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| CVE | Vendors | Products | Updated | CVSS v3.1 |
|---|---|---|---|---|
| CVE-2021-37654 | 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 trigger a crash via a `CHECK`-fail in debug builds of TensorFlow using `tf.raw_ops.ResourceGather` or a read from outside the bounds of heap allocated data in the same API in a release build. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/resource_variable_ops.cc#L660-L668) does not check that the `batch_dims` value that the user supplies is less than the rank of the input tensor. Since the implementation uses several for loops over the dimensions of `tensor`, this results in reading data from outside the bounds of heap allocated buffer backing the tensor. We have patched the issue in GitHub commit bc9c546ce7015c57c2f15c168b3d9201de679a1d. 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-2021-37652 | 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 for `tf.raw_ops.BoostedTreesCreateEnsemble` can result in a use after free error if an attacker supplies specially crafted arguments. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/boosted_trees/resource_ops.cc#L55) uses a reference counted resource and decrements the refcount if the initialization fails, as it should. However, when the code was written, the resource was represented as a naked pointer but later refactoring has changed it to be a smart pointer. Thus, when the pointer leaves the scope, a subsequent `free`-ing of the resource occurs, but this fails to take into account that the refcount has already reached 0, thus the resource has been already freed. During this double-free process, members of the resource object are accessed for cleanup but they are invalid as the entire resource has been freed. We have patched the issue in GitHub commit 5ecec9c6fbdbc6be03295685190a45e7eee726ab. 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-2021-37651 | 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 the implementation for `tf.raw_ops.FractionalAvgPoolGrad` can be tricked into accessing data outside of bounds of heap allocated buffers. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/fractional_avg_pool_op.cc#L205) does not validate that the input tensor is non-empty. Thus, code constructs an empty `EigenDoubleMatrixMap` and then accesses this buffer with indices that are outside of the empty area. We have patched the issue in GitHub commit 0f931751fb20f565c4e94aa6df58d54a003cdb30. 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-2021-37650 | 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 for `tf.raw_ops.ExperimentalDatasetToTFRecord` and `tf.raw_ops.DatasetToTFRecord` can trigger heap buffer overflow and segmentation fault. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/data/experimental/to_tf_record_op.cc#L93-L102) assumes that all records in the dataset are of string type. However, there is no check for that, and the example given above uses numeric types. We have patched the issue in GitHub commit e0b6e58c328059829c3eb968136f17aa72b6c876. 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-2021-37649 | 1 Google | 1 Tensorflow | 2024-11-21 | 7.7 High |
| TensorFlow is an end-to-end open source platform for machine learning. The code for `tf.raw_ops.UncompressElement` can be made to trigger a null pointer dereference. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/data/experimental/compression_ops.cc#L50-L53) obtains a pointer to a `CompressedElement` from a `Variant` tensor and then proceeds to dereference it for decompressing. There is no check that the `Variant` tensor contained a `CompressedElement`, so the pointer is actually `nullptr`. We have patched the issue in GitHub commit 7bdf50bb4f5c54a4997c379092888546c97c3ebd. 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-2021-37648 | 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 code for `tf.raw_ops.SaveV2` does not properly validate the inputs and an attacker can trigger a null pointer dereference. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/save_restore_v2_ops.cc) uses `ValidateInputs` to check that the input arguments are valid. This validation would have caught the illegal state represented by the reproducer above. However, the validation uses `OP_REQUIRES` which translates to setting the `Status` object of the current `OpKernelContext` to an error status, followed by an empty `return` statement which just terminates the execution of the function it is present in. However, this does not mean that the kernel execution is finalized: instead, execution continues from the next line in `Compute` that follows the call to `ValidateInputs`. This is equivalent to lacking the validation. We have patched the issue in GitHub commit 9728c60e136912a12d99ca56e106b7cce7af5986. 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-2021-37647 | 1 Google | 1 Tensorflow | 2024-11-21 | 7.7 High |
