yahoo-inc/cve-impacts huggingface dataset:
CVE-2021-37669: 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.
Key phrases: denial of service, crash
CVE-2021-3767: bookstack is vulnerable to Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')
Key phrases: improper neutralization of input during web page generation, cross-site scripting
CVE-2021-37670: 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 `tf.raw_ops.UpperBound`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/searchsorted_op.cc#L85-L104) does not validate the rank of `sorted_input` argument. A similar issue occurs in `tf.raw_ops.LowerBound`. We have patched the issue in GitHub commit 42459e4273c2e47a3232cc16c4f4fff3b3a35c38. 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.
Key phrases: illegal arguments
CVE-2021-37671: 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.
Key phrases: undefined behavior, null pointer
CVE-2021-37672: 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 `tf.raw_ops.SdcaOptimizerV2`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/sdca_internal.cc#L320-L353) does not check that the length of `example_labels` is the same as the number of examples. We have patched the issue in GitHub commit a4e138660270e7599793fa438cd7b2fc2ce215a6. 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-2021-37673: TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can trigger a denial of service via a `CHECK`-fail in `tf.raw_ops.MapStage`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/map_stage_op.cc#L513) does not check that the `key` input is a valid non-empty tensor. We have patched the issue in GitHub commit d7de67733925de196ec8863a33445b73f9562d1d. 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.
Key phrases: denial of service
CVE-2021-37674: TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can trigger a denial of service via a segmentation fault in `tf.raw_ops.MaxPoolGrad` caused by missing validation. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/maxpooling_op.cc) misses some validation for the `orig_input` and `orig_output` tensors. The fixes for CVE-2021-29579 were incomplete. We have patched the issue in GitHub commit 136b51f10903e044308cf77117c0ed9871350475. 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.
Key phrases: denial of service, segmentation fault
CVE-2021-37675: TensorFlow is an end-to-end open source platform for machine learning. In affected versions most implementations of convolution operators in TensorFlow are affected by a division by 0 vulnerability where an attacker can trigger a denial of service via a crash. The shape inference [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/framework/common_shape_fns.cc#L577) is missing several validations before doing divisions and modulo operations. We have patched the issue in GitHub commit 8a793b5d7f59e37ac7f3cd0954a750a2fe76bad4. 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.
Key phrases: division by 0, denial of service, crash
CVE-2021-37676: 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.
Key phrases: undefined behavior, null pointer
CVE-2021-37677: TensorFlow is an end-to-end open source platform for machine learning. In affected versions the shape inference code for `tf.raw_ops.Dequantize` has a vulnerability that could trigger a denial of service via a segfault if an attacker provides invalid arguments. The shape inference [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/ops/array_ops.cc#L2999-L3014) uses `axis` to select between two different values for `minmax_rank` which is then used to retrieve tensor dimensions. However, code assumes that `axis` can be either `-1` or a value greater than `-1`, with no validation for the other values. We have patched the issue in GitHub commit da857cfa0fde8f79ad0afdbc94e88b5d4bbec764. 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.
Key phrases: denial of service
CVE-2021-37678: TensorFlow is an end-to-end open source platform for machine learning. In affected versions TensorFlow and Keras can be tricked to perform arbitrary code execution when deserializing a Keras model from YAML format. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/python/keras/saving/model_config.py#L66-L104) uses `yaml.unsafe_load` which can perform arbitrary code execution on the input. Given that YAML format support requires a significant amount of work, we have removed it for now. We have patched the issue in GitHub commit 23d6383eb6c14084a8fc3bdf164043b974818012. 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.
Key phrases: perform arbitrary code execution
CVE-2021-37679: 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.
Key phrases: data loss, leak memory
CVE-2021-3768: bookstack is vulnerable to Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')
Key phrases: improper neutralization of input during web page generation, cross-site scripting
CVE-2021-37680: TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of fully connected layers in TFLite is [vulnerable to a division by zero error](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/fully_connected.cc#L226). We have patched the issue in GitHub commit 718721986aa137691ee23f03638867151f74935f. 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.
Key phrases: division by zero error
CVE-2021-37681: 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.
