Parse Server crashes when receiving file download request with invalid byte range

Parse Server is an open source backend that can be deployed to any infrastructure that can run Node.js. Versions prior to 4.10.17, and prior to 5.2.8 on the 5.x branch, crash when a file download request is received with an invalid byte range, resulting in a Denial of Service. This issue has been patched in versions 4.10.17, and 5.2.8. There are no known workarounds.

Abort caused by allocating a vector that is too large in Tensorflow

Tensorflow is an Open Source Machine Learning Framework. During shape inference, TensorFlow can allocate a large vector based on a value from a tensor controlled by the user. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Missing validation causes denial of service in TensorFlow via `LSTMBlockCell`

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.LSTMBlockCell` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. The code does not validate the ranks of any of the arguments to this API call. This results in `CHECK`-failures when the elements of the tensor are accessed. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

Missing validation causes denial of service in TensorFlow via `Conv3DBackpropFilterV2`

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.Conv3DBackpropFilterV2` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. The code does not validate that the `filter_sizes` argument is a vector. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

Denial of service in TensorFlow due to lack of validation in `tf.ragged.constant`

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.ragged.constant` does not fully validate the input arguments. This results in a denial of service by consuming all available memory. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

Slice Memory Allocation with Excessive Size Value in binary

Binary provides encoding/decoding in Borsh and other formats. The vulnerability is a memory allocation vulnerability that can be exploited to allocate slices in memory with (arbitrary) excessive size value, which can either exhaust available memory or crash the whole program. When using `github.com/gagliardetto/binary` to parse unchecked (or wrong type of) data from untrusted sources of input (e.g. the blockchain) into slices, it's possible to allocate memory with excessive size. When `dec.Decode(&val)` method is used to parse data into a structure that is or contains slices of values, the length of the slice was previously read directly from the data itself without any checks on the size of it, and then a slice was allocated. This could lead to an overflow and an allocation of memory with excessive size value. Users should upgrade to `v0.7.1` or higher. A workaround is not to rely on the `dec.Decode(&val)` function to parse the data, but to use a custom `UnmarshalWithDecoder()` method that reads and checks the length of any slice.

linked_list_allocator vulnerable to out-of-bound writes on `Heap` initialization and `Heap::extend`

linked_list_allocator is an allocator usable for no_std systems. Prior to version 0.10.2, the heap initialization methods were missing a minimum size check for the given heap size argument. This could lead to out-of-bound writes when a heap was initialized with a size smaller than `3 * size_of::<usize>` because of metadata write operations. This vulnerability impacts all the initialization functions on the `Heap` and `LockedHeap` types, including `Heap::new`, `Heap::init`, `Heap::init_from_slice`, and `LockedHeap::new`. It also affects multiple uses of the `Heap::extend` method. Version 0.10.2 contains a patch for the issue. As a workaround, ensure that the heap is only initialized with a size larger than `3 * size_of::<usize>` and that the `Heap::extend` method is only called with sizes larger than `2 * size_of::<usize>()`. Also, ensure that the total heap size is (and stays) a multiple of `2 * size_of::<usize>()`.

xmldom allows multiple root nodes in a DOM

xmldom is a pure JavaScript W3C standard-based (XML DOM Level 2 Core) `DOMParser` and `XMLSerializer` module. xmldom parses XML that is not well-formed because it contains multiple top level elements, and adds all root nodes to the `childNodes` collection of the `Document`, without reporting any error or throwing. This breaks the assumption that there is only a single root node in the tree, which led to issuance of CVE-2022-39299 as it is a potential issue for dependents. Update to @xmldom/xmldom@~0.7.7, @xmldom/xmldom@~0.8.4 (dist-tag latest) or @xmldom/xmldom@>=0.9.0-beta.4 (dist-tag next). As a workaround, please one of the following approaches depending on your use case: instead of searching for elements in the whole DOM, only search in the `documentElement`or reject a document with a document that has more then 1 `childNode`.

A vulnerability has been identified in SICAM PAS/PQS (All versions < V7.0), SICAM PAS/PQS (All versions >= 7.0 < V8.06). Affected software does not properly validate the input for a certain parameter in the s7ontcp.dll. This could allow an unauthenticated remote attacker to send messages and create a denial of service condition as the application crashes. At the time of assigning the CVE, the affected firmware version of the component has already been superseded by succeeding mainline versions.

Memory Corruption in modem due to improper length check while copying into memory in Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Voice & Music

`tf.raw_ops.Mfcc` crashes in Tensorflow

TensorFlow is an open source platform for machine learning. If `ThreadUnsafeUnigramCandidateSampler` is given input `filterbank_channel_count` greater than the allowed max size, TensorFlow will crash. We have patched the issue in GitHub commit 39ec7eaf1428e90c37787e5b3fbd68ebd3c48860. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.

In findAllDeAccounts of AccountsDb.java, there is a possible denial of service due to resource exhaustion. This could lead to local denial of service with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-10 Android-11 Android-12 Android-12L Android-13Android ID: A-169762606

In NotificationChannel of NotificationChannel.java, there is a possible failure to persist permissions settings due to resource exhaustion. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-10 Android-11 Android-12 Android-12L Android-13Android ID: A-242703556

In NotificationChannel of NotificationChannel.java, there is a possible failure to persist permissions settings due to resource exhaustion. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-10 Android-11 Android-12 Android-12L Android-13Android ID: A-242703217

In multiple locations, there is a possible display crash loop due to improper input validation. This could lead to local denial of service with system execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-13Android ID: A-238178261

Affected devices don't process correctly certain special crafted packets sent to port 102/tcp, which could allow an attacker to cause a denial of service in the device.

Affected devices don't process correctly certain special crafted packets sent to port 102/tcp, which could allow an attacker to cause a denial of service in the device.

Affected devices don't process correctly certain special crafted packets sent to port 102/tcp, which could allow an attacker to cause a denial of service in the device.

2.2.2 MUTABLE ATTESTATION OR MEASUREMENT REPORTING DATA CWE-1283

The tested version of Dominion Voting Systems ImageCast X’s on-screen application hash display feature, audit log export, and application export functionality rely on self-attestation mechanisms. An attacker could leverage this vulnerability to disguise malicious applications on a device.

Improper Error Handling Issue in LabVIEW

An improper error handling vulnerability in LabVIEW may result in remote code execution. Successful exploitation requires an attacker to provide a user with a specially crafted VI. This vulnerability affects LabVIEW 2024 Q1 and prior versions.