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This CVE ID has been rejected or withdrawn by its CVE Numbering Authority because it is Unused

This CVE ID has been rejected or withdrawn by its CVE Numbering Authority because it is Unused

This CVE ID has been rejected or withdrawn by its CVE Numbering Authority because it is Unused

A Cross Site Request Forgery (CSRF) vulnerability exists in Backdrop CMS 1.20, which allows Remote Attackers to gain Remote Code Execution (RCE) on the Hosting Webserver via uploading a maliciously add-on with crafted PHP file. NOTE: the vendor disputes this because the attack requires a session cookie of a high-privileged authenticated user who is entitled to install arbitrary add-ons

Mastodon before 3.3.2 and 3.4.x before 3.4.6 has incorrect access control because it does not compact incoming signed JSON-LD activities. (JSON-LD signing has been supported since version 1.6.0.)

Tensorflow is an Open Source Machine Learning Framework. The implementation of `SparseCountSparseOutput` is vulnerable to a heap overflow. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Tensorflow is an Open Source Machine Learning Framework. ### Impact An attacker can craft a TFLite model that would trigger a division by zero in the implementation of depthwise convolutions. The parameters of the convolution can be user controlled and are also used within a division operation to determine the size of the padding that needs to be added before applying the convolution. There is no check before this division that the divisor is strictly positive. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Tensorflow is an Open Source Machine Learning Framework. The implementation of `*Bincount` operations allows malicious users to cause denial of service by passing in arguments which would trigger a `CHECK`-fail. There are several conditions that the input arguments must satisfy. Some are not caught during shape inference and others are not caught during kernel implementation. This results in `CHECK` failures later when the output tensors get allocated. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

An issue was discovered in Online-Movie-Ticket-Booking-System 1.0. The file about.php does not perform input validation on the 'id' paramter. An attacker can append SQL queries to the input to extract sensitive information from the database.

Tensorflow is an Open Source Machine Learning Framework. The implementation of `SparseCountSparseOutput` can be made to crash a TensorFlow process by an integer overflow whose result is then used in a memory allocation. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Tensorflow is an Open Source Machine Learning Framework. The implementation of `QuantizedMaxPool` has an undefined behavior where user controlled inputs can trigger a reference binding to null pointer. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Tensorflow is an Open Source Machine Learning Framework. The implementation of `MapStage` is vulnerable a `CHECK`-fail if the key tensor is not a scalar. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Tensorflow is an Open Source Machine Learning Framework. The implementation of `FractionalMaxPool` can be made to crash a TensorFlow process via a division by 0. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Tensorflow is an Open Source Machine Learning Framework. Multiple operations in TensorFlow can be used to trigger a denial of service via `CHECK`-fails (i.e., assertion failures). This is similar to TFSA-2021-198 and has similar fixes. We have patched the reported issues in multiple GitHub commits. It is possible that other similar instances exist in TensorFlow, we will issue fixes as these are discovered. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Tensorflow is an Open Source Machine Learning Framework. The implementation of `UnravelIndex` is vulnerable to a division by zero caused by an integer overflow bug. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Tensorflow is an Open Source Machine Learning Framework. The estimator for the cost of some convolution operations can be made to execute a division by 0. The function fails to check that the stride argument is strictly positive. Hence, the fix is to add a check for the stride argument to ensure it is valid. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Tensorflow is an Open Source Machine Learning Framework. The implementation of `SparseTensorSliceDataset` has an undefined behavior: under certain condition it can be made to dereference a `nullptr` value. The 3 input arguments to `SparseTensorSliceDataset` represent a sparse tensor. However, there are some preconditions that these arguments must satisfy but these are not validated in the implementation. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Tensorflow is an Open Source Machine Learning Framework. The implementations of `Sparse*Cwise*` ops are vulnerable to integer overflows. These can be used to trigger large allocations (so, OOM based denial of service) or `CHECK`-fails when building new `TensorShape` objects (so, assert failures based denial of service). We are missing some validation on the shapes of the input tensors as well as directly constructing a large `TensorShape` with user-provided dimensions. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Tensorflow is an Open Source Machine Learning Framework. The implementation of `AddManySparseToTensorsMap` is vulnerable to an integer overflow which results in a `CHECK`-fail when building new `TensorShape` objects (so, an assert failure based denial of service). We are missing some validation on the shapes of the input tensors as well as directly constructing a large `TensorShape` with user-provided dimensions. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for `ConcatV2` can be used to trigger a denial of service attack via a segfault caused by a type confusion. The `axis` argument is translated into `concat_dim` in the `ConcatShapeHelper` helper function. Then, a value for `min_rank` is computed based on `concat_dim`. This is then used to validate that the `values` tensor has at least the required rank. However, `WithRankAtLeast` receives the lower bound as a 64-bits value and then compares it against the maximum 32-bits integer value that could be represented. Due to the fact that `min_rank` is a 32-bits value and the value of `axis`, the `rank` argument is a negative value, so the error check is bypassed. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Tensorflow is an Open Source Machine Learning Framework. The implementation of `StringNGrams` can be used to trigger a denial of service attack by causing an out of memory condition after an integer overflow. We are missing a validation on `pad_witdh` and that result in computing a negative value for `ngram_width` which is later used to allocate parts of the output. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Tensorflow is an Open Source Machine Learning Framework. The implementation of `ThreadPoolHandle` can be used to trigger a denial of service attack by allocating too much memory. This is because the `num_threads` argument is only checked to not be negative, but there is no upper bound on its value. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for `Dequantize` is vulnerable to an integer overflow weakness. The `axis` argument can be `-1` (the default value for the optional argument) or any other positive value at most the number of dimensions of the input. Unfortunately, the upper bound is not checked, and, since the code computes `axis + 1`, an attacker can trigger an integer overflow. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Tensorflow is an Open Source Machine Learning Framework. The implementation of `Dequantize` does not fully validate the value of `axis` and can result in heap OOB accesses. The `axis` argument can be `-1` (the default value for the optional argument) or any other positive value at most the number of dimensions of the input. Unfortunately, the upper bound is not checked and this results in reading past the end of the array containing the dimensions of the input tensor. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for `ReverseSequence` does not fully validate the value of `batch_dim` and can result in a heap OOB read. There is a check to make sure the value of `batch_dim` does not go over the rank of the input, but there is no check for negative values. Negative dimensions are allowed in some cases to mimic Python's negative indexing (i.e., indexing from the end of the array), however if the value is too negative then the implementation of `Dim` would access elements before the start of an array. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Tensorflow is an Open Source Machine Learning Framework. The implementation of `FractionalAvgPoolGrad` does not consider cases where the input tensors are invalid allowing an attacker to read from outside of bounds of heap. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