Key phrases: null pointer error, null pointer exception
CVE-2021-37682: TensorFlow is an end-to-end open source platform for machine learning. In affected versions all TFLite operations that use quantization can be made to use unitialized values. [For example](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/depthwise_conv.cc#L198-L200). The issue stems from the fact that `quantization.params` is only valid if `quantization.type` is different that `kTfLiteNoQuantization`. However, these checks are missing in large parts of the code. We have patched the issue in GitHub commits 537bc7c723439b9194a358f64d871dd326c18887, 4a91f2069f7145aab6ba2d8cfe41be8a110c18a5 and 8933b8a21280696ab119b63263babdb54c298538. 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-2021-37683: TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of division in TFLite is [vulnerable to a division by 0 error](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/div.cc). There is no check that the divisor tensor does not contain zero elements. We have patched the issue in GitHub commit 1e206baedf8bef0334cca3eb92bab134ef525a28. 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.
Key phrases: division by 0 error
CVE-2021-37684: TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementations of pooling in TFLite are vulnerable to division by 0 errors as there are no checks for divisors not being 0. We have patched the issue in GitHub commit [dfa22b348b70bb89d6d6ec0ff53973bacb4f4695](https://github.com/tensorflow/tensorflow/commit/dfa22b348b70bb89d6d6ec0ff53973bacb4f4695). 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.
Key phrases: division by 0 errors
CVE-2021-37685: TensorFlow is an end-to-end open source platform for machine learning. In affected versions TFLite's [`expand_dims.cc`](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/lite/kernels/expand_dims.cc#L36-L50) contains a vulnerability which allows reading one element outside of bounds of heap allocated data. If `axis` is a large negative value (e.g., `-100000`), then after the first `if` it would still be negative. The check following the `if` statement will pass and the `for` loop would read one element before the start of `input_dims.data` (when `i = 0`). We have patched the issue in GitHub commit d94ffe08a65400f898241c0374e9edc6fa8ed257. 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.
Key phrases: reading one element outside of bounds of heap
CVE-2021-37686: TensorFlow is an end-to-end open source platform for machine learning. In affected versions the strided slice implementation in TFLite has a logic bug which can allow an attacker to trigger an infinite loop. This arises from newly introduced support for [ellipsis in axis definition](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/lite/kernels/strided_slice.cc#L103-L122). An attacker can craft a model such that `ellipsis_end_idx` is smaller than `i` (e.g., always negative). In this case, the inner loop does not increase `i` and the `continue` statement causes execution to skip over the preincrement at the end of the outer loop. We have patched the issue in GitHub commit dfa22b348b70bb89d6d6ec0ff53973bacb4f4695. TensorFlow 2.6.0 is the only affected version.
Key phrases: trigger an infinite loop, logic bug
CVE-2021-37687: TensorFlow is an end-to-end open source platform for machine learning. In affected versions TFLite's [`GatherNd` implementation](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/lite/kernels/gather_nd.cc#L124) does not support negative indices but there are no checks for this situation. Hence, an attacker can read arbitrary data from the heap by carefully crafting a model with negative values in `indices`. Similar issue exists in [`Gather` implementation](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/lite/kernels/gather.cc). We have patched the issue in GitHub commits bb6a0383ed553c286f87ca88c207f6774d5c4a8f and eb921122119a6b6e470ee98b89e65d721663179d. 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.
Key phrases: read arbitrary data
CVE-2021-37688: 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.
Key phrases: null pointer dereference, denial of service, crash
CVE-2021-37689: 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.
Key phrases: null pointer dereference, denial of service, crash
CVE-2021-3769: # Vulnerability in `pygmalion`, `pygmalion-virtualenv` and `refined` themes **Description**: these themes use `print -P` on user-supplied strings to print them to the terminal. All of them do that on git information, particularly the branch name, so if the branch has a specially-crafted name the vulnerability can be exploited. **Fixed in**: [b3ba9978](https://github.com/ohmyzsh/ohmyzsh/commit/b3ba9978). **Impacted areas**: - `pygmalion` theme. - `pygmalion-virtualenv` theme. - `refined` theme.
