protobuf allows remote authenticated attackers to cause a heap-based buffer overflow.

Improper input validation vulnerability in parser_infe and sheifd_find_itemIndexin fuctions of libsimba library prior to SMR Apr-2022 Release 1 allows out of bounds write by privileged attackers.

A possible heap-based buffer overflow vulnerability in Exynos CP Chipset prior to SMR Oct-2021 Release 1 allows arbitrary memory write and code execution.

Tensorflow is an Open Source Machine Learning Framework. TensorFlow is vulnerable to a heap OOB write in `Grappler`. The `set_output` function writes to an array at the specified index. Hence, this gives a malicious user a write primitive. 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.

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.

Tensorflow is an Open Source Machine Learning Framework. An attacker can craft a TFLite model that would cause a write outside of bounds of an array in TFLite. In fact, the attacker can override the linked list used by the memory allocator. This can be leveraged for an arbitrary write primitive under certain conditions. 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.

Tensorflow is an Open Source Machine Learning Framework. The implementation of `Dequantize` does not fully validate the value of `axis` and can result in heap OOB accesses. The `axis` argument can be `-1` (the default value for the optional argument) or any other positive value at most the number of dimensions of the input. Unfortunately, the upper bound is not checked and this results in reading past the end of the array containing the dimensions of the input tensor. 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.

Tensorflow is an Open Source Machine Learning Framework. The implementation of `SparseCountSparseOutput` is vulnerable to a heap overflow. 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.

In cellular modem firmware, there is a possible out of bounds read due to a missing bounds check. This could lead to remote code execution with LTE authentication needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android kernelAndroid ID: A-240462530References: N/A

In Tensorflow version 2.3.0, the `SparseCountSparseOutput` and `RaggedCountSparseOutput` implementations don't validate that the `weights` tensor has the same shape as the data. The check exists for `DenseCountSparseOutput`, where both tensors are fully specified. In the sparse and ragged count weights are still accessed in parallel with the data. But, since there is no validation, a user passing fewer weights than the values for the tensors can generate a read from outside the bounds of the heap buffer allocated for the weights. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the implementation of `SparseFillEmptyRowsGrad` uses a double indexing pattern. It is possible for `reverse_index_map(i)` to be an index outside of bounds of `grad_values`, thus resulting in a heap buffer overflow. The issue is patched in commit 390611e0d45c5793c7066110af37c8514e6a6c54, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

Out-of-Bounds Read in netfilter/ipset in Linux Kernel ChromeOS [6.1, 5.15, 5.10, 5.4, 4.19] allows a local attacker with low privileges to trigger an out-of-bounds read, potentially leading to information disclosure

In the Pixel cellular firmware, there is a possible out of bounds write due to a missing bounds check. This could lead to remote code execution with LTE authentication needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android kernelAndroid ID: A-238914868References: N/A

A possible stack-based buffer overflow vulnerability in Exynos CP Chipset prior to SMR Oct-2021 Release 1 allows arbitrary memory write and code execution.

Improper access control for some Intel Unison software may allow an authenticated user to potentially enable escalation of privilege via network access.

Insufficient data validation in V8 API in Google Chrome prior to 128.0.6613.84 allowed a remote attacker to potentially exploit heap corruption via a crafted Chrome Extension. (Chromium security severity: Medium)

Improper authentication for some Intel Unison software may allow an authenticated user to potentially enable escalation of privilege via network access.

In launchDeepLinkIntentToRight of SettingsHomepageActivity.java, there is a possible way to launch arbitrary activities due to improper input validation. This could lead to local escalation of privilege with User execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-12L Android-13Android ID: A-250589026

A Code Execution vulnerability exists in Android prior to 4.4.0 related to the addJavascriptInterface method and the accessibility and accessibilityTraversal objects, which could let a remote malicious user execute arbitrary code.

The Device Administrator code in Android before 4.4.1_r1 might allow attackers to spoof device administrators and consequently bypass MDM restrictions by leveraging failure to update the mAdminMap data structure.

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.

Tensorflow is an Open Source Machine Learning Framework. The implementation of `Range` suffers from integer overflows. These can trigger undefined behavior or, in some scenarios, extremely large allocations. 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.

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.

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.

Tensorflow is an Open Source Machine Learning Framework. The implementation of `AssignOp` can result in copying uninitialized data to a new tensor. This later results in undefined behavior. The implementation has a check that the left hand side of the assignment is initialized (to minimize number of allocations), but does not check that the right hand side is also initialized. 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.

Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for `Dequantize` is vulnerable to an integer overflow weakness. The `axis` argument can be `-1` (the default value for the optional argument) or any other positive value at most the number of dimensions of the input. Unfortunately, the upper bound is not checked, and, since the code computes `axis + 1`, an attacker can trigger an integer overflow. 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.

An issue was discovered on Samsung mobile devices with N(7.x) software. An attacker can boot a device with root privileges because the bootloader for the Qualcomm MSM8998 chipset lacks an integrity check of the system image, aka the "SamFAIL" issue. The Samsung ID is SVE-2017-10465 (November 2017).

Access Control Vulnerability in Gerrit chromiumos project configuration in Google ChromeOS 16063.87.0 allows an attacker with a registered Gerrit account to inject malicious code into ChromeOS projects and potentially achieve Remote Code Execution and Denial of Service via editing trusted pipelines by insufficient access controls and misconfigurations in Gerrit's project.config.

Insufficient data validation in Updater in Google Chrome prior to 128.0.6537.0 allowed a remote attacker to perform privilege escalation via a malicious file. (Chromium security severity: Medium)

Improper input validation for some Intel Unison software may allow an authenticated user to potentially enable escalation of privilege via network access.

Android before 2024-10-05 on Google Pixel devices allows privilege escalation in the ABL component, A-330537292.

A privilege escalation vulnerability impacting the Google Exposure Notification Verification Server (versions prior to 0.23.1), allows an attacker who (1) has UserWrite permissions and (2) is using a carefully crafted request or malicious proxy, to create another user with higher privileges than their own. This occurs due to insufficient checks on the allowed set of permissions. The new user creation event would be captured in the Event Log.

Heap buffer overflow in Tab Groups in Google Chrome prior to 126.0.6478.54 allowed a remote attacker who convinced a user to engage in specific UI gestures to potentially exploit heap corruption via a crafted HTML page. (Chromium security severity: High)

Type Confusion in V8 in Google Chrome prior to 126.0.6478.54 allowed a remote attacker to perform an out of bounds memory write via a crafted HTML page. (Chromium security severity: High)

Out of bounds access in SwiftShader in Google Chrome prior to 73.0.3683.75 allowed a remote attacker to potentially exploit heap corruption via a crafted HTML page.

In ppcfw_deny_sec_dram_access of ppcfw.c, there is a possible arbitrary read from TEE memory due to a logic error in the code. This could lead to local information disclosure with System execution privileges needed. User interaction is not needed for exploitation.

Out of bounds write in Streams API in Google Chrome prior to 125.0.6422.141 allowed a remote attacker to execute arbitrary code inside a sandbox via a crafted HTML page. (Chromium security severity: High)

In closeChannel of secureelementimpl.cpp, there is a possible out of bounds read due to an incorrect bounds check. This could lead to local information disclosure with no additional execution privileges needed. User interaction is not needed for exploitation.

In static long dev_send of tipc_dev_ql, there is a possible out of bounds read due to an incorrect bounds check. This could lead to local information disclosure with no additional execution privileges needed. User interaction is not needed for exploitation.

In all Android releases from CAF using the Linux kernel, a kernel driver has an off-by-one buffer over-read vulnerability.

In a camera driver function in all Android releases from CAF using the Linux kernel, a bounds check is missing when writing into an array potentially leading to an out-of-bounds heap write.

In Android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, while processing a specially crafted cfg80211 vendor command, a buffer over-read can occur.

Out of bounds access in SwiftShader in Google Chrome prior to 73.0.3683.75 allowed a remote attacker to potentially exploit heap corruption via a crafted HTML page.

Heap buffer overflow in ANGLE in Google Chrome on Windows prior to 74.0.3729.108 allowed a remote attacker to potentially exploit heap corruption via a crafted HTML page.

Insufficient input validation in WebGL in Google Chrome prior to 72.0.3626.81 allowed a remote attacker to perform an out of bounds memory read via a crafted HTML page.

In all Qualcomm products with Android releases from CAF using the Linux kernel, in a driver function, a value from userspace is not properly validated potentially leading to an out of bounds heap write.

In all Qualcomm products with Android releases from CAF using the Linux kernel, due to a type downcast, a value may improperly pass validation and cause an out of bounds write later.

Out of bounds read in Skia in Google Chrome prior to 75.0.3770.80 allowed a remote attacker to obtain potentially sensitive information from process memory via a crafted HTML page.

Integer overflow in PDFium in Google Chrome prior to 74.0.3729.108 allowed a remote attacker to potentially exploit heap corruption via a crafted PDF file.

Integer overflow in PDFium in Google Chrome prior to 76.0.3809.87 allowed a remote attacker to potentially exploit heap corruption via a crafted PDF file.