Access of Resource Using Incompatible Type ('Type Confusion')

In Eclipse Openj9 before version 0.32.0, Java 8 & 11 fail to throw the exception captured during bytecode verification when verification is triggered by a MethodHandle invocation, allowing unverified methods to be invoked using MethodHandles.Show less

In Firebase PHP-JWT before 6.0.0, an algorithm-confusion issue (e.g., RS256 / HS256) exists via the kid (aka Key ID) header, when multiple types of keys are loaded in a key ring. This allows an attacker to forge tokens that validate under the incorrect key. NOTE: this provides a straightforward way to use the PHP-JWT library unsafely, but might not be considered a vulnerability in the library itself.Show less

A type confusion issue was addressed with improved state handling. This issue is fixed in macOS Big Sur 11.6.5, macOS Monterey 12.3, Security Update 2022-003 Catalina. An application may be able to execute arbitrary code with kernel privileges.Show less

Envoy is an open source edge and service proxy, designed for cloud-native applications. The default_validator.cc implementation used to implement the default certificate validation routines has a "type confusion" bug when processing subjectAltNames. This processing allows, for example, an rfc822Name or uniformResourceIndicator to be authenticated as a domain name. This confusion allows for the bypassing of nameConstraints, as processed by the underlying OpenSSL/BoringSSL implementation, exposing the possibility of impersonation of arbitrary servers. As a result Envoy will trust upstream certificates that should not be trusted.Show less

A vulnerability has been identified in Simcenter Femap V2020.2 (All versions), Simcenter Femap V2021.1 (All versions). Affected application contains a type confusion vulnerability while parsing NEU files. This could allow an attacker to execute code in the context of the current process. (ZDI-CAN-14643, ZDI-CAN-14644, ZDI-CAN-14755, ZDI-CAN-15183)Show less

Tensorflow is an Open Source Machine Learning Framework. A malicious user can cause a denial of service by altering a `SavedModel` such that any binary op would trigger `CHECK` failures. This occurs when the protobuf part corresponding to the tensor arguments is modified such that the `dtype` no longer matches the `dtype` expected by the op. In that case, calling the templated binary operator for the binary op would receive corrupted data, due to the type confusion involved. If `Tin` and `Tout` don't match the type of data in `out` and `input_*` tensors then `flat<*>` would interpret it wrongly. In most cases, this would be a silent failure, but we have noticed scenarios where this results in a `CHECK` crash, hence a denial of service. 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.Show less

Tensorflow is an Open Source Machine Learning Framework. The implementation of `MapStage` is vulnerable a `CHECK`-fail if the key tensor is not a scalar. 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.Show less

Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for `ConcatV2` can be used to trigger a denial of service attack via a segfault caused by a type confusion. The `axis` argument is translated into `concat_dim` in the `ConcatShapeHelper` helper function. Then, a value for `min_rank` is computed based on `concat_dim`. This is then used to validate that the `values` tensor has at least the required rank. However, `WithRankAtLeast` receives the lower bound as a 64-bits value and then compares it against the maximum 32-bits integer value that could be represented. Due to the fact that `min_rank` is a 32-bits value and the value of `axis`, the `rank` argument is a negative value, so the error check is bypassed. 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.Show less

This vulnerability allows local attackers to escalate privileges on affected installations of Linux Kernel 5.14-rc3. An attacker must first obtain the ability to execute low-privileged code on the target system in order to exploit this vulnerability. The specific flaw exists within the handling of eBPF programs. The issue results from the lack of proper validation of user-supplied eBPF programs, which can result in a type confusion condition. An attacker can leverage this vulnerability to escalate privileges and execute arbitrary code in the context of the kernel. Was ZDI-CAN-14689.Show less

By passing invalid javascript code where await and yield were called upon non-async and non-generator getter/setter functions, Hermes would invoke generator functions and error out on invalid await/yield positions. This could result in segmentation fault as a consequence of type confusion error, with a low chance of RCE. This issue affects Hermes versions prior to v0.10.0.Show less