Key phrases: impacted areas
CVE-2021-37690: TensorFlow is an end-to-end open source platform for machine learning. In affected versions when running shape functions, some functions (such as `MutableHashTableShape`) produce extra output information in the form of a `ShapeAndType` struct. The shapes embedded in this struct are owned by an inference context that is cleaned up almost immediately; if the upstream code attempts to access this shape information, it can trigger a segfault. `ShapeRefiner` is mitigating this for normal output shapes by cloning them (and thus putting the newly created shape under ownership of an inference context that will not die), but we were not doing the same for shapes and types. This commit fixes that by doing similar logic on output shapes and types. We have patched the issue in GitHub commit ee119d4a498979525046fba1c3dd3f13a039fbb1. 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-2021-37691: 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 division by zero error in LSH [implementation](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/lite/kernels/lsh_projection.cc#L118). We have patched the issue in GitHub commit 0575b640091680cfb70f4dd93e70658de43b94f9. The fix will be included in TensorFlow 2.6.0. We will also cherrypick thiscommit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
Key phrases: division by zero error
CVE-2021-37692: TensorFlow is an end-to-end open source platform for machine learning. In affected versions under certain conditions, Go code can trigger a segfault in string deallocation. For string tensors, `C.TF_TString_Dealloc` is called during garbage collection within a finalizer function. However, tensor structure isn't checked until encoding to avoid a performance penalty. The current method for dealloc assumes that encoding succeeded, but segfaults when a string tensor is garbage collected whose encoding failed (e.g., due to mismatched dimensions). To fix this, the call to set the finalizer function is deferred until `NewTensor` returns and, if encoding failed for a string tensor, deallocs are determined based on bytes written. We have patched the issue in GitHub commit 8721ba96e5760c229217b594f6d2ba332beedf22. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, which is the other affected version.
Key phrases: performance penalty
CVE-2021-37693: 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.
CVE-2021-37694: @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.
Key phrases: arbitrary code injection
CVE-2021-37695: 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.
Key phrases: fake objects
CVE-2021-37696: 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.
Key phrases: access sensitive information by crafting a specific MassDM
CVE-2021-37697: 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.
Key phrases: access sensitive information by crafting a specific membership
CVE-2021-37698: Icinga is a monitoring system which checks the availability of network resources, notifies users of outages, and generates performance data for reporting. In versions 2.5.0 through 2.13.0, ElasticsearchWriter, GelfWriter, InfluxdbWriter and Influxdb2Writer do not verify the server's certificate despite a certificate authority being specified. Icinga 2 instances which connect to any of the mentioned time series databases (TSDBs) using TLS over a spoofable infrastructure should immediately upgrade to version 2.13.1, 2.12.6, or 2.11.11 to patch the issue. Such instances should also change the credentials (if any) used by the TSDB writer feature to authenticate against the TSDB. There are no workarounds aside from upgrading.
Key phrases: spoofable infrastructure, availability
CVE-2021-37699: 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.
Key phrases: occur to an external site, an attacker's domain from a trusted domain, specially encoded paths, open redirect, harm users
CVE-2021-3770: vim is vulnerable to Heap-based Buffer Overflow
Key phrases: heap-based buffer overflow
CVE-2021-37700: @github/paste-markdown is an npm package for pasting markdown objects. A self Cross-Site Scripting vulnerability exists in the @github/paste-markdown before version 0.3.4. If the clipboard data contains the string `<table>`, a **div** is dynamically created, and the clipboard content is copied into its **innerHTML** property without any sanitization, resulting in improper execution of JavaScript in the browser of the victim (the user who pasted the code). Users directed to copy text from a malicious website and paste it into pages that utilize this library are affected. This is fixed in version 0.3.4. Refer the to the referenced GitHub Advisory for more details including an example exploit.
Key phrases: cross-site scripting
CVE-2021-37701: 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.
Key phrases: allowing arbitrary file creation, bypass node-tar symlink checks, symlink into an arbitrary location and subsequently extracting, a more recent version of node-tar, arbitrary file creation overwrite, arbitrary code execution, arbitrary file creation and overwrite
CVE-2021-37702: 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.
