TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.QuantizeAndDequantizeV4Grad` is vulnerable to an integer overflow issue caused by converting a signed integer value to an unsigned one and then allocating memory based on this value. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L126) uses the `axis` value as the size argument to `absl::InlinedVector` constructor. But, the constructor uses an unsigned type for the argument, so the implicit conversion transforms the negative value to a large integer. We have patched the issue in GitHub commit 96f364a1ca3009f98980021c4b32be5fdcca33a1. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, and TensorFlow 2.4.3, as these are also affected and still in supported range.

An issue was discovered in the anymap crate through 0.12.1 for Rust. It violates soundness via conversion of a *u8 to a *u64.

Trend Micro Password Manager (Consumer) version 5.0.0.1217 and below is vulnerable to an Integer Truncation Privilege Escalation vulnerability which could allow a local attacker to trigger a buffer overflow and escalate privileges on affected installations. An attacker must first obtain the ability to execute low-privileged code on the target system in order to exploit this vulnerability.

Due to unexpected data type conversions, a use-after-free could have occurred when interacting with the font cache. We presume that with enough effort this could have been exploited to run arbitrary code. This vulnerability affects Firefox < 88.

Cranelift is an open-source code generator maintained by Bytecode Alliance. It translates a target-independent intermediate representation into executable machine code. There is a bug in 0.73 of the Cranelift x64 backend that can create a scenario that could result in a potential sandbox escape in a Wasm program. This bug was introduced in the new backend on 2020-09-08 and first included in a release on 2020-09-30, but the new backend was not the default prior to 0.73. The recently-released version 0.73 with default settings, and prior versions with an explicit build flag to select the new backend, are vulnerable. The bug in question performs a sign-extend instead of a zero-extend on a value loaded from the stack, under a specific set of circumstances. If those circumstances occur, the bug could allow access to memory addresses upto 2GiB before the start of the Wasm program heap. If the heap bound is larger than 2GiB, then it would be possible to read memory from a computable range de…

TensorFlow is an end-to-end open source platform for machine learning. Calling `tf.raw_ops.ImmutableConst`(https://www.tensorflow.org/api_docs/python/tf/raw_ops/ImmutableConst) with a `dtype` of `tf.resource` or `tf.variant` results in a segfault in the implementation as code assumes that the tensor contents are pure scalars. We have patched the issue in 4f663d4b8f0bec1b48da6fa091a7d29609980fa4 and will release TensorFlow 2.5.0 containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved. If using `tf.raw_ops.ImmutableConst` in code, you can prevent the segfault by inserting a filter for the `dtype` argument.

An information disclosure vulnerability exists in the /proc/pid/syscall functionality of Linux Kernel 5.1 Stable and 5.4.66. More specifically, this issue has been introduced in v5.1-rc4 (commit 631b7abacd02b88f4b0795c08b54ad4fc3e7c7c0) and is still present in v5.10-rc4, so it’s likely that all versions in between are affected. An attacker can read /proc/pid/syscall to trigger this vulnerability, which leads to the kernel leaking memory contents.

django-filter is a generic system for filtering Django QuerySets based on user selections. In django-filter before version 2.4.0, automatically generated `NumberFilter` instances, whose value was later converted to an integer, were subject to potential DoS from maliciously input using exponential format with sufficiently large exponents. Version 2.4.0+ applies a `MaxValueValidator` with a a default `limit_value` of 1e50 to the form field used by `NumberFilter` instances. In addition, `NumberFilter` implements the new `get_max_validator()` which should return a configured validator instance to customise the limit, or else `None` to disable the additional validation. Users may manually apply an equivalent validator if they are not able to upgrade.

The bpf verifier in the Linux kernel did not properly handle mod32 destination register truncation when the source register was known to be 0. A local attacker with the ability to load bpf programs could use this gain out-of-bounds reads in kernel memory leading to information disclosure (kernel memory), and possibly out-of-bounds writes that could potentially lead to code execution. This issue was addressed in the upstream kernel in commit 9b00f1b78809 ("bpf: Fix truncation handling for mod32 dst reg wrt zero") and in Linux stable kernels 5.11.2, 5.10.19, and 5.4.101.

An issue was discovered in GNOME GLib before 2.66.7 and 2.67.x before 2.67.4. If g_byte_array_new_take() was called with a buffer of 4GB or more on a 64-bit platform, the length would be truncated modulo 2**32, causing unintended length truncation.