Total
12553 CVE
| CVE | Vendors | Products | Updated | CVSS v3.1 |
|---|---|---|---|---|
| CVE-2020-15228 | 1 Toolkit Project | 1 Toolkit | 2024-11-21 | 3.5 Low |
| In the `@actions/core` npm module before version 1.2.6,`addPath` and `exportVariable` functions communicate with the Actions Runner over stdout by generating a string in a specific format. Workflows that log untrusted data to stdout may invoke these commands, resulting in the path or environment variables being modified without the intention of the workflow or action author. The runner will release an update that disables the `set-env` and `add-path` workflow commands in the near future. For now, users should upgrade to `@actions/core v1.2.6` or later, and replace any instance of the `set-env` or `add-path` commands in their workflows with the new Environment File Syntax. Workflows and actions using the old commands or older versions of the toolkit will start to warn, then error out during workflow execution. | ||||
| CVE-2020-15210 | 2 Google, Opensuse | 2 Tensorflow, Leap | 2024-11-21 | 6.5 Medium |
| In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, if a TFLite saved model uses the same tensor as both input and output of an operator, then, depending on the operator, we can observe a segmentation fault or just memory corruption. We have patched the issue in d58c96946b and will release patch releases for all versions between 1.15 and 2.3. We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1. | ||||
| CVE-2020-15206 | 2 Google, Opensuse | 2 Tensorflow, Leap | 2024-11-21 | 9 Critical |
| In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, changing the TensorFlow's `SavedModel` protocol buffer and altering the name of required keys results in segfaults and data corruption while loading the model. This can cause a denial of service in products using `tensorflow-serving` or other inference-as-a-service installments. Fixed were added in commits f760f88b4267d981e13f4b302c437ae800445968 and fcfef195637c6e365577829c4d67681695956e7d (both going into TensorFlow 2.2.0 and 2.3.0 but not yet backported to earlier versions). However, this was not enough, as #41097 reports a different failure mode. The issue is patched in commit adf095206f25471e864a8e63a0f1caef53a0e3a6, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1. | ||||
| CVE-2020-15203 | 2 Google, Opensuse | 2 Tensorflow, Leap | 2024-11-21 | 7.5 High |
| In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, by controlling the `fill` argument of tf.strings.as_string, a malicious attacker is able to trigger a format string vulnerability due to the way the internal format use in a `printf` call is constructed. This may result in segmentation fault. The issue is patched in commit 33be22c65d86256e6826666662e40dbdfe70ee83, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1. | ||||
| CVE-2020-15201 | 1 Google | 1 Tensorflow | 2024-11-21 | 4.8 Medium |
| In Tensorflow before version 2.3.1, the `RaggedCountSparseOutput` implementation does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the values in the `splits` tensor generate a valid partitioning of the `values` tensor. Hence, the code is prone to heap buffer overflow. If `split_values` does not end with a value at least `num_values` then the `while` loop condition will trigger a read outside of the bounds of `split_values` once `batch_idx` grows too large. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1. | ||||
| CVE-2020-15200 | 1 Google | 1 Tensorflow | 2024-11-21 | 5.9 Medium |
| In Tensorflow before version 2.3.1, the `RaggedCountSparseOutput` implementation does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the values in the `splits` tensor generate a valid partitioning of the `values` tensor. Thus, the code sets up conditions to cause a heap buffer overflow. A `BatchedMap` is equivalent to a vector where each element is a hashmap. However, if the first element of `splits_values` is not 0, `batch_idx` will never be 1, hence there will be no hashmap at index 0 in `per_batch_counts`. Trying to access that in the user code results in a segmentation fault. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1. | ||||