Key phrases: formular injection
CVE-2021-37703: Discourse is an open-source platform for community discussion. In Discourse before versions 2.7.8 and 2.8.0.beta5, a user's read state for a topic such as the last read post number and the notification level is exposed.
CVE-2021-37704: 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.
Key phrases: `phpinfo()`
CVE-2021-37705: OneFuzz is an open source self-hosted Fuzzing-As-A-Service platform. Starting with OneFuzz 2.12.0 or greater, an incomplete authorization check allows an authenticated user from any Azure Active Directory tenant to make authorized API calls to a vulnerable OneFuzz instance. To be vulnerable, a OneFuzz deployment must be both version 2.12.0 or greater and deployed with the non-default --multi_tenant_domain option. This can result in read/write access to private data such as software vulnerability and crash information, security testing tools and proprietary code and symbols. Via authorized API calls, this also enables tampering with existing data and unauthorized code execution on Azure compute resources. This issue is resolved starting in release 2.31.0, via the addition of application-level check of the bearer token's `issuer` against an administrator-configured allowlist. As a workaround users can restrict access to the tenant of a deployed OneFuzz instance < 2.31.0 by redeploying in the default configuration, which omits the `--multi_tenant_domain` option.
Key phrases: make authorized API calls to a vulnerable OneFuzz, software, crash, code execution
CVE-2021-37706: PJSIP is a free and open source multimedia communication library written in C language implementing standard based protocols such as SIP, SDP, RTP, STUN, TURN, and ICE. In affected versions if the incoming STUN message contains an ERROR-CODE attribute, the header length is not checked before performing a subtraction operation, potentially resulting in an integer underflow scenario. This issue affects all users that use STUN. A malicious actor located within the victim’s network may forge and send a specially crafted UDP (STUN) message that could remotely execute arbitrary code on the victim’s machine. Users are advised to upgrade as soon as possible. There are no known workarounds.
Key phrases: execute arbitrary code, integer underflow scenario
CVE-2021-37707: Shopware is an open source eCommerce platform. Versions prior to 6.4.3.1 contain a vulnerability that allows manipulation of product reviews via API. 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.
Key phrases: manipulation of product reviews via API
CVE-2021-37708: 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.
Key phrases: command injection
CVE-2021-37709: 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.
Key phrases: insecure direct object reference
CVE-2021-37710: 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.
Key phrases: cross-site scripting
CVE-2021-37711: 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.
Key phrases: authenticated server-side request forgery, server side request forgery, file upload
CVE-2021-37712: The npm package "tar" (aka node-tar) before versions 4.4.18, 5.0.10, and 6.1.9 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 names containing unicode values that normalized to the same value. Additionally, on Windows systems, long path portions would resolve to the same file system entities as their 8.3 "short path" counterparts. A specially crafted tar archive could thus include a directory with one form of the path, followed by a symbolic link with a different string that resolves to the same file system entity, followed by a file using the first form. By first creating a directory, and then replacing that directory with a symlink that had a different apparent name that resolved to the same entry in the filesystem, 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. These issues were addressed in releases 4.4.18, 5.0.10 and 6.1.9. 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-qq89-hq3f-393p.
Key phrases: allowing arbitrary file creation, bypass node-tar symlink checks, symlink into an arbitrary location and subsequently extracting, a more recent version of node-tar, arbitrary file creation overwrite, arbitrary code execution, arbitrary file creation and overwrite
CVE-2021-37713: The npm package "tar" (aka node-tar) before versions 4.4.18, 5.0.10, and 6.1.9 has an arbitrary file creation/overwrite and arbitrary code execution vulnerability. node-tar aims to guarantee that any file whose location would be outside of the extraction target directory is not extracted. This is, in part, accomplished by sanitizing absolute paths of entries within the archive, skipping archive entries that contain `..` path portions, and resolving the sanitized paths against the extraction target directory. This logic was insufficient on Windows systems when extracting tar files that contained a path that was not an absolute path, but specified a drive letter different from the extraction target, such as `C:some\\\\path`. If the drive letter does not match the extraction target, for example `D:\\\\extraction\\\\dir`, then the result of `path.resolve(extractionDirectory, entryPath)` would resolve against the current working directory on the `C:` drive, rather than the extraction target directory. Additionally, a `..` portion of the path could occur immediately after the drive letter, such as `C:../foo`, and was not properly sanitized by the logic that checked for `..` within the normalized and split portions of the path. This only affects users of `node-tar` on Windows systems. These issues were addressed in releases 4.4.18, 5.0.10 and 6.1.9. 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. There is no reasonable way to work around this issue without performing the same path normalization procedures that node-tar now does. Users are encouraged to upgrade to the latest patched versions of node-tar, rather than attempt to sanitize paths themselves.
