Total
210374 CVE
| CVE | Vendors | Products | Updated | CVSS v2 | CVSS v3 |
|---|---|---|---|---|---|
| CVE-2021-37646 | 1 Google | 1 Tensorflow | 2021-08-18 | 2.1 LOW | 5.5 MEDIUM |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.StringNGrams` is vulnerable to an integer overflow issue caused by converting a signed integer value to an unsigned one and then allocating memory based on this value. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/string_ngrams_op.cc#L184) calls `reserve` on a `tstring` with a value that sometimes can be negative if user supplies negative `ngram_widths`. The `reserve` method calls `TF_TString_Reserve` which has an `unsigned long` argument for the size of the buffer. Hence, the implicit conversion transforms the negative value to a large integer. We have patched the issue in GitHub commit c283e542a3f422420cfdb332414543b62fc4e4a5. 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-2021-37644 | 1 Google | 1 Tensorflow | 2021-08-18 | 2.1 LOW | 5.5 MEDIUM |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions providing a negative element to `num_elements` list argument of `tf.raw_ops.TensorListReserve` causes the runtime to abort the process due to reallocating a `std::vector` to have a negative number of elements. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/list_kernels.cc#L312) calls `std::vector.resize()` with the new size controlled by input given by the user, without checking that this input is valid. We have patched the issue in GitHub commit 8a6e874437670045e6c7dc6154c7412b4a2135e2. 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-2021-37645 | 1 Google | 1 Tensorflow | 2021-08-18 | 2.1 LOW | 5.5 MEDIUM |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.QuantizeAndDequantizeV4Grad` is vulnerable to an integer overflow issue caused by converting a signed integer value to an unsigned one and then allocating memory based on this value. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L126) uses the `axis` value as the size argument to `absl::InlinedVector` constructor. But, the constructor uses an unsigned type for the argument, so the implicit conversion transforms the negative value to a large integer. We have patched the issue in GitHub commit 96f364a1ca3009f98980021c4b32be5fdcca33a1. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, and TensorFlow 2.4.3, as these are also affected and still in supported range. | |||||
| CVE-2021-37650 | 1 Google | 1 Tensorflow | 2021-08-18 | 4.6 MEDIUM | 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-2021-38511 | 1 Tar Project | 1 Tar | 2021-08-18 | 5.0 MEDIUM | 7.5 HIGH |
| An issue was discovered in the tar crate before 0.4.36 for Rust. When symlinks are present in a TAR archive, extraction can create arbitrary directories via .. traversal. | |||||
| CVE-2021-37651 | 1 Google | 1 Tensorflow | 2021-08-18 | 4.6 MEDIUM | 7.8 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-2021-33708 | 1 Kyma-project | 1 Kyma | 2021-08-18 | 6.5 MEDIUM | 8.8 HIGH |
| Due to insufficient input validation in Kyma, authenticated users can pass a Header of their choice and escalate privileges. | |||||
| CVE-2021-37654 | 1 Google | 1 Tensorflow | 2021-08-18 | 3.6 LOW | 7.1 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-2021-37655 | 1 Google | 1 Tensorflow | 2021-08-18 | 4.6 MEDIUM | 7.3 HIGH |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can trigger a read from outside of bounds of heap allocated data by sending invalid arguments to `tf.raw_ops.ResourceScatterUpdate`. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/resource_variable_ops.cc#L919-L923) has an incomplete validation of the relationship between the shapes of `indices` and `updates`: instead of checking that the shape of `indices` is a prefix of the shape of `updates` (so that broadcasting can happen), code only checks that the number of elements in these two tensors are in a divisibility relationship. We have patched the issue in GitHub commit 01cff3f986259d661103412a20745928c727326f. 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-2021-37659 | 1 Google | 1 Tensorflow | 2021-08-18 | 4.6 MEDIUM | 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 all binary cwise operations that don't require broadcasting (e.g., gradients of binary cwise operations). The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/cwise_ops_common.h#L264) assumes that the two inputs have exactly the same number of elements but does not check that. Hence, when the eigen functor executes it triggers heap OOB reads and undefined behavior due to binding to nullptr. We have patched the issue in GitHub commit 93f428fd1768df147171ed674fee1fc5ab8309ec. 