## Version 2.7.4

_2016-02-07_

 *  Fix: Don't crash when finding the trust manager if the Play Services (GMS)
    security provider is installed.
 *  Fix: The previous release introduced a performance regression on Android,
    caused by looking up CA certificates. This is now fixed.


## Version 2.7.3

_2016-02-06_

 *  Fix: Permit the trusted CA root to be pinned by `CertificatePinner`.


## Version 2.7.2

      }

    /**
     * Sets the certificate pinner that constrains which certificates are trusted. By default HTTPS
     * connections rely on only the [SSL socket factory][sslSocketFactory] to establish trust.
     * Pinning certificates avoids the need to trust certificate authorities.
     */
    fun certificatePinner(certificatePinner: CertificatePinner) =
      apply {

        map = new HashMap();

        if (dfs.isTrustedDomain(getServer(), auth)) {
            /* The server name is actually the name of a trusted
             * domain. Add DFS roots to the list.
             */
            try {
                entries = doDfsRootEnum();
                for (int ei = 0; ei < entries.length; ei++) {

	rCASecret := secret.GetValidationContext()
	if rCASecret != nil {
		trustCA := rCASecret.GetTrustedCa()
		if trustCA != nil {
			inlineBytes := trustCA.GetInlineBytes()
			if inlineBytes != nil {
				returnStr = base64.StdEncoding.EncodeToString(inlineBytes)
				returnErr = nil
			} else {
				returnStr = ""
				returnErr = fmt.Errorf("can not retrieve inlineBytes from trustCA section")
			}
		} else {
			returnStr = ""

- Fixed an issue where the `vsphere` cloud provider would not trust a certificate if:
  - The issuer of the certificate was unknown (`x509.UnknownAuthorityError`)
  - The requested name did not match the set of authorized names (`x509.HostnameError`)

computation
[**graphs**](https://developers.google.com/machine-learning/glossary/#graph).
Since models are practically programs that TensorFlow executes, using untrusted
models or graphs is equivalent to running untrusted code.

If you need to run untrusted models, execute them inside a
[**sandbox**](https://developers.google.com/code-sandboxing). Memory corruptions
in TensorFlow ops can be recognized as security issues only if they are

- **Focus**:
  1. Configuration and communication of Ambient components.
  1. Interaction between `ztunnel` and Ambient components.
  1. Validation of zero-trust security policies.
  1. Testing of ambient traffic management.
  1. Specific `istioctl ztunnel-config` commands being tested: `all`, `services`, `workloads`, `policies`, `certificates`.

      .build()
  }

  /** Returns an SSL client for this host's localhost address. */
  @JvmStatic
  fun localhost(): HandshakeCertificates = localhost

  /** Returns a trust manager that trusts `trustedCertificates`. */
  @JvmStatic @IgnoreJRERequirement
  fun newTrustManager(
    keyStoreType: String?,
    trustedCertificates: List<X509Certificate>,
    insecureHosts: List<String>,

take some action immediately after upgrading. In multi-tenant clusters where not all users are trusted, you are advised to create appropriate quotas for two default priority classes, system-cluster-critical and system-node-critical, which are added to clusters by default. `ResourceQuota` should be created to limit users from creating Pods at these priorities if not all users of your cluster are trusted. We do not advise disabling this feature because critical system Pods rely on the scheduler preemption...

     * OS family that can be tested for. {@value}
     */
    private static final String FAMILY_OS2 = "os/2";

    /**
     * OS family that can be tested for. {@value}
     */
    private static final String FAMILY_NETWARE = "netware";

    /**
     * OS family that can be tested for. {@value}
     */
    private static final String FAMILY_DOS = "dos";

    /**
     * OS family that can be tested for. {@value}
     */