Key phrases: arbitrary file creation overwrite, arbitrary code execution
CVE-2021-37714: jsoup is a Java library for working with HTML. Those using jsoup versions prior to 1.14.2 to parse untrusted HTML or XML may be vulnerable to DOS attacks. If the parser is run on user supplied input, an attacker may supply content that causes the parser to get stuck (loop indefinitely until cancelled), to complete more slowly than usual, or to throw an unexpected exception. This effect may support a denial of service attack. The issue is patched in version 1.14.2. There are a few available workarounds. Users may rate limit input parsing, limit the size of inputs based on system resources, and/or implement thread watchdogs to cap and timeout parse runtimes.
Key phrases: dos, denial of service
CVE-2021-37715: A remote cross-site scripting (XSS) vulnerability was discovered in Aruba AirWave Management Platform version(s): Prior to 8.2.13.0. Aruba has released upgrades for the Aruba AirWave Management Platform that address this security vulnerability.
Key phrases: remote cross-site scripting (xss)
CVE-2021-37716: A remote buffer overflow vulnerability was discovered in Aruba SD-WAN Software and Gateways; Aruba Operating System Software version(s): Prior to 8.6.0.4-2.2.0.4; Prior to 8.7.1.2, 8.6.0.8, 8.5.0.12, 8.3.0.15. Aruba has released patches for Aruba SD-WAN Software and Gateways and ArubaOS that address this security vulnerability.
Key phrases: remote buffer overflow
CVE-2021-37717: A remote arbitrary command execution vulnerability was discovered in Aruba SD-WAN Software and Gateways; Aruba Operating System Software version(s): Prior to 8.6.0.4-2.2.0.6; Prior to 8.7.1.4, 8.6.0.7, 8.5.0.12, 8.3.0.16. Aruba has released patches for Aruba SD-WAN Software and Gateways and ArubaOS that address this security vulnerability.
Key phrases: remote arbitrary command execution, arbitrary commands
CVE-2021-37718: A remote arbitrary command execution vulnerability was discovered in Aruba SD-WAN Software and Gateways; Aruba Operating System Software version(s): Prior to 8.6.0.4-2.2.0.6; Prior to 8.7.1.4, 8.6.0.7, 8.5.0.12, 8.3.0.16. Aruba has released patches for Aruba SD-WAN Software and Gateways and ArubaOS that address this security vulnerability.
Key phrases: remote arbitrary command execution, arbitrary commands
CVE-2021-37719: A remote arbitrary command execution vulnerability was discovered in Aruba SD-WAN Software and Gateways; Aruba Operating System Software version(s): Prior to 8.6.0.4-2.2.0.4; Prior to 8.7.1.4, 8.6.0.9, 8.5.0.13, 8.3.0.16, 6.5.4.20, 6.4.4.25. Aruba has released patches for Aruba SD-WAN Software and Gateways and ArubaOS that address this security vulnerability.
Key phrases: remote arbitrary command execution, arbitrary commands
CVE-2021-3772: A flaw was found in the Linux SCTP stack. A blind attacker may be able to kill an existing SCTP association through invalid chunks if the attacker knows the IP-addresses and port numbers being used and the attacker can send packets with spoofed IP addresses.
Key phrases: invalid chunks
CVE-2021-37720: A remote arbitrary command execution vulnerability was discovered in Aruba SD-WAN Software and Gateways; Aruba Operating System Software version(s): Prior to 8.6.0.4-2.2.0.4; Prior to 8.7.1.4, 8.6.0.9, 8.5.0.13, 8.3.0.16, 6.5.4.20, 6.4.4.25. Aruba has released patches for Aruba SD-WAN Software and Gateways and ArubaOS that address this security vulnerability.
