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| CVE | Vendors | Products | Updated | CVSS v3.1 |
|---|---|---|---|---|
| CVE-2021-37711 | 1 Shopware | 1 Shopware | 2024-11-21 | 8.8 High |
| Versions prior to 6.4.3.1 contain an authenticated server-side request forgery vulnerability in file upload via URL. 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. | ||||
| CVE-2021-37710 | 1 Shopware | 1 Shopware | 2024-11-21 | 8 High |
| Shopware is an open source eCommerce platform. Versions prior to 6.4.3.1 contain a Cross-Site Scripting vulnerability via SVG media files. 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. | ||||
| CVE-2021-37708 | 1 Shopware | 1 Shopware | 2024-11-21 | 8.8 High |
| Shopware is an open source eCommerce platform. Versions prior to 6.4.3.1 contain a command injection vulnerability in mail agent settings. 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. | ||||
| CVE-2021-37702 | 1 Pimcore | 1 Pimcore | 2024-11-21 | 8 High |
| Pimcore is an open source data & experience management platform. Prior to version 10.1.1, Data Object CSV import allows formular injection. The problem is patched in 10.1.1. Aside from upgrading, one may apply the patch manually as a workaround. | ||||
| CVE-2021-37701 | 5 Debian, Npmjs, Oracle and 2 more | 9 Debian Linux, Tar, Graalvm and 6 more | 2024-11-21 | 8.2 High |
| The npm package "tar" (aka node-tar) before versions 4.4.16, 5.0.8, and 6.1.7 has an arbitrary file creation/overwrite and arbitrary code execution vulnerability. node-tar aims to guarantee that any file whose location would be modified by a symbolic link is not extracted. This is, in part, achieved by ensuring that extracted directories are not symlinks. Additionally, in order to prevent unnecessary stat calls to determine whether a given path is a directory, paths are cached when directories are created. This logic was insufficient when extracting tar files that contained both a directory and a symlink with the same name as the directory, where the symlink and directory names in the archive entry used backslashes as a path separator on posix systems. The cache checking logic used both `\` and `/` characters as path separators, however `\` is a valid filename character on posix systems. By first creating a directory, and then replacing that directory with a symlink, it was thus possible to bypass node-tar symlink checks on directories, essentially allowing an untrusted tar file to symlink into an arbitrary location and subsequently extracting arbitrary files into that location, thus allowing arbitrary file creation and overwrite. Additionally, a similar confusion could arise on case-insensitive filesystems. If a tar archive contained a directory at `FOO`, followed by a symbolic link named `foo`, then on case-insensitive file systems, the creation of the symbolic link would remove the directory from the filesystem, but _not_ from the internal directory cache, as it would not be treated as a cache hit. A subsequent file entry within the `FOO` directory would then be placed in the target of the symbolic link, thinking that the directory had already been created. These issues were addressed in releases 4.4.16, 5.0.8 and 6.1.7. The v3 branch of node-tar has been deprecated and did not receive patches for these issues. If you are still using a v3 release we recommend you update to a more recent version of node-tar. If this is not possible, a workaround is available in the referenced GHSA-9r2w-394v-53qc. | ||||
| CVE-2021-37697 | 1 Tmerc-cogs Project | 1 Tmerc-cogs | 2024-11-21 | 7.1 High |
| tmerc-cogs are a collection of open source plugins for the Red Discord bot. A vulnerability has been found in the code that allows any user to access sensitive information by crafting a specific membership event message. Issue is patched in commit d63c49b4cfc30c795336e4fff08cba3795e0fcc0. As a workaround users may unload the Welcome cog. | ||||
| CVE-2021-37696 | 1 Tmerc-cogs Project | 1 Tmerc-cogs | 2024-11-21 | 7.1 High |
| tmerc-cogs are a collection of open source plugins for the Red Discord bot. A vulnerability has been found in the code that allows any user to access sensitive information by crafting a specific MassDM message. Issue is patched in commit 92325be650a6c17940cc52611797533ed95dbbe1. All users are advised to update to the current commit. As a workaround users may unload the MassDM cog or globally disable the `[p]massdm` command. | ||||
| CVE-2021-37695 | 4 Ckeditor, Debian, Fedoraproject and 1 more | 12 Ckeditor, Debian Linux, Fedora and 9 more | 2024-11-21 | 7.3 High |
| ckeditor is an open source WYSIWYG HTML editor with rich content support. A potential vulnerability has been discovered in CKEditor 4 [Fake Objects](https://ckeditor.com/cke4/addon/fakeobjects) package. The vulnerability allowed to inject malformed Fake Objects HTML, which could result in executing JavaScript code. It affects all users using the CKEditor 4 plugins listed above at version < 4.16.2. The problem has been recognized and patched. The fix will be available in version 4.16.2. | ||||
| CVE-2021-37694 | 1 Asyncapi | 1 Java-spring-cloud-stream-template | 2024-11-21 | 8.7 High |
| @asyncapi/java-spring-cloud-stream-template generates a Spring Cloud Stream (SCSt) microservice. In versions prior to 0.7.0 arbitrary code injection was possible when an attacker controls the AsyncAPI document. An example is provided in GHSA-xj6r-2jpm-qvxp. There are no mitigations available and all users are advised to update. | ||||
