C10; V500R002C00; V600R006C00; TE40 V500R002C00; V600R006C00; TE50 V500R002C00; V600R006C00; TE60 V100R001C01; V100R001C10; V500R002C00; V600R006C00; TP3106 V100R002C00; TP3206 V100R002C00; V100R002C10; USG9500 V500R001C00; V500R001C30; ViewPoint 9030 V100R011C02; V100R011C03 has a DoS vulnerability in PEM module of Huawei products due to insufficient verification. An authenticated local attacker can make processing into deadloop by a malicious certificate. The attacker can exploit this vulnerability to cause a denial of service.
TensorFlow is an end-to-end open source platform for machine learning. Incomplete validation in `SparseReshape` results in a denial of service based on a `CHECK`-failure. The implementation(https://github.com/tensorflow/tensorflow/blob/e87b51ce05c3eb172065a6ea5f48415854223285/tensorflow/core/kernels/sparse_reshape_op.cc#L40) has no validation that the input arguments specify a valid sparse tensor. 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 the only affected versions.
TensorFlow is an end-to-end open source platform for machine learning. In affected versions under certain conditions, Go code can trigger a segfault in string deallocation. For string tensors, `C.TF_TString_Dealloc` is called during garbage collection within a finalizer function. However, tensor structure isn't checked until encoding to avoid a performance penalty. The current method for dealloc assumes that encoding succeeded, but segfaults when a string tensor is garbage collected whose encoding failed (e.g., due to mismatched dimensions). To fix this, the call to set the finalizer function is deferred until `NewTensor` returns and, if encoding failed for a string tensor, deallocs are determined based on bytes written. We have patched the issue in GitHub commit 8721ba96e5760c229217b594f6d2ba332beedf22. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, which is the other affected version.
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 segmentation fault in `tf.raw_ops.MaxPoolGrad` caused by missing validation. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/maxpooling_op.cc) misses some validation for the `orig_input` and `orig_output` tensors. The fixes for CVE-2021-29579 were incomplete. We have patched the issue in GitHub commit 136b51f10903e044308cf77117c0ed9871350475. 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.