| TensorFlow is an end-to-end open source platform for machine learning. When a user does not supply arguments that determine a valid sparse tensor, `tf.raw_ops.SparseTensorSliceDataset` implementation can be made to dereference a null pointer. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/data/sparse_tensor_slice_dataset_op.cc#L240-L251) has some argument validation but fails to consider the case when either `indices` or `values` are provided for an empty sparse tensor when the other is not. If `indices` is empty, then [code that performs validation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/data/sparse_tensor_slice_dataset_op.cc#L260-L261) (i.e., checking that the indices are monotonically increasing) results in a null pointer dereference. If `indices` as provided by the user is empty, then `indices` in the C++ code above is backed by an empty `std::vector`, hence calling `indices->dim_size(0)` results in null pointer dereferencing (same as calling `std::vector::at()` on an empty vector). We have patched the issue in GitHub commit 02cc160e29d20631de3859c6653184e3f876b9d7. 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-2021-37643 | 1 Google | 1 Tensorflow | 2024-11-21 | 7.7 High |
| TensorFlow is an end-to-end open source platform for machine learning. If a user does not provide a valid padding value to `tf.raw_ops.MatrixDiagPartOp`, then the code triggers a null pointer dereference (if input is empty) or produces invalid behavior, ignoring all values after the first. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/linalg/matrix_diag_op.cc#L89) reads the first value from a tensor buffer without first checking that the tensor has values to read from. We have patched the issue in GitHub commit 482da92095c4d48f8784b1f00dda4f81c28d2988. 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-2021-37641 | 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 if the arguments to `tf.raw_ops.RaggedGather` don't determine a valid ragged tensor code can trigger a read from outside of bounds of heap allocated buffers. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/ragged_gather_op.cc#L70) directly reads the first dimension of a tensor shape before checking that said tensor has rank of at least 1 (i.e., it is not a scalar). Furthermore, the implementation does not check that the list given by `params_nested_splits` is not an empty list of tensors. We have patched the issue in GitHub commit a2b743f6017d7b97af1fe49087ae15f0ac634373. 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-2021-37639 | 1 Google | 1 Tensorflow | 2024-11-21 | 8.4 High |
| TensorFlow is an end-to-end open source platform for machine learning. When restoring tensors via raw APIs, if the tensor name is not provided, TensorFlow can be tricked into dereferencing a null pointer. Alternatively, attackers can read memory outside the bounds of heap allocated data by providing some tensor names but not enough for a successful restoration. The [implementation](https://github.com/tensorflow/tensorflow/blob/47a06f40411a69c99f381495f490536972152ac0/tensorflow/core/kernels/save_restore_tensor.cc#L158-L159) retrieves the tensor list corresponding to the `tensor_name` user controlled input and immediately retrieves the tensor at the restoration index (controlled via `preferred_shard` argument). This occurs without validating that the provided list has enough values. If the list is empty this results in dereferencing a null pointer (undefined behavior). If, however, the list has some elements, if the restoration index is outside the bounds this results in heap OOB read. We have patched the issue in GitHub commit 9e82dce6e6bd1f36a57e08fa85af213e2b2f2622. 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-2021-37638 | 1 Google | 1 Tensorflow | 2024-11-21 | 7.7 High |
| TensorFlow is an end-to-end open source platform for machine learning. Sending invalid argument for `row_partition_types` of `tf.raw_ops.RaggedTensorToTensor` API results in a null pointer dereference and undefined behavior. The [implementation](https://github.com/tensorflow/tensorflow/blob/47a06f40411a69c99f381495f490536972152ac0/tensorflow/core/kernels/ragged_tensor_to_tensor_op.cc#L328) accesses the first element of a user supplied list of values without validating that the provided list is not empty. We have patched the issue in GitHub commit 301ae88b331d37a2a16159b65b255f4f9eb39314. 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-2021-37637 | 1 Google | 1 Tensorflow | 2024-11-21 | 7.7 High |
| TensorFlow is an end-to-end open source platform for machine learning. It is possible to trigger a null pointer dereference in TensorFlow by passing an invalid input to `tf.raw_ops.CompressElement`. The [implementation](https://github.com/tensorflow/tensorflow/blob/47a06f40411a69c99f381495f490536972152ac0/tensorflow/core/data/compression_utils.cc#L34) was accessing the size of a buffer obtained from the return of a separate function call before validating that said buffer is valid. We have patched the issue in GitHub commit 5dc7f6981fdaf74c8c5be41f393df705841fb7c5. 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-2021-37635 | 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 the implementation of sparse reduction operations in TensorFlow can trigger accesses outside of bounds of heap allocated data. The [implementation](https://github.com/tensorflow/tensorflow/blob/a1bc56203f21a5a4995311825ffaba7a670d7747/tensorflow/core/kernels/sparse_reduce_op.cc#L217-L228) fails to validate that each reduction group does not overflow and that each corresponding index does not point to outside the bounds of the input tensor. We have patched the issue in GitHub commit 87158f43f05f2720a374f3e6d22a7aaa3a33f750. 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-2021-37634 | 1 Vapor | 1 Leafkit | 2024-11-21 | 7.4 High |
