To generate true random values that can be used for cryptography std::random_device has to be used as generator.

#include <iostream>
#include <random>

int main()
{
   std::random_device crypto_random_generator;
   std::uniform_int_distribution<int> int_distribution(0,9);
   
   int actual_distribution[10] = {0,0,0,0,0,0,0,0,0,0};
   
   for(int i = 0; i < 10000; i++) {
       int result = int_distribution(crypto_random_generator);
       actual_distribution[result]++;
   }

   for(int i = 0; i < 10; i++) {
       std::cout << actual_distribution[i] << " ";
   }
   
   return 0;
}

std::random_device is used in the same way as a pseudo random value generator is used.

However std::random_device may be implemented in terms of an implementation-defined pseudo-random number engine if a non-deterministic source (e.g. a hardware device) isn't available to the implementation.

Detecting such implementations should be possible via the entropy member function (which return zero when the generator is completely deterministic), but many popular libraries (both GCC's libstdc++ and LLVM's libc++) always return zero, even when they're using high-quality external randomness.

A pseudo-random number generator generates values that can be guessed based on previously generated values. In other words: it is deterministic. Do not use a pseudo-random number generator in situations where a true random number is required.

#include <iostream>
#include <random>

int main()
{
   std::default_random_engine pseudo_random_generator;
   std::uniform_int_distribution<int> int_distribution(0, 9);
   
   int actual_distribution[10] = {0,0,0,0,0,0,0,0,0,0};
   
   for(int i = 0; i < 10000; i++) {
       int result = int_distribution(pseudo_random_generator);
       actual_distribution[result]++;
   }

   for(int i = 0; i <= 9; i++) {
       std::cout << actual_distribution[i] << " ";
   }
   
   return 0;
}

This code creates a random number generator, and a distribution that generates integers in the range [0,9] with equal likelihood. It then counts how many times each result was generated.

The template parameter of std::uniform_int_distribution<T> specifies the type of integer that should be generated. Use std::uniform_real_distribution<T> to generate floats or doubles.

The random number generator can (and should) be used for multiple distributions.

#include <iostream>
#include <random>

int main()
{
   std::default_random_engine pseudo_random_generator;
   std::uniform_int_distribution<int> int_distribution(0, 9);
   std::uniform_real_distribution<float> float_distribution(0.0, 1.0);
   std::discrete_distribution<int> rigged_dice({1,1,1,1,1,100});
   
   std::cout << int_distribution(pseudo_random_generator) << std::endl;
   std::cout << float_distribution(pseudo_random_generator) << std::endl;
   std::cout << (rigged_dice(pseudo_random_generator) + 1) << std::endl;
   
   return 0;
}

In this example, only one generator is defined. It is subsequently used to generate a random value in three different distributions. The rigged_dice distribution will generate a value between 0 and 5, but almost always generates a 5, because the chance to generate a 5 is 100 / 105.