SQL Injection vulnerability discovered in Unified Office Total Connect Now that would allow an attacker to extract sensitive information through a cookie parameter.

Victor CMS v1.0 was discovered to contain a SQL injection vulnerability that allows attackers to inject arbitrary commands via 'user_firstname' parameter.

mozilo2.0 was discovered to be vulnerable to directory traversal attacks via the parameter curent_dir.

Multiple cross-site scripting (XSS) vulnerabilities in the component outcomes_addProcess.php of Gibbon CMS v22.0.01 allow attackers to execute arbitrary web scripts or HTML via a crafted payload insterted into the name, category, description parameters.

An issue was discovered in NvmExpressDxe in Insyde InsydeH2O with kernel 5.1 through 5.5. An SMM memory corruption vulnerability allows an attacker to write fixed or predictable data to SMRAM. Exploiting this issue could lead to escalating privileges to SMM.

An issue was discovered in Kernel 5.x in Insyde InsydeH2O, affecting HddPassword. Software SMI services that use the Communicate() function of the EFI_SMM_COMMUNICATION_PROTOCOL do not check whether the address of the buffer is valid, which allows use of SMRAM, MMIO, or OS kernel addresses.

An issue was discovered in UsbCoreDxe in Insyde InsydeH2O with kernel 5.5 before 05.51.45, 5.4 before 05.43.45, 5.3 before 05.35.45, 5.2 before 05.26.45, 5.1 before 05.16.45, and 5.0 before 05.08.45. An SMM callout vulnerability allows an attacker to hijack execution flow of code running in System Management Mode. Exploiting this issue could lead to escalating privileges to SMM.

An issue was discovered in StorageSecurityCommandDxe in Insyde InsydeH2O with Kernel 5.1 before 05.14.28, Kernel 5.2 before 05.24.28, and Kernel 5.3 before 05.32.25. An SMM callout vulnerability allows an attacker to hijack execution flow of code running in System Management Mode. Exploiting this issue could lead to escalating privileges to SMM.

An issue was discovered in SdHostDriver in the kernel 5.0 through 5.5 in Insyde InsydeH2O. There is an SMM callout that allows an attacker to access the System Management Mode and execute arbitrary code. This occurs because of a Numeric Range Comparison Without a Minimum Check.

