Vulnerabilities (CVE)

IBM Tivoli Key Lifecycle Manager 3.0, 3.0.1, 4.0, and 4.1 receives input or data, but it does not validate or incorrectly validates that the input has the properties that are required to process the data safely and correctly.

IBM Tivoli Key Lifecycle Manager 3.0, 3.0.1, 4.0, and 4.1 receives input or data, but it does not validate or incorrectly validates that the input has the properties that are required to process the data safely and correctly.

IBM Security Verify 10.0.0, 10.0.1.0, and 10.0.2.0 could disclose sensitive information due to hazardous input validation during QR code generation. IBM X-Force ID: 212040.

IBM DataPower Gateway V10CD, 10.0.1, and 2108.4.1 could allow a remote attacker to bypass security restrictions, caused by the improper validation of input. By sending a specially crafted JSON message, an attacker could exploit this vulnerability to modify structure and fields. IBM X-Force ID: 209824.

The affected product is vulnerable to improper input validation in the restore file. This enables an attacker to provide malicious config files to replace any file on disk.

The affected product’s OS Service does not verify any given parameter. A user can supply any type of parameter that will be passed to inner calls without checking the type of the parameter or the value.

Improper input validation in the National Instruments NI-PAL driver in versions 20.0.0 and prior may allow a privileged user to potentially enable escalation of privilege via local access.

Due to insufficient input validation of Kyma, authenticated users can pass a Header of their choice and escalate privileges which can completely compromise the cluster.

Inappropriate implementation in input in Google Chrome prior to 96.0.4664.45 allowed an attacker who convinced a user to install a malicious extension to bypass navigation restrictions via a crafted Chrome Extension.

Insufficient validation of untrusted input Downloads in Google Chrome prior to 95.0.4638.54 allowed a remote attacker to bypass navigation restrictions via a malicious file.

WriteRegistry function in TSSServiSign component does not filter and verify users’ input, remote attackers can rewrite to the registry without permissions thus perform hijack attacks to execute arbitrary code.

Mattermost 6.0 and earlier fails to sufficiently validate parameters during post creation, which allows authenticated attackers to cause a client-side crash of the web application via a maliciously crafted post.

Shopware is an open source eCommerce platform. Versions prior to 6.4.3.1 contain a vulnerability that allows manipulation of product reviews via API. Version 6.4.3.1 contains a patch. As workarounds for older versions of 6.1, 6.2, and 6.3, corresponding security measures are also available via a plugin.

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 encodi ... 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.

Show More

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` ... 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.

Show More

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 patche ... 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.

Show More

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 ... 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.

Show More

TensorFlow is an end-to-end open source platform for machine learning. In affected versions due to incomplete validation in MKL implementation of requantization, an attacker can trigger undefined behavior via binding a reference to a null pointer or can access data outside the bounds of heap allocated arrays. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/mkl/mkl_requantization_range_per_channel_op.cc) does not ... TensorFlow is an end-to-end open source platform for machine learning. In affected versions due to incomplete validation in MKL implementation of requantization, an attacker can trigger undefined behavior via binding a reference to a null pointer or can access data outside the bounds of heap allocated arrays. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/mkl/mkl_requantization_range_per_channel_op.cc) does not validate the dimensions of the `input` tensor. A similar issue occurs in `MklRequantizePerChannelOp`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/mkl/mkl_requantize_per_channel_op.cc) does not perform full validation for all the input arguments. We have patched the issue in GitHub commit 9e62869465573cb2d9b5053f1fa02a81fce21d69 and in the Github commit 203214568f5bc237603dbab6e1fd389f1572f5c9. 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.

Show More

TensorFlow is an end-to-end open source platform for machine learning. In affected versions due to incomplete validation in `tf.raw_ops.QuantizeV2`, an attacker can trigger undefined behavior via binding a reference to a null pointer or can access data outside the bounds of heap allocated arrays. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/quantize_op.cc#L59) has some validation but does not check that `min_r ... TensorFlow is an end-to-end open source platform for machine learning. In affected versions due to incomplete validation in `tf.raw_ops.QuantizeV2`, an attacker can trigger undefined behavior via binding a reference to a null pointer or can access data outside the bounds of heap allocated arrays. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/quantize_op.cc#L59) has some validation but does not check that `min_range` and `max_range` both have the same non-zero number of elements. If `axis` is provided (i.e., not `-1`), then validation should check that it is a value in range for the rank of `input` tensor and then the lengths of `min_range` and `max_range` inputs match the `axis` dimension of the `input` tensor. We have patched the issue in GitHub commit 6da6620efad397c85493b8f8667b821403516708. 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.