| CVE-2020-15199 | 1 Google | 1 Tensorflow | 2024-11-21 | 5.9 Medium |
| In Tensorflow before version 2.3.1, the `RaggedCountSparseOutput` does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the `splits` tensor has the minimum required number of elements. Code uses this quantity to initialize a different data structure. Since `BatchedMap` is equivalent to a vector, it needs to have at least one element to not be `nullptr`. If user passes a `splits` tensor that is empty or has exactly one element, we get a `SIGABRT` signal raised by the operating system. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1. | ||||
| CVE-2020-15197 | 1 Google | 1 Tensorflow | 2024-11-21 | 6.3 Medium |
| In Tensorflow before version 2.3.1, the `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the `indices` tensor has rank 2. This tensor must be a matrix because code assumes its elements are accessed as elements of a matrix. However, malicious users can pass in tensors of different rank, resulting in a `CHECK` assertion failure and a crash. This can be used to cause denial of service in serving installations, if users are allowed to control the components of the input sparse tensor. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1. | ||||
| CVE-2020-15194 | 2 Google, Opensuse | 2 Tensorflow, Leap | 2024-11-21 | 5.3 Medium |
| In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `SparseFillEmptyRowsGrad` implementation has incomplete validation of the shapes of its arguments. Although `reverse_index_map_t` and `grad_values_t` are accessed in a similar pattern, only `reverse_index_map_t` is validated to be of proper shape. Hence, malicious users can pass a bad `grad_values_t` to trigger an assertion failure in `vec`, causing denial of service in serving installations. The issue is patched in commit 390611e0d45c5793c7066110af37c8514e6a6c54, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1." | ||||
| CVE-2020-15192 | 2 Google, Opensuse | 2 Tensorflow, Leap | 2024-11-21 | 4.3 Medium |
| In Tensorflow before versions 2.2.1 and 2.3.1, if a user passes a list of strings to `dlpack.to_dlpack` there is a memory leak following an expected validation failure. The issue occurs because the `status` argument during validation failures is not properly checked. Since each of the above methods can return an error status, the `status` value must be checked before continuing. The issue is patched in commit 22e07fb204386768e5bcbea563641ea11f96ceb8 and is released in TensorFlow versions 2.2.1, or 2.3.1. | ||||
| CVE-2020-15191 | 2 Google, Opensuse | 2 Tensorflow, Leap | 2024-11-21 | 5.3 Medium |
| In Tensorflow before versions 2.2.1 and 2.3.1, if a user passes an invalid argument to `dlpack.to_dlpack` the expected validations will cause variables to bind to `nullptr` while setting a `status` variable to the error condition. However, this `status` argument is not properly checked. Hence, code following these methods will bind references to null pointers. This is undefined behavior and reported as an error if compiling with `-fsanitize=null`. The issue is patched in commit 22e07fb204386768e5bcbea563641ea11f96ceb8 and is released in TensorFlow versions 2.2.1, or 2.3.1. | ||||
| CVE-2020-15190 | 2 Google, Opensuse | 2 Tensorflow, Leap | 2024-11-21 | 5.3 Medium |
| In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `tf.raw_ops.Switch` operation takes as input a tensor and a boolean and outputs two tensors. Depending on the boolean value, one of the tensors is exactly the input tensor whereas the other one should be an empty tensor. However, the eager runtime traverses all tensors in the output. Since only one of the tensors is defined, the other one is `nullptr`, hence we are binding a reference to `nullptr`. This is undefined behavior and reported as an error if compiling with `-fsanitize=null`. In this case, this results in a segmentation fault The issue is patched in commit da8558533d925694483d2c136a9220d6d49d843c, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1. | ||||
| CVE-2020-15186 | 2 Helm, Redhat | 2 Helm, Acm | 2024-11-21 | 3.4 Low |
