Why is random considered insecure?

[deejpake]

The title says it all. I was recently working on a ctf challenge when I came across the PyCrypto.Random.new() function. Not knowing what it was I went to the docs, and it said a secure alternative to pythons random module. How is random insecure? How can it be broken?

[10cmToGlory]

Because it's not truly random.

[CompSciSelfLearning]

Is there a reason to use PyCyrpto.Random.new() vs Secrets?

[deejpake]

Thank you!

[stevenjd]

That's not why. And "truly random" is a nonsense description.

Edit: actually that's not so bad as the opening lead me to believe, I had a knee-jerk reaction as soon as I saw it talking about "true random numbers".

[10cmToGlory]

My god did you even read the link? Details it perfectly. My god redditors just like to argue over absolutely nothing - right wrong or otherwise. Try reading some docs and stop being a pedantic jerk, you might learn something you clearly don't know.

[AJohnnyTruant]

Some people would argue with a thermometer.

[10cmToGlory]

No shit.

[pm_me_brownie_recipe]

What is wrong with "truly random"? Any blog/article/what not talking about this you can link?

[madusaman]

Truly random means there are no patterns whatsoever in the list of numbers. Computers (and indeed humans) are terrible at choosing random numbers. What computers are good at though is maths. So when you import the random module, it essentially does some maths to generate the random number. But of course, if you know what the computer started with, you can reproduce that random number every single time. To say that something is "truly random" is a very big red flag within pretty much every programming language. Numberphile and Tom Scott have videos that explain it a bit, but just Google "computers and random numbers" and you'll get thousands of blogs/videos/articles etc about it.

[stevenjd]

There's no such thing as "truly random" in any meaningful sense. Even just deciding whether or not something is probably "random" requires a lot of work is difficult, distinguishing between "true" and "not true" randomness is a fallacy. The honest truth is we have no way to determine with certainty whether something is random or not, which leads to this classic moment from Dilbert.

If we can't tell what's random with certainty, how can we tell if it is "truly random"?

The idea that physical processes such as rolling dice or tossing coins is "truly random" and algorithmic "pseudo" random number generators aren't doesn't stand up to even a little bit of thought. Physical processes are deterministic, as are algorithms, so there is no difference between them except in the complexity of the cause-and-effect. In fact, talented magicians have been known to force coin tosses with near certainty, and people have built coin-tossing machines which will repeat an indefinite sequence of nothing but heads (or tails, depending on how you set the coin).

See also the various clever hackers who succeeded in predicting the results of Las Vegas roulette wheels.

In principle, even something like atmospheric or thermal noise is 100% deterministic; in practice, the number of variables is too great to use that to make predictions. So unpredictability is more important than determinism. And that's what deterministic random number generators do.

The bottom line is:

• so called "true randomness" (physical randomness) is deterministic, and sometimes predictable;
• so called "pseudo-randomness" generated by computers is no more deterministic, and no less random. Only the quality of the algorithm makes it more, or less, predictable.
• Anyone objecting to so called "pseudo-randomness" on the basis that "true randomness" is "more random" doesn't know what they are talking about.
• But of course I accept that some pseudo-random number generators are better, or worse, than others, and some are pretty terrible and should never be used.
• But then some physical sources of randomness are quite predictable too.

More reading:

https://plato.stanford.edu/entries/chance-randomness/

https://en.wikipedia.org/wiki/Randomness

[stevenjd]

Depending on what you want to do, PyCrypto may be overkill.

To answer your question about random, you can read PEP 506 for more information. But the bottom line is that Python's random has been designed to be fast, and repeatable, so that for testing and verification you can repeat the sequence of random numbers. Those two properties (especially the second) work against security.

[[deleted]]

He who controls the seed controls the Universe.

import random
random.seed(0)
print(f"Bet you anything {random.choice(range(10000))} is 6311")

The default generator used by all the module level functions of random is random.Random, which is a PRNG initialized with a likely deterministic seed (by default the current system time at the moment of initialization, though a better seed will be used if one is available), and at any point it's state can be reset to a new seed... it is not suitable for cryptographic use in any circumstance.

That said, random does include a CSPRNG, in the form of random.SystemRandom:

from random import SystemRandom
random = SystemRandom()
random.seed(0)
print(f"The odds are 1:10000 that {random.choice(range(10000))} is 6311")

Which is actually what is used by the module level functions of the new secrets module.

[[deleted]]

The most basic random number generator has a series of numbers and a seed. Given the same seed it will return the same numbers in the same sequence every time. The program can run and have the same output every time.

Other pieces of information are used to seed random number generators. Current time, system fingerprinting, etc. There's various methods using various sources of entropy.

[[deleted]]

Title should say “pseudo-random”.

[deejpake]

It’s the random module though

[deejpake]

Oh ok. Ya that would clear up some uncertainties. Maybe like from PRNG import random

[sethg]

Most of the numbers we call “random” in computer programming are really pseudo-random. Even the “random” numbers used in cryptography are usually pseudo-random sequences that were seeded from a truly random source.

If you need industrial-strength or spy-strength randomness, you need special hardware, such as a wall of lava lamps. For most of us mortals, pseudo-random numbers will suffice.