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A use-after-free flaw was found in the Linux kernel’s Bluetooth subsystem in the way user calls connect to the socket and disconnect simultaneously due to a race condition. This flaw allows a user to crash the system or escalate their privileges. The highest threat from this vulnerability is to confidentiality, integrity, as well as system availability.

In Apache Teaclave Rust SGX SDK 1.1.3, a side-channel vulnerability in base64 PEM file decoding allows system-level (administrator) attackers to obtain information about secret RSA keys via a controlled-channel and side-channel attack on software running in isolated environments that can be single stepped, especially Intel SGX.

### Impact The [`UnbatchGradOp`](https://github.com/tensorflow/tensorflow/blob/769eddaf479c8debead9a59a72617d6ed6f0fe10/tensorflow/core/kernels/batch_kernels.cc#L891) function takes an argument `id` that is assumed to be a scalar. A nonscalar `id` can trigger a `CHECK` failure and crash the program. ```python import numpy as np import tensorflow as tf # `id` is not scalar tf.raw_ops.UnbatchGrad(original_input= tf.constant([1]),batch_index=tf.constant([[0,0,0 ], ], dtype=tf.int64),grad=tf.constant([1,]),id=tf.constant([1,1,], dtype=tf.int64)) ``` It also requires its argument `batch_index` to contain three times the number of elements as indicated in its `batch_index.dim_size(0)`. An incorrect `batch_index` can trigger a `CHECK` failure and crash the program. ```python import numpy as np import tensorflow as tf # batch_index's size is not 3 tf.raw_ops.UnbatchGrad(original_input= tf.constant([1]),batch_index=tf.constant([[0,0], ], dtype=tf.int64),grad=tf.constant([1,]),id=tf.constant([...

Certain versions of HP PC Hardware Diagnostics Windows are potentially vulnerable to buffer overflow.

An issue was discovered in the Linux kernel through 6.0.9. drivers/media/dvb-core/dvb_net.c has a .disconnect versus dvb_device_open race condition that leads to a use-after-free.

# Microsoft Security Advisory CVE-2024-30045 | .NET Remote code Execution Vulnerability ## <a name="executive-summary"></a>Executive summary Microsoft is releasing this security advisory to provide information about a vulnerability in .NET. This advisory also provides guidance on what developers can do to update their applications to remove this vulnerability. A Remote Code Execution vulnerability exists in .NET 7.0 and .NET 8.0 where a stack buffer overrun occurs in .NET Double Parse routine. ## Discussion Discussion for this issue can be found at https://github.com/dotnet/runtime/issues/102206 ## <a name="mitigation-factors"></a>Mitigation factors Microsoft has not identified any mitigating factors for this vulnerability. ## <a name="affected-software"></a>Affected software * Any .NET 7.0 application running on .NET 7.0.18 or earlier. * Any .NET 8.0 application running on .NET 8.0.4 or earlier. ## <a name="affected-packages"></a>Affected Packages The vulnerability affects...

### Impact When `tf.linalg.matrix_rank` receives an empty input `a`, the GPU kernel gives a `CHECK` fail that can be used to trigger a denial of service attack. ```python import tensorflow as tf a = tf.constant([], shape=[0, 1, 1], dtype=tf.float32) tf.linalg.matrix_rank(a=a) ``` ### Patches We have patched the issue in GitHub commit [c55b476aa0e0bd4ee99d0f3ad18d9d706cd1260a](https://github.com/tensorflow/tensorflow/commit/c55b476aa0e0bd4ee99d0f3ad18d9d706cd1260a). 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. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions. ### Attribution This vulnerability has been reported by Kang Hong Jin.

### Impact If `tf.sparse.cross` receives an input `separator` that is not a scalar, it gives a `CHECK` fail that can be used to trigger a denial of service attack. ```python import tensorflow as tf tf.sparse.cross(inputs=[],name='a',separator=tf.constant(['a', 'b'],dtype=tf.string)) ``` ### Patches We have patched the issue in GitHub commit [83dcb4dbfa094e33db084e97c4d0531a559e0ebf](https://github.com/tensorflow/tensorflow/commit/83dcb4dbfa094e33db084e97c4d0531a559e0ebf). 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. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions. ### Attribution This vulnerability has been reported by Kang Hong Jin.

A segmentation fault can occur in Brocade Fabric OS after Brocade Fabric OS v9.0 and before Brocade Fabric OS v9.2.0a through the passwdcfg command. This could allow an authenticated privileged user local user to crash a Brocade Fabric OS swith using the cli “passwdcfg --set -expire -minDiff“.

### Impact When [`mlir::tfg::GraphDefImporter::ConvertNodeDef`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/ir/importexport/graphdef_import.cc) tries to convert NodeDefs without an op name, it crashes. ```cpp Status GraphDefImporter::ConvertNodeDef(OpBuilder &builder, ConversionState &s, const NodeDef &node) { VLOG(4) << "Importing: " << node.name(); OperationState state(ConvertLocation(node), absl::StrCat("tfg.", node.op())); // The GraphImporter does light shape inference, but here we will defer all of // that to the shape inference pass. const OpDef *op_def; const OpRegistrationData *op_reg_data = nullptr; if ((op_reg_data = registry_.LookUp(node.op()))) { op_def = &op_reg_data->op_def; } else { auto it = function_op_defs_.find(node.op()); if (it == function_op_defs_.end()) return InvalidArgument("Unable to find OpDef for ", node.op()); op_def = it->second; } ``` `node.op().empt...