| In Helm before versions 2.16.11 and 3.3.2 plugin names are not sanitized properly. As a result, a malicious plugin author could use characters in a plugin name that would result in unexpected behavior, such as duplicating the name of another plugin or spoofing the output to `helm --help`. This issue has been patched in Helm 3.3.2. A possible workaround is to not install untrusted Helm plugins. Examine the `name` field in the `plugin.yaml` file for a plugin, looking for characters outside of the [a-zA-Z0-9._-] range. | ||||
| CVE-2020-15184 | 2 Helm, Redhat | 2 Helm, Acm | 2024-11-21 | 3.7 Low |
| In Helm before versions 2.16.11 and 3.3.2 there is a bug in which the `alias` field on a `Chart.yaml` is not properly sanitized. This could lead to the injection of unwanted information into a chart. This issue has been patched in Helm 3.3.2 and 2.16.11. A possible workaround is to manually review the `dependencies` field of any untrusted chart, verifying that the `alias` field is either not used, or (if used) does not contain newlines or path characters. | ||||
| CVE-2020-15181 | 1 Alfresco | 1 Reset Password | 2024-11-21 | 9.3 Critical |
| The Alfresco Reset Password add-on before version 1.2.0 relies on untrusted inputs in a security decision. Intruders can get admin's access to the system using the vulnerability in the project. Impacts all servers where this add-on is installed. The problem is fixed in version 1.2.0 | ||||
| CVE-2020-15180 | 5 Debian, Galeracluster, Mariadb and 2 more | 9 Debian Linux, Galera Cluster For Mysql, Mariadb and 6 more | 2024-11-21 | 9.0 Critical |
| A flaw was found in the mysql-wsrep component of mariadb. Lack of input sanitization in `wsrep_sst_method` allows for command injection that can be exploited by a remote attacker to execute arbitrary commands on galera cluster nodes. This threatens the system's confidentiality, integrity, and availability. This flaw affects mariadb versions before 10.1.47, before 10.2.34, before 10.3.25, before 10.4.15 and before 10.5.6. | ||||
| CVE-2020-15174 | 1 Electronjs | 1 Electron | 2024-11-21 | 7.5 High |
| In Electron before versions 11.0.0-beta.1, 10.0.1, 9.3.0 or 8.5.1 the `will-navigate` event that apps use to prevent navigations to unexpected destinations as per our security recommendations can be bypassed when a sub-frame performs a top-frame navigation across sites. The issue is patched in versions 11.0.0-beta.1, 10.0.1, 9.3.0 or 8.5.1 As a workaround sandbox all your iframes using the sandbox attribute. This will prevent them creating top-frame navigations and is good practice anyway. | ||||
| CVE-2020-15170 | 1 Ctrip | 1 Apollo | 2024-11-21 | 7 High |
| apollo-adminservice before version 1.7.1 does not implement access controls. If users expose apollo-adminservice to internet(which is not recommended), there are potential security issues since apollo-adminservice is designed to work in intranet and it doesn't have access control built-in. Malicious hackers may access apollo-adminservice apis directly to access/edit the application's configurations. To fix the potential issue without upgrading, simply follow the advice that do not expose apollo-adminservice to internet. | ||||
| CVE-2020-15168 | 2 Node-fetch Project, Redhat | 2 Node-fetch, Acm | 2024-11-21 | 2.6 Low |
| node-fetch before versions 2.6.1 and 3.0.0-beta.9 did not honor the size option after following a redirect, which means that when a content size was over the limit, a FetchError would never get thrown and the process would end without failure. For most people, this fix will have a little or no impact. However, if you are relying on node-fetch to gate files above a size, the impact could be significant, for example: If you don't double-check the size of the data after fetch() has completed, your JS thread could get tied up doing work on a large file (DoS) and/or cost you money in computing. | ||||
| CVE-2020-15112 | 3 Etcd, Fedoraproject, Redhat | 5 Etcd, Fedora, Openshift and 2 more | 2024-11-21 | 6.5 Medium |
| In etcd before versions 3.3.23 and 3.4.10, it is possible to have an entry index greater then the number of entries in the ReadAll method in wal/wal.go. This could cause issues when WAL entries are being read during consensus as an arbitrary etcd consensus participant could go down from a runtime panic when reading the entry. | ||||