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If I run this command in Ubuntu

$ sudo cat /proc/sys/kernel/random/entropy_avail

it returns a number that indicates how much "entropy" is available to the kernel, but that's about all I know. What unit is this entropy measured in? What is it used for? I've been told it's "bad" if that number is "low"... How low is "low" and what "bad" things will happen if it is? What's a good range for it to be at? How is it determined?

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I love when people ask for explanations of complex, nuanced technical issues in "plain english". It turns out that almost every profession uses incredibly specific language to describe issues unique to that field or problem-set. That aren't doing it to exclude you, they're doing it because the exact form of that language has meaning inside of that profession that can't be conveyed in "plain english". There's a reason people get paid to do stuff and experience counts. Often an answer in "plain english" will leave out nuanced detail, biting the receiver in the butt later... –  jj33 Aug 19 '10 at 15:41
@jj33 There's no reason a high-level overview can't be given. The answers in this question are quite helpful. It doesn't sound like he needs the "nuanced detail". –  ceejayoz Jul 8 '11 at 14:05
@ceejayoz I actually totally agreed. I have no idea why I unloaded on this question. My general statement is true, but I'm not sure why I felt it needed to be said in response to this question, which seems like a perfectly reasonable request for information. –  jj33 Jul 8 '11 at 14:25

3 Answers 3

up vote 3 down vote accepted

Your system gathers some "real" random numbers by keeping an eye about different events: network activity, hardware random number generator (if available; for example VIA processors usually has a "real" random number generator), and so on. If feeds those to kernel entropy pool, which is used by /dev/random. Applications which need some extreme security tend to use /dev/random as their entropy source, or in other words, the randomness source.

If /dev/random runs out of available entropy, it's unable to serve out more randomness and the application waiting for the randomness stalls until more random stuff is available. The example I've seen during my career is that Cyrus IMAP daemon wanted to use /dev/random for the randomness and its POP sessions wanted to generate the random strings in APOP connections from /dev/random. In a busy environment there were more login attempts than traffic for feeding the /dev/random -> everything stalled. In that case I installed rng-tools and activated the rngd it had -- that shoveled semi-random numbers from /dev/urandom to /dev/random in case /dev/random ran out of "real" entropy.

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If you want a simpler overview of the underlying issue: Some applications (such as encryption) need random numbers. You can generate random numbers using an algorithm - but although these seem random in one sense they are totally predictable in another. For instance if I give you the digits 58209749445923078164062862089986280348253421170679, they look pretty random. But if you realise they are actually digits of PI, then you would know the next one is going to be 8.

For some applications this is OK, but for other applications (especially security related ones) people want genuine unpredictable randomness - which can't be generated by an algorithm (i.e. program) since that is by definition predictable. This is a problem in that your computer essentially is a program, so how can it possibly get genuine random numbers? The answer is by measuring genuinely random events from the outside world - for example gaps between your keypresses and using these to inject genuine randomness into the otherwise predictable random number generator. The 'entropy pool' could be thought of as the store of this randomness which gets built up by the keystrokes (or whatever is being used) and drained by the generation of random numbers.

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Nice explanation ... –  pradipta Jul 23 '13 at 19:35

The read-only file entropy_avail gives the available entropy. Normally, this will be 4096 (bits), a full entropy pool.

You can read more at: http://linux.die.net/man/4/random

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