Out-of-bounds Read

A CWE-125: Out-of-bounds Read vulnerability exists that could cause denial of service when an attacker repeatedly sends a specially crafted message. Affected Product: Interactive Graphical SCADA System Data Server (V15.0.0.22020 and prior)Show less

A CWE-125: Out-of-bounds Read vulnerability exists that could cause memory leaks potentially resulting in denial of service when an attacker repeatedly sends a specially crafted message. Affected Product: Interactive Graphical SCADA System Data Server (V15.0.0.22020 and prior)Show less

In camera driver, there is a possible out of bounds read due to an incorrect bounds check. This could lead to local information disclosure with System execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS05862973; Issue ID: ALPS05862973.Show less

In cmdq driver, there is a possible out of bounds read due to an incorrect bounds check. This could lead to local information disclosure with System execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS05747150; Issue ID: ALPS05747150.Show less

Out of bounds read under complex microarchitectural condition in memory subsystem for some Intel Atom(R) Processors may allow authenticated user to potentially enable information disclosure or cause denial of service via network access.Show less

A vulnerability has been identified in JT2Go (All versions < V13.2.0.7), Solid Edge SE2021 (All versions < SE2021MP9), Solid Edge SE2022 (All versions < SE2022MP1), Teamcenter Visualization V13.1 (All versions < V13.1.0.9), Teamcenter Visualization V13.2 (All versions < V13.2.0.7), Teamcenter Visualization V13.3 (All versions < V13.3.0.1). The plmxmlAdapterSE70.dll library is vulnerable to memory corruption condition while parsing specially crafted PAR files. An attacker could leverage this vulnerability to execute code in the context of the current process. (ZDI-CAN-15112)Show less

A security out-of-bounds read information disclosure vulnerability in Trend Micro Worry-Free Business Security Server could allow a local attacker to send garbage data to a specific named pipe and crash the server. Please note: an attacker must first obtain the ability to execute low-privileged code on the target system in order to exploit this vulnerability.Show less

Tensorflow is an Open Source Machine Learning Framework. The TFG dialect of TensorFlow (MLIR) makes several assumptions about the incoming `GraphDef` before converting it to the MLIR-based dialect. If an attacker changes the `SavedModel` format on disk to invalidate these assumptions and the `GraphDef` is then converted to MLIR-based IR then they can cause a crash in the Python interpreter. Under certain scenarios, heap OOB read/writes are possible. These issues have been discovered via fuzzing and it is possible that more weaknesses exist. We will patch them as they are discovered.Show less

Tensorflow is an Open Source Machine Learning Framework. TensorFlow's type inference can cause a heap out of bounds read as the bounds checking is done in a `DCHECK` (which is a no-op during production). An attacker can control the `input_idx` variable such that `ix` would be larger than the number of values in `node_t.args`. The fix will be included in TensorFlow 2.8.0. This is the only affected version.Show less

Tensorflow is an Open Source Machine Learning Framework. There is a typo in TensorFlow's `SpecializeType` which results in heap OOB read/write. Due to a typo, `arg` is initialized to the `i`th mutable argument in a loop where the loop index is `j`. Hence it is possible to assign to `arg` from outside the vector of arguments. Since this is a mutable proto value, it allows both read and write to outside of bounds data. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, and TensorFlow 2.6.3, as these are also affected and still in supported range.Show less

Tensorflow is an Open Source Machine Learning Framework. An attacker can craft a TFLite model that would allow limited reads and writes outside of arrays in TFLite. This exploits missing validation in the conversion from sparse tensors to dense tensors. The fix is 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. Users are advised to upgrade as soon as possible.Show less

Tensorflow is an Open Source Machine Learning Framework. The implementation of `FractionalAvgPoolGrad` does not consider cases where the input tensors are invalid allowing an attacker to read from outside of bounds of heap. 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.Show less

Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for `ReverseSequence` does not fully validate the value of `batch_dim` and can result in a heap OOB read. There is a check to make sure the value of `batch_dim` does not go over the rank of the input, but there is no check for negative values. Negative dimensions are allowed in some cases to mimic Python's negative indexing (i.e., indexing from the end of the array), however if the value is too negative then the implementation of `Dim` would access elements before the start of an array. 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.Show less