In wlan driver, there is a possible missing bounds check, This could lead to local denial of service in wlan services.

An integer overflow in the VNC module in VideoLAN VLC Media Player through 3.0.17.4 allows attackers, by tricking a user into opening a crafted playlist or connecting to a rogue VNC server, to crash VLC or execute code under some conditions.

In wlan driver, there is a possible missing bounds check, This could lead to local denial of service in wlan services.

Message length overflow in frontier

Frontier is Substrate's Ethereum compatibility layer. A security issue was discovered affecting parsing of the RPC result of the exit reason in case of EVM reversion. In release build, this would cause the exit reason being incorrectly parsed and returned by RPC. In debug build, this would cause an overflow panic. No action is needed unless you have a bridge node that needs to distinguish different reversion exit reasons and you used RPC for this. There are currently no known workarounds.

Int overflow in `RaggedRangeOp` in Tensoflow

TensorFlow is an open source platform for machine learning. The `RaggedRangOp` function takes an argument `limits` that is eventually used to construct a `TensorShape` as an `int64`. If `limits` is a very large float, it can overflow when converted to an `int64`. This triggers an `InvalidArgument` but also throws an abort signal that crashes the program. We have patched the issue in GitHub commit 37cefa91bee4eace55715eeef43720b958a01192. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

Integer overflow in math ops in TensorFlow

TensorFlow is an open source platform for machine learning. When `RangeSize` receives values that do not fit into an `int64_t`, it crashes. We have patched the issue in GitHub commit 37e64539cd29fcfb814c4451152a60f5d107b0f0. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

Integer Overflow in xrdp

xrdp is an open source project which provides a graphical login to remote machines using Microsoft Remote Desktop Protocol (RDP). xrdp < v0.9.21 contain a Integer Overflow in xrdp_mm_process_rail_update_window_text() function. There are no known workarounds for this issue. Users are advised to upgrade.

Integer overflow vulnerability in Samsung decoding library for video thumbnails prior to SMR Dec-2022 Release 1 allows local attacker to perform Out-Of-Bounds Write.

In battery, there is a possible escalation of privilege due to an integer overflow. This could lead to local escalation of privilege with System execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS08485622; Issue ID: ALPS08485622.

In battery, there is a possible out of bounds read due to an integer overflow. This could lead to local information disclosure with System execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS08587865; Issue ID: ALPS08486807.

In da, there is a possible out of bounds write due to an integer overflow. This could lead to local escalation of privilege with System execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS08541686; Issue ID: ALPS08541686.

Integer overflow in Tensorflow

Tensorflow is an Open Source Machine Learning Framework. Under certain scenarios, Grappler component of TensorFlow is vulnerable to an integer overflow during cost estimation for crop and resize. Since the cropping parameters are user controlled, a malicious person can trigger undefined behavior. 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.

Integer overflow in Tensorflow

Tensorflow is an Open Source Machine Learning Framework. The implementation of `OpLevelCostEstimator::CalculateOutputSize` is vulnerable to an integer overflow if an attacker can create an operation which would involve tensors with large enough number of elements. We can have a large enough number of dimensions in `output_shape.dim()` or just a small number of dimensions being large enough to cause an overflow in the multiplication. 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.

Integer overflow in TFLite

Tensorflow is an Open Source Machine Learning Framework. An attacker can craft a TFLite model that would cause an integer overflow in embedding lookup operations. Both `embedding_size` and `lookup_size` are products of values provided by the user. Hence, a malicious user could trigger overflows in the multiplication. In certain scenarios, this can then result in heap OOB read/write. Users are advised to upgrade to a patched version.

Integer overflow in TFLite array creation

Tensorflow is an Open Source Machine Learning Framework. An attacker can craft a TFLite model that would cause an integer overflow in `TfLiteIntArrayCreate`. The `TfLiteIntArrayGetSizeInBytes` returns an `int` instead of a `size_t. An attacker can control model inputs such that `computed_size` overflows the size of `int` datatype. 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.

Integer overflow in table parsing extension leads to heap memory corruption

cmark-gfm is GitHub's extended version of the C reference implementation of CommonMark. Prior to versions 0.29.0.gfm.3 and 0.28.3.gfm.21, an integer overflow in cmark-gfm's table row parsing `table.c:row_from_string` may lead to heap memory corruption when parsing tables who's marker rows contain more than UINT16_MAX columns. The impact of this heap corruption ranges from Information Leak to Arbitrary Code Execution depending on how and where `cmark-gfm` is used. If `cmark-gfm` is used for rendering remote user controlled markdown, this vulnerability may lead to Remote Code Execution (RCE) in applications employing affected versions of the `cmark-gfm` library. This vulnerability has been patched in the following cmark-gfm versions 0.29.0.gfm.3 and 0.28.3.gfm.21. A workaround is available. The vulnerability exists in the table markdown extensions of cmark-gfm. Disabling the table extension will prevent this vulnerability from being triggered.

Buffer Overflow and Integer Overflow in yajl-ruby

yajl-ruby is a C binding to the YAJL JSON parsing and generation library. The 1.x branch and the 2.x branch of `yajl` contain an integer overflow which leads to subsequent heap memory corruption when dealing with large (~2GB) inputs. The reallocation logic at `yajl_buf.c#L64` may result in the `need` 32bit integer wrapping to 0 when `need` approaches a value of 0x80000000 (i.e. ~2GB of data), which results in a reallocation of buf->alloc into a small heap chunk. These integers are declared as `size_t` in the 2.x branch of `yajl`, which practically prevents the issue from triggering on 64bit platforms, however this does not preclude this issue triggering on 32bit builds on which `size_t` is a 32bit integer. Subsequent population of this under-allocated heap chunk is based on the original buffer size, leading to heap memory corruption. This vulnerability mostly impacts process availability. Maintainers believe exploitation for arbitrary code execution is unlikely. A patch is available and anticipated to be part of yajl-ruby version 1.4.2. As a workaround, avoid passing large inputs to YAJL.

Integer overflow in `SpaceToBatchND` in TensorFlow

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.SpaceToBatchND` (in all backends such as XLA and handwritten kernels) is vulnerable to an integer overflow: The result of this integer overflow is used to allocate the output tensor, hence we get a denial of service via a `CHECK`-failure (assertion failure), as in TFSA-2021-198. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

Memory corruption in WLAN due to integer overflow to buffer overflow while parsing GTK frames. in Snapdragon Auto, Snapdragon Compute, Snapdragon Connectivity, Snapdragon Consumer Electronics Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon IoT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wearables, Snapdragon Wired Infrastructure and Networking

In da, there is a possible out of bounds read due to an integer overflow. This could lead to local information disclosure, if an attacker has physical access to the device, with no additional execution privileges needed. User interaction is needed for exploitation. Patch ID: ALPS09291064; Issue ID: MSV-2046.