Insecure Random Number Generator

[gonzalo-munillag]

Hello,

I would like to bring to your attention that using the random number generator from TensorFlow could lead to vulnerabilities when sampling from a distribution to fulfill differential privacy during training: https://www.tmlt.io/research/tiny-bits-matter-precision-based-attacks-on-differential-privacy

PyTorch Opacus uses a secure RNG: https://opacus.ai/api/privacy_engine.html

In contrast, TensorFlow RNG: https://www.tensorflow.org/api_docs/python/tf/random/Generator https://stackoverflow.com/questions/63350248/is-tf-random-normal-cryptographically-secure

Additionally, there is no documentation that states the use of floating-point vulnerability protection as in https://scholar.google.com/citations?view_op=view_citation&hl=en&user=hg3A9TgAAAAJ&citation_for_view=hg3A9TgAAAAJ:dhFuZR0502QC and https://research.ibm.com/publications/secure-random-sampling-in-differential-privacy

Kind regards, Gonzalo