| Leafkit is a templating language with Swift-inspired syntax. Versions prior to 1.3.0 are susceptible to Cross-site Scripting (XSS) attacks. This affects anyone passing unsanitised data to Leaf's variable tags. Before this fix, Leaf would not escape any strings passed to tags as variables. If an attacker managed to find a variable that was rendered with their unsanitised data, they could inject scripts into a generated Leaf page, which could enable XSS attacks if other mitigations such as a Content Security Policy were not enabled. This has been patched in 1.3.0. As a workaround sanitize any untrusted input before passing it to Leaf and enable a CSP to block inline script and CSS data. | ||||
| CVE-2021-37633 | 1 Discourse | 1 Discourse | 2024-11-21 | 7.4 High |
| Discourse is an open source discussion platform. In versions prior to 2.7.8 rendering of d-popover tooltips can be susceptible to XSS attacks. This vulnerability only affects sites which have modified or disabled Discourse's default Content Security Policy. This issue is patched in the latest `stable` 2.7.8 version of Discourse. As a workaround users may ensure that the Content Security Policy is enabled, and has not been modified in a way which would make it more vulnerable to XSS attacks. | ||||
| CVE-2021-37632 | 1 Config Lib Project | 1 Config Lib | 2024-11-21 | 8.1 High |
| SuperMartijn642's Config Lib is a library used by a number of mods for the game Minecraft. The versions of SuperMartijn642's Config Lib between 1.0.4 and 1.0.8 are affected by a vulnerability and can be exploited on both servers and clients. Using SuperMartijn642's Config Lib, servers will send a packet to clients with the server's config values. In order to read `enum` values from the packet data, `ObjectInputStream#readObject` is used. `ObjectInputStream#readObject` will instantiate a class based on the input data. Since, the packet data is not validated before `ObjectInputStream#readObject` is called, an attacker can instantiate any class by sending a malicious packet. If a suitable class is found, the vulnerability can lead to a number of exploits, including remote code execution. Although the vulnerable packet is typically only send from server to client, it can theoretically also be send from client to server. This means both clients and servers running SuperMartijn642's Config Lib between 1.0.4 and 1.0.8 are vulnerable. The vulnerability has been patched in SuperMartijn642's Config lib 1.0.9. Both, players and server owners, should update to 1.0.9 or higher. | ||||
| CVE-2021-37628 | 1 Nextcloud | 1 Richdocuments | 2024-11-21 | 7.5 High |
| Nextcloud Richdocuments is an open source collaborative office suite. In affected versions the File Drop features ("Upload Only" public link shares in Nextcloud) can be bypassed using the Nextcloud Richdocuments app. An attacker was able to read arbitrary files in such a share. It is recommended that the Nextcloud Richdocuments is upgraded to 3.8.4 or 4.2.1. If upgrading is not possible then it is recommended to disable the Richdocuments application. | ||||
| CVE-2021-37627 | 1 Contao | 1 Contao | 2024-11-21 | 8 High |
| Contao is an open source CMS that allows creation of websites and scalable web applications. In affected versions it is possible to gain privileged rights in the Contao back end. Installations are only affected if they have untrusted back end users who have access to the form generator. All users are advised to update to Contao 4.4.56, 4.9.18 or 4.11.7. As a workaround users may disable the form generator or disable the login for untrusted back end users. | ||||
| CVE-2021-37626 | 1 Contao | 1 Contao | 2024-11-21 | 7.2 High |
| Contao is an open source CMS that allows you to create websites and scalable web applications. In affected versions it is possible to load PHP files by entering insert tags in the Contao back end. Installations are only affected if they have untrusted back end users who have the rights to modify fields that are shown in the front end. Update to Contao 4.4.56, 4.9.18 or 4.11.7 to resolve. If you cannot update then disable the login for untrusted back end users. | ||||
| CVE-2021-37625 | 1 Skytable | 1 Skytable | 2024-11-21 | 7.5 High |
| Skytable is an open source NoSQL database. In versions prior to 0.6.4 an incorrect check of return value of the accept function in the run-loop for a TCP socket/TLS socket/TCP+TLS multi-socket causes an early exit from the run loop that should continue infinitely unless terminated by a local user, effectively causing the whole database server to shut down. This has severe impact and can be used to easily cause DoS attacks without the need to use much bandwidth. The attack vectors include using an incomplete TLS connection for example by not providing the certificate for the connection and using a specially crafted TCP packet that triggers the application layer backoff algorithm. | ||||