| CVE |
Vendors |
Products |
Updated |
CVSS v3.1 |
| Shopware is an open source eCommerce platform. Versions prior to 6.4.3.1 contain a vulnerability involving an insecure direct object reference of log files of the Import/Export feature. 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. |
| PhpFastCache is a high-performance backend cache system (packagist package phpfastcache/phpfastcache). In versions before 6.1.5, 7.1.2, and 8.0.7 the `phpinfo()` can be exposed if the `/vendor` is not protected from public access. This is a rare situation today since the vendor directory is often located outside the web directory or protected via server rule (.htaccess, etc). Only the v6, v7 and v8 will be patched respectively in 8.0.7, 7.1.2, 6.1.5. Older versions such as v5, v4 are not longer supported and will **NOT** be patched. As a workaround, protect the `/vendor` directory from public access. |
| Next.js is an open source website development framework to be used with the React library. In affected versions specially encoded paths could be used when pages/_error.js was statically generated allowing an open redirect to occur to an external site. In general, this redirect does not directly harm users although can allow for phishing attacks by redirecting to an attacker's domain from a trusted domain. We recommend everyone to upgrade regardless of whether you can reproduce the issue or not. The issue has been patched in release 11.1.0. |
| Discourse is an open-source platform for community discussion. In Discourse before versions 2.7.8 and 2.8.0.beta4, when adding additional email addresses to an existing account on a Discourse site an email token is generated as part of the email verification process. Deleting the additional email address does not invalidate an unused token which can then be used in other contexts, including reseting a password. |
| 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. |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause denial of service in applications serving models using `tf.raw_ops.NonMaxSuppressionV5` by triggering a division by 0. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/image/non_max_suppression_op.cc#L170-L271) uses a user controlled argument to resize a `std::vector`. However, as `std::vector::resize` takes the size argument as a `size_t` and `output_size` is an `int`, there is an implicit conversion to unsigned. If the attacker supplies a negative value, this conversion results in a crash. A similar issue occurs in `CombinedNonMaxSuppression`. We have patched the issue in GitHub commit 3a7362750d5c372420aa8f0caf7bf5b5c3d0f52d and commit [b5cdbf12ffcaaffecf98f22a6be5a64bb96e4f58. 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. |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause a denial of service in `boosted_trees_create_quantile_stream_resource` by using negative arguments. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantile_ops.cc#L96) does not validate that `num_streams` only contains non-negative numbers. In turn, [this results in using this value to allocate memory](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantiles/quantile_stream_resource.h#L31-L40). However, `reserve` receives an unsigned integer so there is an implicit conversion from a negative value to a large positive unsigned. This results in a crash from the standard library. We have patched the issue in GitHub commit 8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992. 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. |
| 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. |
| 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. |
| 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. |
| Deck is an open source kanban style organization tool aimed at personal planning and project organization for teams integrated with Nextcloud. In affected versions the Deck application didn't properly check membership of users in a Circle. This allowed other users in the instance to gain access to boards that have been shared with a Circle, even if the user was not a member of the circle. It is recommended that Nextcloud Deck is upgraded to 1.5.1, 1.4.4 or 1.2.9. If you are unable to update it is advised to disable the Deck plugin. |
| Nextcloud Circles is an open source social network built for the nextcloud ecosystem. In affected versions the Nextcloud Circles application allowed any user to join any "Secret Circle" without approval by the Circle owner leaking private information. It is recommended that Nextcloud Circles is upgraded to 0.19.15, 0.20.11 or 0.21.4. There are no workarounds for this issue. |
| 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. |
| In version 6.5 Microchip MiWi software and all previous versions including legacy products, the stack is validating only two out of four Message Integrity Check (MIC) bytes. |
| In version 6.5 of Microchip MiWi software and all previous versions including legacy products, there is a possibility of frame counters being validated/updated prior to the message authentication. With this vulnerability in place, an attacker may increment the incoming frame counter values by injecting messages with a sufficiently large frame counter value and invalid payload. This results in denial of service/valid packets in the network. There is also a possibility of a replay attack in the stack. |
| In JetBrains YouTrack before 2021.2.16363, time-unsafe comparisons were used. |
| In JetBrains Hub before 2021.1.13402, HTML injection in the password reset email was possible. |
| A double-free vulnerability exists in fig2dev through 3.28a is affected by: via the free_stream function in readpics.c, which could cause a denial of service (context-dependent). |
| Altova MobileTogether Server before 7.3 SP1 allows XXE attacks, such as an InfoSetChanges/Changes attack against /workflowmanagement, or reading mobiletogetherserver.cfg and then reading the certificate and private key. |
| An open redirect vulnerability exists in Nagios XI before version 5.8.5 that could lead to spoofing. To exploit the vulnerability, an attacker could send a link that has a specially crafted URL and convince the user to click the link. |