Show More

In FreeRDP before 2.4.0 on Windows, wf_cliprdr_server_file_contents_request in client/Windows/wf_cliprdr.c has missing input checks for a FILECONTENTS_RANGE File Contents Request PDU.

In FreeRDP before 2.4.0 on Windows, wf_cliprdr_server_file_contents_request in client/Windows/wf_cliprdr.c has missing input checks for a FILECONTENTS_SIZE File Contents Request PDU.

The PowerPlay Web component of Mitel Interaction Recording Multitenancy systems before 6.7 could allow a user (with Administrator rights) to replay a previously recorded conversation of another tenant due to insufficient validation.

A vulnerability has been identified in SIPROTEC 5 relays with CPU variants CP050 (All versions < V8.80), SIPROTEC 5 relays with CPU variants CP100 (All versions < V8.80), SIPROTEC 5 relays with CPU variants CP300 (All versions < V8.80). Received webpackets are not properly processed. An unauthenticated remote attacker with access to any of the Ethernet interfaces could send specially crafted packets to force a restart of the target device.

Improper Input Validation vulnerability in header parsing of Apache Traffic Server allows an attacker to smuggle requests. This issue affects Apache Traffic Server 8.0.0 to 8.1.2 and 9.0.0 to 9.1.0.

Improper input validation vulnerability in header parsing of Apache Traffic Server allows an attacker to smuggle requests. This issue affects Apache Traffic Server 8.0.0 to 8.1.2 and 9.0.0 to 9.0.1.

Improper input validation vulnerability in header parsing of Apache Traffic Server allows an attacker to smuggle requests. This issue affects Apache Traffic Server 8.0.0 to 8.1.2 and 9.0.0 to 9.1.0.

PCManager has a Weaknesses Introduced During Design vulnerability .Successful exploitation of this vulnerability may cause that the PIN of the subscriber is changed.

There is a Improper Input Validation vulnerability in Huawei Smartphone.Successful exploitation of this vulnerability may lead to user privacy disclosed.

There is a Improper Input Validation vulnerability in Huawei Smartphone.Successful exploitation of this vulnerability may lead to system denial of service.

There is a Improper Input Validation vulnerability in Huawei Smartphone.Successful exploitation of this vulnerability may lead to malicious invoking other functions of the Smart Assistant through text messages.

There is a Improper Input Validation vulnerability in Huawei Smartphone.Successful exploitation of this vulnerability may lead to nearby crash.

There is a Improper Input Validation vulnerability in Huawei Smartphone.Successful exploitation of this vulnerability may lead to SAMGR Heap Address Leakage.

There is a Improper Input Validation vulnerability in Huawei Smartphone.Successful exploitation of this vulnerability may lead to fake visitors to control PC,play a video,etc.

There is an Input verification vulnerability in Huawei Smartphone.Successful exploitation of this vulnerability may cause some services to restart.

There is an Input verification vulnerability in Huawei Smartphone.Successful exploitation of this vulnerability may cause Bluetooth DoS.

There is a Improper Input Validation vulnerability in Huawei Smartphone.Successful exploitation of this vulnerability will cause kernel crash.

There is a Improper Input Validation vulnerability in Huawei Smartphone.Successful exploitation of this vulnerability will cause kernel crash.

There is a Improper Input Validation vulnerability in Huawei Smartphone.Successful exploitation of this vulnerability will cause kernel crash.

There is a Improper Input Validation vulnerability in Huawei Smartphone.Successful exploitation of this vulnerability will cause kernel crash.

There is a Improper Input Validation vulnerability in Huawei Smartphone.Successful exploitation of this vulnerability will cause kernel crash.