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Common Weakness Enumeration (CWE)
TensorFlow is an open source platform for machine learning. In affected versions TensorFlow's Grappler optimizer has a use of unitialized variable. If the `train_nodes` vector (obtained from the saved model that gets optimized) does not contain a `Dequeue` node, then `dequeue_node` is left unitialized. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
This vulnerability allows local attackers to disclose sensitive information on affected installations of Parallels Desktop 16.1.3 (49160). An attacker must first obtain the ability to execute low-privileged code on the target guest system in order to exploit this vulnerability. The specific flaw exists within the Toolgate component. The issue results from the lack of proper initialization of memory prior to accessing it. An attacker can leverage this in conjunction with other vulnerabilities to escalate privileges and execute arbitrary code in the context of the hypervisor. Was ZDI-CAN-13592.
In display driver, there is a possible memory corruption due to uninitialized data. This could lead to local escalation of privilege with System execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS05594994; Issue ID: ALPS05594994.
In memzero_explicit of compiler-clang.h, there is a possible bypass of defense in depth due to uninitialized data. This could lead to local information disclosure with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android kernelAndroid ID: A-171418586References: Upstream kernel
An issue was discovered in function scanallsubs in src/sbbs3/scansubs.cpp in Synchronet BBS, which may allow attackers to view sensitive information due to an uninitialized value.
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.
Uninitialized use in Media in Google Chrome prior to 92.0.4515.107 allowed a remote attacker to perform out of bounds memory access via a crafted HTML page.
A flaw was found in libwebp in versions before 1.0.1. An unitialized variable is used in function ReadSymbol. The highest threat from this vulnerability is to data confidentiality and integrity as well as system availability.
TensorFlow is an end-to-end open source platform for machine learning. Due to lack of validation in `tf.raw_ops.CTCBeamSearchDecoder`, an attacker can trigger denial of service via segmentation faults. The implementation(https://github.com/tensorflow/tensorflow/blob/a74768f8e4efbda4def9f16ee7e13cf3922ac5f7/tensorflow/core/kernels/ctc_decoder_ops.cc#L68-L79) fails to detect cases when the input tensor is empty and proceeds to read data from a null buffer. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
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