Key phrases: remote arbitrary command execution, arbitrary commands
CVE-2021-37721: A remote arbitrary command execution vulnerability was discovered in Aruba SD-WAN Software and Gateways; Aruba Operating System Software version(s): Prior to 8.6.0.4-2.2.0.4; Prior to 8.7.1.4, 8.6.0.9, 8.5.0.13, 8.3.0.16, 6.5.4.20, 6.4.4.25. Aruba has released patches for Aruba SD-WAN Software and Gateways and ArubaOS that address this security vulnerability.
Key phrases: remote arbitrary command execution, arbitrary commands
CVE-2021-37722: A remote arbitrary command execution vulnerability was discovered in Aruba SD-WAN Software and Gateways; Aruba Operating System Software version(s): Prior to 8.6.0.4-2.2.0.4; Prior to 8.7.1.4, 8.6.0.9, 8.5.0.13, 8.3.0.16, 6.5.4.20, 6.4.4.25. Aruba has released patches for Aruba SD-WAN Software and Gateways and ArubaOS that address this security vulnerability.
Key phrases: remote arbitrary command execution, arbitrary commands
CVE-2021-37723: A remote arbitrary command execution vulnerability was discovered in Aruba Operating System Software version(s): Prior to 8.7.1.2, 8.6.0.8, 8.5.0.12, 8.3.0.16. Aruba has released patches for ArubaOS that address this security vulnerability.
Key phrases: remote arbitrary command execution, arbitrary commands
CVE-2021-37724: A remote arbitrary command execution vulnerability was discovered in Aruba Operating System Software version(s): Prior to 8.7.1.2, 8.6.0.8, 8.5.0.12, 8.3.0.16. Aruba has released patches for ArubaOS that address this security vulnerability.
Key phrases: remote arbitrary command execution, arbitrary commands
CVE-2021-37725: A remote cross-site request forgery (csrf) vulnerability was discovered in Aruba SD-WAN Software and Gateways; Aruba Operating System Software version(s): Prior to 8.6.0.4-2.2.0.4; Prior to 8.8.0.1, 8.7.1.2, 8.6.0.8, 8.5.0.12, 8.3.0.15. Aruba has released patches for Aruba SD-WAN Software and Gateways and ArubaOS that address this security vulnerability.
Key phrases: cross-site request forgery (csrf), cross site request forgery
CVE-2021-37726: A remote buffer overflow vulnerability was discovered in HPE Aruba Instant (IAP) version(s): Aruba Instant 8.7.x.x: 8.7.0.0 through 8.7.1.2. Aruba has released patches for Aruba Instant (IAP) that address this security vulnerability.
Key phrases: remote buffer overflow
CVE-2021-37727: A remote arbitrary command execution vulnerability was discovered in HPE Aruba Instant (IAP) version(s): 6.4.x.x: 6.4.4.8-4.2.4.18 and below; Aruba Instant 6.5.x.x: 6.5.4.20 and below; Aruba Instant 8.5.x.x: 8.5.0.12 and below; Aruba Instant 8.6.x.x: 8.6.0.11 and below; Aruba Instant 8.7.x.x: 8.7.1.3 and below. Aruba has released patches for Aruba Instant (IAP) that address this security vulnerability.
Key phrases: remote arbitrary command execution, arbitrary commands
CVE-2021-37728: A remote path traversal vulnerability was discovered in Aruba Operating System Software version(s): Prior to 8.8.0.1, 8.7.1.4, 8.6.0.11, 8.5.0.13. Aruba has released patches for ArubaOS that address this security vulnerability.
Key phrases: remote path traversal
CVE-2021-37729: A remote path traversal vulnerability was discovered in Aruba SD-WAN Software and Gateways; Aruba Operating System Software version(s): Prior to 8.6.0.0-2.2.0.4; Prior to 8.7.1.3, 8.6.0.9, 8.5.0.12, 8.3.0.16, 6.5.4.19, 6.4.4.25. Aruba has released patches for Aruba SD-WAN Software and Gateways and ArubaOS that address this security vulnerability.
