default <T> T newProxy(T target, Class<T> interfaceType, Duration timeout) {
    return newProxy(target, interfaceType, toNanosSaturated(timeout), TimeUnit.NANOSECONDS);
  }

  /**
   * Invokes a specified Callable, timing out after the specified time limit. If the target method
   * call finishes before the limit is reached, the return value or a wrapped exception is

    # Return some error
    ...
```

But by using the `secrets.compare_digest()` it will be secure against a type of attacks called "timing attacks".

### Timing Attacks

But what's a "timing attack"?

Let's imagine some attackers are trying to guess the username and password.

And they send a request with a username `johndoe` and a password `love123`.

    # Einen Error zurückgeben
    ...
```

Aber durch die Verwendung von `secrets.compare_digest()` ist dieser Code sicher vor einer Art von Angriffen, die „Timing-Angriffe“ genannt werden.

### Timing-Angriffe

Aber was ist ein „Timing-Angriff“?

Stellen wir uns vor, dass einige Angreifer versuchen, den Benutzernamen und das Passwort zu erraten.

    /**
     * Attaches [tag] to the request using [T] as a key. Tags can be read from a request using
     * [Request.tag]. Use null to remove any existing tag assigned for [T].
     *
     * Use this API to attach timing, debugging, or other application data to a request so that
     * you may read it in interceptors, event listeners, or callbacks.
     */
    @JvmName("reifiedTag")

    # Return some error
    ...
```

Porém, ao utilizar o `secrets.compare_digest()`, isso estará seguro contra um tipo de ataque chamado "timing attacks" (ataques de temporização).

### Ataques de Temporização

Mas o que é um "timing attack" (ataque de temporização)?

Vamos imaginar que alguns invasores estão tentando adivinhar o usuário e a senha.

      slowFactorials[i] = RANDOM_SOURCE.nextInt(factorialBound);
      binomials[i] = RANDOM_SOURCE.nextInt(factorials[i] + 1);
    }
  }

  /** Previous version of BigIntegerMath.factorial, kept for timing purposes. */
  private static BigInteger oldSlowFactorial(int n) {
    if (n <= 20) {
      return BigInteger.valueOf(LongMath.factorial(n));
    } else {
      int k = 20;

      slowFactorials[i] = RANDOM_SOURCE.nextInt(factorialBound);
      binomials[i] = RANDOM_SOURCE.nextInt(factorials[i] + 1);
    }
  }

  /** Previous version of BigIntegerMath.factorial, kept for timing purposes. */
  private static BigInteger oldSlowFactorial(int n) {
    if (n <= 20) {
      return BigInteger.valueOf(LongMath.factorial(n));
    } else {
      int k = 20;

  public static final String SERVER = "Server";
  /**
   * The HTTP <a href="https://www.w3.org/TR/server-timing/">{@code Server-Timing}</a> header field
   * name.
   *
   * @since 23.6
   */
  public static final String SERVER_TIMING = "Server-Timing";
  /**
   * The HTTP <a href="https://www.w3.org/TR/service-workers/#update-algorithm">{@code
   * Service-Worker-Allowed}</a> header field name.

	return locked
}

const (
	lockRetryInterval = 50 * time.Millisecond
)

// lockLoop will acquire either a read or a write lock
//
// The call will block until the lock is granted using a built-in
// timing randomized back-off algorithm to try again until successful
func (lm *LRWMutex) lockLoop(ctx context.Context, id, source string, timeout time.Duration, isWriteLock bool) (locked bool) {

            activeThreads--
            startNextTask()
          }
        }
      }
    }
  }

  /**
   * This blocking queue hooks into a fake clock rather than using regular JVM timing for functions
   * like [poll]. It is only usable within task faker tasks.
   */
  private inner class TaskFakerBlockingQueue<T>(
    val delegate: BlockingQueue<T>,
  ) : AbstractQueue<T>(), BlockingQueue<T> {