Incorrect Conversion between Numeric Types

TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.StringNGrams` 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/string_ngrams_op.cc#L184) calls `reserve` on a `tstring` with a value that sometimes can be negative if user supplies negative `ngram_widths`. The `reserve` method calls `TF_TString_Reserve` which has an `unsigned long` argument for the size of the buffer. Hence, the implicit conversion transforms the negative value to a large integer. We have patched the issue in GitHub commit c283e542a3f422420cfdb332414543b62fc4e4a5. 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.Show less

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.Show less

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.Show less

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.Show less

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 dependent on the size of the heaps bound. The impact of this bug is highly dependent on heap implementation, specifically: * if the heap has bounds checks, and * does not rely exclusively on guard pages, and * the heap bound is 2GiB or smaller * then this bug cannot be used to reach memory from another Wasm program heap. The impact of the vulnerability is mitigated if there is no memory mapped in the range accessible using this bug, for example, if there is a 2 GiB guard region before the Wasm program heap. The bug in question performs a sign-extend instead of a zero-extend on a value loaded from the stack, when the register allocator reloads a spilled integer value narrower than 64 bits. This interacts poorly with another optimization: the instruction selector elides a 32-to-64-bit zero-extend operator when we know that an instruction producing a 32-bit value actually zeros the upper 32 bits of its destination register. Hence, we rely on these zeroed bits, but the type of the value is still i32, and the spill/reload reconstitutes those bits as the sign extension of the i32’s MSB. The issue would thus occur when: * An i32 value in a Wasm program is greater than or equal to 0x8000_0000; * The value is spilled and reloaded by the register allocator due to high register pressure in the program between the value’s definition and its use; * The value is produced by an instruction that we know to be “special” in that it zeroes the upper 32 bits of its destination: add, sub, mul, and, or; * The value is then zero-extended to 64 bits in the Wasm program; * The resulting 64-bit value is used. Under these circumstances there is a potential sandbox escape when the i32 value is a pointer. The usual code emitted for heap accesses zero-extends the Wasm heap address, adds it to a 64-bit heap base, and accesses the resulting address. If the zero-extend becomes a sign-extend, the program could reach backward and access memory up to 2GiB before the start of its heap. In addition to assessing the nature of the code generation bug in Cranelift, we have also determined that under specific circumstances, both Lucet and Wasmtime using this version of Cranelift may be exploitable. See referenced GitHub Advisory for more details.Show less

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.Show less

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.Show less

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.Show less

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.Show less

An issue was discovered in GNOME GLib before 2.66.6 and 2.67.x before 2.67.3. The function g_bytes_new has an integer overflow on 64-bit platforms due to an implicit cast from 64 bits to 32 bits. The overflow could potentially lead to memory corruption.Show less

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.Show less

An exploitable signed conversion vulnerability exists in the TextMaker document parsing functionality of SoftMaker Office 2021’s TextMaker application. A specially crafted document can cause the document parser to miscalculate a length used to allocate a buffer, later upon usage of this buffer the application will write outside its bounds resulting in a heap-based memory corruption. An attacker can entice the victim to open a document to trigger this vulnerability.Show less

An exploitable sign extension vulnerability exists in the TextMaker document parsing functionality of SoftMaker Office 2021’s TextMaker application. A specially crafted document can cause the document parser to sign-extend a length used to terminate a loop, which can later result in the loop’s index being used to write outside the bounds of a heap buffer during the reading of file data. An attacker can entice the victim to open a document to trigger this vulnerability.Show less

An issue was discovered in Contiki through 3.0. A memory corruption vulnerability exists in the uIP TCP/IP stack component when handling RPL extension headers of IPv6 network packets in rpl_remove_header in net/rpl/rpl-ext-header.c.Show less

An Integer signedness error in the JavaScript Interpreter in Facebook Hermes prior to commit 2c7af7ec481ceffd0d14ce2d7c045e475fd71dc6 allows attackers to cause a denial of service attack or a potential RCE via crafted JavaScript. Note that this is only exploitable if the application using Hermes permits evaluation of untrusted JavaScript. Hence, most React Native applications are not affected.Show less

Due to confusion about ValueTags on JavaScript Objects, an object may pass through the type barrier, resulting in memory corruption and a potentially exploitable crash. *Note: this issue only affects Firefox on ARM64 platforms.* This vulnerability affects Firefox ESR < 68.10, Firefox < 78, and Thunderbird < 68.10.0.Show less