| CVE-2021-37689 | 1 Google | 1 Tensorflow | 2024-11-21 | 7.8 High |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can craft a TFLite model that would trigger a null pointer dereference, which would result in a crash and denial of service. This is caused by the MLIR optimization of `L2NormalizeReduceAxis` operator. The [implementation](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/compiler/mlir/lite/transforms/optimize.cc#L67-L70) unconditionally dereferences a pointer to an iterator to a vector without checking that the vector has elements. We have patched the issue in GitHub commit d6b57f461b39fd1aa8c1b870f1b974aac3554955. 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. | ||||
| CVE-2021-37688 | 1 Google | 1 Tensorflow | 2024-11-21 | 7.8 High |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can craft a TFLite model that would trigger a null pointer dereference, which would result in a crash and denial of service. The [implementation](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/lite/kernels/internal/optimized/optimized_ops.h#L268-L285) unconditionally dereferences a pointer. We have patched the issue in GitHub commit 15691e456c7dc9bd6be203b09765b063bf4a380c. 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. | ||||
| CVE-2021-37681 | 1 Google | 1 Tensorflow | 2024-11-21 | 7.8 High |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of SVDF in TFLite is [vulnerable to a null pointer error](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/svdf.cc#L300-L313). The [`GetVariableInput` function](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/kernel_util.cc#L115-L119) can return a null pointer but `GetTensorData` assumes that the argument is always a valid tensor. Furthermore, because `GetVariableInput` calls [`GetMutableInput`](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/kernel_util.cc#L82-L90) which might return `nullptr`, the `tensor->is_variable` expression can also trigger a null pointer exception. We have patched the issue in GitHub commit 5b048e87e4e55990dae6b547add4dae59f4e1c76. 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. | ||||
| CVE-2021-37679 | 1 Google | 1 Tensorflow | 2024-11-21 | 7.1 High |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions it is possible to nest a `tf.map_fn` within another `tf.map_fn` call. However, if the input tensor is a `RaggedTensor` and there is no function signature provided, code assumes the output is a fully specified tensor and fills output buffer with uninitialized contents from the heap. The `t` and `z` outputs should be identical, however this is not the case. The last row of `t` contains data from the heap which can be used to leak other memory information. The bug lies in the conversion from a `Variant` tensor to a `RaggedTensor`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/ragged_tensor_from_variant_op.cc#L177-L190) does not check that all inner shapes match and this results in the additional dimensions. The same implementation can result in data loss, if input tensor is tweaked. We have patched the issue in GitHub commit 4e2565483d0ffcadc719bd44893fb7f609bb5f12. 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. | ||||
| CVE-2021-37676 | 1 Google | 1 Tensorflow | 2024-11-21 | 7.8 High |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in `tf.raw_ops.SparseFillEmptyRows`. The shape inference [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/ops/sparse_ops.cc#L608-L634) does not validate that the input arguments are not empty tensors. We have patched the issue in GitHub commit 578e634b4f1c1c684d4b4294f9e5281b2133b3ed. 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. | ||||
| CVE-2021-37671 | 1 Google | 1 Tensorflow | 2024-11-21 | 7.8 High |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in `tf.raw_ops.Map*` and `tf.raw_ops.OrderedMap*` operations. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/map_stage_op.cc#L222-L248) has a check in place to ensure that `indices` is in ascending order, but does not check that `indices` is not empty. We have patched the issue in GitHub commit 532f5c5a547126c634fefd43bbad1dc6417678ac. 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. | ||||
| CVE-2021-37667 | 1 Google | 1 Tensorflow | 2024-11-21 | 7.8 High |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in `tf.raw_ops.UnicodeEncode`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/unicode_ops.cc#L533-L539) reads the first dimension of the `input_splits` tensor before validating that this tensor is not empty. We have patched the issue in GitHub commit 2e0ee46f1a47675152d3d865797a18358881d7a6. 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. | ||||
| CVE-2021-37666 | 1 Google | 1 Tensorflow | 2024-11-21 | 7.8 High |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in `tf.raw_ops.RaggedTensorToVariant`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/ragged_tensor_to_variant_op.cc#L129) has an incomplete validation of the splits values, missing the case when the argument would be empty. We have patched the issue in GitHub commit be7a4de6adfbd303ce08be4332554dff70362612. 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. | ||||
| CVE-2021-37665 | 1 Google | 1 Tensorflow | 2024-11-21 | 7.8 High |
| 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. | ||||
| CVE-2021-37664 | 1 Google | 1 Tensorflow | 2024-11-21 | 7.3 High |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can read from outside of bounds of heap allocated data by sending specially crafted illegal arguments to `BoostedTreesSparseCalculateBestFeatureSplit`. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/stats_ops.cc) needs to validate that each value in `stats_summary_indices` is in range. We have patched the issue in GitHub commit e84c975313e8e8e38bb2ea118196369c45c51378. 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. | ||||
| CVE-2021-37663 | 1 Google | 1 Tensorflow | 2024-11-21 | 7.8 High |
| 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. | ||||