An issue was discovered in Insyde InsydeH2O with Kernel 5.0 before 05.08.42, Kernel 5.1 before 05.16.42, Kernel 5.2 before 05.26.42, Kernel 5.3 before 05.35.42, Kernel 5.4 before 05.42.51, and Kernel 5.5 before 05.50.51. An SMM memory corruption vulnerability in FvbServicesRuntimeDxe allows a possible attacker to write fixed or predictable data to SMRAM. Exploiting this issue could lead to escalating privileges to SMM.

An issue was discovered in NvmExpressDxe in the kernel 5.0 through 5.5 in Insyde InsydeH2O. Because of an Untrusted Pointer Dereference that causes SMM memory corruption, an attacker may be able to write fixed or predictable data to SMRAM. Exploiting this issue could lead to escalating privileges to SMM.

An issue was discovered in Insyde InsydeH2O Kernel 5.0 before 05.09.11, 5.1 before 05.17.11, 5.2 before 05.27.11, 5.3 before 05.36.11, 5.4 before 05.44.11, and 5.5 before 05.52.11 affecting FwBlockServiceSmm. Software SMI services that use the Communicate() function of the EFI_SMM_COMMUNICATION_PROTOCOL do not check whether the address of the buffer is valid, which allows use of SMRAM, MMIO, or OS kernel addresses.

An issue was discovered in Insyde InsydeH2O Kernel 5.0 through 05.08.41, Kernel 5.1 through 05.16.41, Kernel 5.2 before 05.23.22, and Kernel 5.3 before 05.32.22. An Int15ServiceSmm SMM callout vulnerability allows an attacker to hijack execution flow of code running in System Management Mode. Exploiting this issue could lead to escalating privileges to SMM.

An issue was discovered in AhciBusDxe in the kernel 5.0 through 5.5 in Insyde InsydeH2O. Because of an Untrusted Pointer Dereference that causes SMM memory corruption, an attacker may be able to write fixed or predictable data to SMRAM. Exploiting this issue could lead to escalating privileges to SMM.

An issue was discovered in NvmExpressDxe in the kernel 5.0 through 5.5 in Insyde InsydeH2O. There is an SMM callout that allows an attacker to access the System Management Mode and execute arbitrary code. This occurs because of Inclusion of Functionality from an Untrusted Control Sphere.

An issue was discovered in AhciBusDxe in Insyde InsydeH2O with kernel 5.1 through 5.5. An SMM memory corruption vulnerability allows an attacker to write fixed or predictable data to SMRAM. Exploiting this issue could lead to escalating privileges to SMM.

An issue was discovered in Insyde InsydeH2O Kernel 5.0 before 05.08.41, Kernel 5.1 before 05.16.41, Kernel 5.2 before 05.26.41, Kernel 5.3 before 05.35.41, and Kernel 5.4 before 05.42.20. A stack-based buffer overflow leads toarbitrary code execution in UEFI DisplayTypeDxe DXE driver.

An issue was discovered in HddPassword in Insyde InsydeH2O with kernel 5.1 before 05.16.23, 5.2 before 05.26.23, 5.3 before 05.35.23, 5.4 before 05.43.22, and 5.5 before 05.51.22. An SMM memory corruption vulnerability allows an attacker to write fixed or predictable data to SMRAM. Exploiting this issue could lead to escalating privileges to SMM.

An issue was discovered in AhciBusDxe in the kernel 5.0 through 5.5 in Insyde InsydeH2O. There is an SMM callout that allows an attacker to access the System Management Mode and execute arbitrary code. This occurs because of Inclusion of Functionality from an Untrusted Control Sphere.

A vulnerability exists in System Management Interrupt (SWSMI) handler of InsydeH2O UEFI Firmware code located in SWSMI handler that dereferences gRT (EFI_RUNTIME_SERVICES) pointer to call a GetVariable service, which is located outside of SMRAM. This can result in code execution in SMM (escalating privilege from ring 0 to ring -2).

An XSS vulnerability was found in Kibana index patterns. Using this vulnerability, an authenticated user with permissions to create index patterns can inject malicious javascript into the index pattern which could execute against other users

Pillow before 9.0.1 allows attackers to delete files because spaces in temporary pathnames are mishandled.

A flaw was found in Quarkus. The state and potentially associated permissions can leak from one web request to another in RestEasy Reactive. This flaw allows a low-privileged user to perform operations on the database with a different set of privileges than intended.

An issue was discovered in AhciBusDxe in Insyde InsydeH2O with kernel 5.0 before 05.08.41, 5.1 before 05.16.29, 5.2 before 05.26.29, 5.3 before 05.35.29, 5.4 before 05.43.29, and 5.5 before 05.51.29. An SMM callout vulnerability allows an attacker to hijack the execution flow of code running in System Management Mode. Exploiting this issue could lead to escalating privileges to SMM.