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  1. PO
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    <p>I found a great solution by simply mimicking what Java's SecureRandom.nextInt(int) is doing at here: <a href="http://grepcode.com/file/repository.grepcode.com/java/root/jdk/openjdk/6-b14/java/security/SecureRandom.java#SecureRandom.next%28int%29" rel="nofollow">SecureRandom.nextInt(int)</a> Will post code as soon as I can get to code it (I'm busy at the moment). I plan to use the code I develop from it, since I confirmed the proposed solution has a bias (it is not acceptable at all).</p> <p>Here is the adaptation of the JDK code. Notice the limitations on 31 bit numbers, since I realized JS does all its bitwise operations on two's complement with 32 bits. I did not implement the special case for power of 2 numbers since I won't be using it. The solution is for numbers in general and not only powers of 10... I'm sure there must be a better solution for numbers with base 10, but whatever. I rewrote the code to not use my libraries and to make it in English, so that others can use it more easily.</p> <pre><code>var crypto_random_number_range = function (n, cb) { //result is a number from 0 a n-1 //Javascript works with 32 bits for bitwise operations but these are signed (2-complement), so it is good to limit the size of n if (n &lt;= 0 || n &gt; 2147483647) { return cb("n must be larger than 0 and smaller than 2147483647", null); } var bits, val; async.doWhilst( function (cb2) { crypto.randomBytes(4, function (err, rbytes) { if (err) { return cb2(err); } bits = ((rbytes[3] &amp; 0x7f) &lt;&lt; 24) + (rbytes[2] &lt;&lt; 16) + (rbytes[1] &lt;&lt; 8) + rbytes[0]; val = bits % n; cb2(); }); }, function () { return (bits - val + (n-1)) &lt; 0; }, function (err) { if (err) { return cb(err, null); } return cb(null, val); } ); } </code></pre> <p>Did several tests, it seems to be working just fine.</p>
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    1. POGenerating cryptographc random number for modulus of powers of 10 with node.js
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    1. POGenerating cryptographc random number for modulus of powers of 10 with node.js
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    1. COI programmed the same thing for Java Card, which worked fine as well. It is important to at least create tests for the distribution of the random numbers. Note that while this is a much better solution than just directly testing for the range - but it is not *optimal* (especially regarding numbers slightly above half the maximum, for which about half the loops will fail). Then again it is probably good enough and extremely fast and simple to program.
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    2. COI did some tests on the distribution (and found a stupid bug I introduced while I rashly programmed it) and it seems to work beautifully. Indeed, the docs I found on the method estimate that the worst average case is 2 iterations. When doing tests I found it is behaving with most of the times doing only one iteration. Thank you for your feedback!
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    3. COYes, most of the time it is reliable for the first try, but if you have e.g. a single byte, value 0..255 and you request a number of 128 or slightly more, then it becomes less effective. This is normally only an issue if you have a very slow RNG, or if you need oodles of random numbers within a range (+1 of course)
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