CWE-415

diplib v3.0.0 is vulnerable to Double Free.

TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation for `tf.raw_ops.BoostedTreesCreateEnsemble` can result in a use after free error if an attacker supplies specially crafted arguments. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/boosted_trees/resource_ops.cc#L55) uses a reference counted resource and decrements the refcount if the initialization fails, as it should. However, when the code was written, the resource was represented as a naked pointer but later refactoring has changed it to be a smart pointer. Thus, when the pointer leaves the scope, a subsequent `free`-ing of the resource occurs, but this fails to take into account that the refcount has already reached 0, thus the resource has been already freed. During this double-free process, members of the resource object are accessed for cleanup but they are invalid as the entire resource has been freed. We have patched the issue in GitHub commit 5ecec9c6fbdbc6be03295685190a45e7eee726ab. 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.

A double-free vulnerability exists in fig2dev through 3.28a is affected by: via the free_stream function in readpics.c, which could cause a denial of service (context-dependent).

hso_free_net_device in drivers/net/usb/hso.c in the Linux kernel through 5.13.4 calls unregister_netdev without checking for the NETREG_REGISTERED state, leading to a use-after-free and a double free.

There is a Double free vulnerability in Smartphone.Successful exploitation of this vulnerability may cause a kernel crash or privilege escalation.

There is a Incorrect Calculation of Buffer Size vulnerability in Huawei Smartphone.Successful exploitation of this vulnerability may lead to memory crash.