Background. Being able to trust cryptographic algorithms is a crucial part of society today, because of all the information that is gathered by companies all over the world. With this thesis, we want to help both Promestra AB and potential future customers to evaluate if you can trust their random number generator.

Objectives. The main objective for the study is to compare the random number generator in Promestra security with the help of the test suite made by the NationalInstitute of Standards and Technology. The comparison will be made with other random number generators such as Mersenne Twister, Blum-Blum-Schub and more.

Methods. The selected method in this study was to gather a total of 100 million bits of each random number generator and use these in the National Institute ofStandards and Technology test suite for 100 tests to get a fair evaluation of the algorithms. The test suite provides a statistical summary which was then analyzed.

Results. The results show how many iterations out of 100 that have passed and also the distribution between the results. The obtained results show that there are some random number generators that have been tested that clearly struggles in many of the tests. It also shows that half of the tested generators passed all of the tests.

Conclusions. Promestra security and Blum-Blum-Schub is close to passing all the tests, but in the end, they cannot be considered to be the preferable random number generator. The five that passed and seem to have no clear limitations are:Random.org, Micali-Schnorr, Linear-Congruential, CryptGenRandom, and MersenneTwister.