- FibreChannel volume plugin may match the wrong device and wrong associated devicemapper parent. This may cause a disaster that pods attach wrong disks. ([#110719](https://github.com/kubernetes/kubernetes/pull/110719), [@xakdwch](https://github.com/xakdwch))

- Only update Azure data disks when attach/detach ([#94265](https://github.com/kubernetes/kubernetes/pull/94265), [@andyzhangx](https://github.com/andyzhangx)) [SIG Cloud Provider]
- Promote SupportNodePidsLimit to GA to provide node-to-pod PID isolation.

- Fixes issue where you can't attach more than 15 GCE Persistent Disks to c2, n2, m1, m2 machine types. ([#88602](https://github.com/kubernetes/kubernetes/pull/88602), [@yuga711](https://github.com/yuga711)) [SIG Storage]

- Fixes issue where you can't attach more than 15 GCE Persistent Disks to c2, n2, m1, m2 machine types. ([#88602](https://github.com/kubernetes/kubernetes/pull/88602), [@yuga711](https://github.com/yuga711)) [SIG Storage]

* Azure VM names can now contain the underscore (`_`) character ([#63526](https://github.com/kubernetes/kubernetes/pull/63526), [@djsly](https://github.com/djsly))
* Azure disks now support external resource groups.
([#64427](https://github.com/kubernetes/kubernetes/pull/64427), [@andyzhangx](https://github.com/andyzhangx))
* Added reason message logs for non-existent Azure resources.

to set requests and limits on ephemeral local storage resources. In addition, you can now create [Local Persistent Storage](https://github.com/kubernetes/enhancements/issues/121), which enables PersistentVolumes to be created with locally attached disks, and not just network volumes.

On the Persistent Volumes side, this release [Prevents deletion of Persistent Volume Claims that are used by a pod](https://github.com/kubernetes/enhancements/issues/498) and [Persistent Volumes that are...

# Using TensorFlow Securely

This document discusses the TensorFlow security model. It describes the security
risks to consider when using models, checkpoints or input data for training or
serving. We also provide guidelines on what constitutes a vulnerability in
TensorFlow and how to report them.

This document applies to other repositories in the TensorFlow organization,
covering security practices for the entirety of the TensorFlow ecosystem.

- **Security:**
Java serialization poses security risks, especially related to deserialization vulnerabilities.

- **Version Compatibility:**
With Java serialization, even minor changes to a class (like adding a field) can break compatibility.

- **Cross-Language Compatibility:**

    // If anyone in our monorepo uses the Android copy of Guava on a JVM, that would be unfortunate.
    // But that is only likely to happen in Robolectric tests, where the risks of JDK regex are low.
    return new JdkPatternCompiler();
  }

  private static final class JdkPatternCompiler implements PatternCompiler {
    @Override
    public CommonPattern compile(String pattern) {

PURPOSE. Each Recipient is solely responsible for determining the
appropriateness of using and distributing the Program and assumes all
risks associated with its exercise of rights under this Agreement,
including but not limited to the risks and costs of program errors,
compliance with applicable laws, damage to or loss of data, programs
or equipment, and unavailability or interruption of operations.