Key phrases: remote path traversal
CVE-2021-3773: A flaw in netfilter could allow a network-connected attacker to infer openvpn connection endpoint information for further use in traditional network attacks.
Key phrases: infer openvpn connection endpoint information for further use, flaw in netfilter, traditional network
CVE-2021-37730: A remote arbitrary command execution vulnerability was discovered in HPE Aruba Instant (IAP) version(s): Aruba Instant 6.4.x.x: 6.4.4.8-4.2.4.18 and below; Aruba Instant 6.5.x.x: 6.5.4.20 and below; Aruba Instant 8.5.x.x: 8.5.0.12 and below; Aruba Instant 8.6.x.x: 8.6.0.11 and below; Aruba Instant 8.7.x.x: 8.7.1.3 and below. Aruba has released patches for Aruba Instant (IAP) that address this security vulnerability.
Key phrases: remote arbitrary command execution, arbitrary commands
CVE-2021-37731: A local path traversal vulnerability was discovered in Aruba SD-WAN Software and Gateways; Aruba Operating System Software version(s): Prior to 8.6.0.0-2.2.0.4; Prior to 8.7.1.1, 8.6.0.7, 8.5.0.12, 8.3.0.16. Aruba has released patches for Aruba SD-WAN Software and Gateways and ArubaOS that address this security vulnerability.
Key phrases: local path traversal
CVE-2021-37732: A remote arbitrary command execution vulnerability was discovered in HPE Aruba Instant (IAP) version(s): Aruba Instant 6.4.x.x: 6.4.4.8-4.2.4.17 and below; Aruba Instant 6.5.x.x: 6.5.4.18 and below; Aruba Instant 8.5.x.x: 8.5.0.11 and below; Aruba Instant 8.6.x.x: 8.6.0.6 and below; Aruba Instant 8.7.x.x: 8.7.1.0 and below. Aruba has released patches for Aruba Instant (IAP) that address this security vulnerability.
Key phrases: remote arbitrary command execution, arbitrary commands
CVE-2021-37733: A remote path traversal vulnerability was discovered in Aruba SD-WAN Software and Gateways; Aruba Operating System Software version(s): Prior to 8.6.0.4-2.2.0.4; Prior to 8.7.1.1, 8.6.0.7, 8.5.0.11, 8.3.0.16. Aruba has released patches for Aruba SD-WAN Software and Gateways and ArubaOS that address this security vulnerability.
Key phrases: remote path traversal
CVE-2021-37734: A remote unauthorized read access to files vulnerability was discovered in Aruba Instant version(s): 6.4.x.x: 6.4.4.8-4.2.4.18 and below; Aruba Instant 6.5.x.x: 6.5.4.19 and below; Aruba Instant 8.5.x.x: 8.5.0.12 and below; Aruba Instant 8.6.x.x: 8.6.0.11 and below; Aruba Instant 8.7.x.x: 8.7.1.3 and below; Aruba Instant 8.8.x.x: 8.8.0.0 and below. Aruba has released patches for Aruba Instant (IAP) that address this security vulnerability.
Key phrases: remote unauthorized read access to files
CVE-2021-37735: A remote denial of service vulnerability was discovered in Aruba Instant version(s): Aruba Instant 6.5.x.x: 6.5.4.18 and below; Aruba Instant 8.5.x.x: 8.5.0.10 and below; Aruba Instant 8.6.x.x: 8.6.0.4 and below. Aruba has released patches for Aruba Instant (IAP) that address this security vulnerability.
Key phrases: remote denial of service
CVE-2021-37736: A remote authentication bypass vulnerability was discovered in Aruba ClearPass Policy Manager version(s): ClearPass Policy Manager 6.10.x prior to 6.10.2 - - ClearPass Policy Manager 6.9.x prior to 6.9.7-HF1 - - ClearPass Policy Manager 6.8.x prior to 6.8.9-HF1. Aruba has released patches for ClearPass Policy Manager that address this security vulnerability.
Key phrases: authentication bypass, remote authentication bypass