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-2021-37656 | 1 Google | 1 Tensorflow | 2021-08-18 | 4.6 MEDIUM | 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.RaggedTensorToSparse`. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/ragged_tensor_to_sparse_kernel.cc#L30) has an incomplete validation of the splits values: it does not check that they are in increasing order. We have patched the issue in GitHub commit 1071f554dbd09f7e101324d366eec5f4fe5a3ece. 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-2021-37657 | 1 Google | 1 Tensorflow | 2021-08-18 | 4.6 MEDIUM | 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 all operations of type `tf.raw_ops.MatrixDiagV*`. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/linalg/matrix_diag_op.cc) has incomplete validation that the value of `k` is a valid tensor. We have check that this value is either a scalar or a vector, but there is no check for the number of elements. If this is an empty tensor, then code that accesses the first element of the tensor is wrong. We have patched the issue in GitHub commit f2a673bd34f0d64b8e40a551ac78989d16daad09. 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-2021-25659 | 1 Siemens | 1 Automation License Manager | 2021-08-18 | 5.0 MEDIUM | 7.5 HIGH |
| A vulnerability has been identified in Automation License Manager 5 (All versions), Automation License Manager 6 (All versions < V6.0 SP9 Update 2). Sending specially crafted packets to port 4410/tcp of an affected system could lead to extensive memory being consumed and as such could cause a denial-of-service preventing legitimate users from using the system. | |||||
| CVE-2021-33717 | 1 Siemens | 2 Jt2go, Teamcenter Visualization | 2021-08-18 | 4.3 MEDIUM | 5.5 MEDIUM |
| A vulnerability has been identified in JT2Go (All versions < V13.2.0.1), Teamcenter Visualization (All versions < V13.2.0.1). When parsing specially crafted CGM Files, a NULL pointer deference condition could cause the application to crash. The application must be restarted to restore the service. An attacker could leverage this vulnerability to cause a Denial-of-Service condition in the application. | |||||
| CVE-2021-28372 | 1 Throughtek | 1 Kalay P2p Software Development Kit | 2021-08-18 | 7.6 HIGH | 8.3 HIGH |
| ThroughTek's Kalay Platform 2.0 network allows an attacker to impersonate an arbitrary ThroughTek (TUTK) device given a valid 20-byte uniquely assigned identifier (UID). This could result in an attacker hijacking a victim's connection and forcing them into supplying credentials needed to access the victim TUTK device. | |||||
| CVE-2021-21601 | 1 Dell | 2 Emc Data Protection Search, Emc Integrated Data Protection Appliance | 2021-08-18 | 2.1 LOW | 7.8 HIGH |
| Dell EMC Data Protection Search, 19.4 and prior, and IDPA, 2.6.1 and prior, contain an Information Exposure in Log File Vulnerability in CIS. A local low privileged attacker could potentially exploit this vulnerability, leading to the disclosure of certain user credentials. The attacker may be able to use the exposed credentials to access the vulnerable application with the privileges of the compromised account. | |||||
| CVE-2021-21600 | 1 Dell | 1 Emc Networker | 2021-08-18 | 4.0 MEDIUM | 6.5 MEDIUM |
| Dell EMC NetWorker, 19.4 or older, contain an uncontrolled resource consumption flaw in its API service. An authorized API user could potentially exploit this vulnerability via the web and desktop user interfaces, leading to denial of service in the manageability path. | |||||
| CVE-2021-3587 | 2021-08-17 | N/A | N/A | ||
| ** REJECT ** DO NOT USE THIS CANDIDATE NUMBER. ConsultIDs: CVE-2021-38208. Reason: This candidate is a reservation duplicate of CVE-2021-38208. Notes: All CVE users should reference CVE-2021-38208 instead of this candidate. All references and descriptions in this candidate have been removed to prevent accidental usage. | |||||
| CVE-2021-24495 | 1 Marmoset | 1 Marmoset Viewer | 2021-08-17 | 4.3 MEDIUM | 6.1 MEDIUM |
| The Marmoset Viewer WordPress plugin before 1.9.3 does not property sanitize, validate or escape the 'id' parameter before outputting back in the page, leading to a reflected Cross-Site Scripting issue. | |||||
| CVE-2021-24501 | 1 Amentotech | 1 Workreap | 2021-08-17 | 5.5 MEDIUM | 8.1 HIGH |
| The Workreap WordPress theme before 2.2.2 had several AJAX actions missing authorization checks to verify that a user was authorized to perform critical operations such as modifying or deleting objects. This allowed a logged in user to modify or delete objects belonging to other users on the site. | |||||