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This question isn't really a problem looking for a solution, it's more just a matter of simple curiosity. The PHP uniqid function has a more entropy flag, to make the output "more unique". This got me wondering, just how likely is it for this function to produce the same result more than once when more_entropy is true, versus when it isn't. In other words, how unique is uniqid when more_entropy is enabled, versus when it is disabled? Are there any drawbacks to having more_entropy enabled all the time?

 Answers

4

Update, March 2014:

Firstly, it is important to note that uniqid is a bit of a misnomer as it doesnt guarantee a unique ID.

Per the PHP documentation:

WARNING!

This function does not create random nor unpredictable string. This function must not be used for security purposes. Use cryptographically secure random function/generator and cryptographically secure hash functions to create unpredictable secure ID.

And

This function does not generate cryptographically secure tokens, in fact without being passed any additional parameters the return value is little different from microtime(). If you need to generate cryptographically secure tokens use openssl_random_pseudo_bytes().


Setting more-entropy to true generates a more unique value, however the execution time is longer (though to a tiny degree), according to the docs:

If set to TRUE, uniqid() will add additional entropy (using the combined linear congruential generator) at the end of the return value, which increases the likelihood that the result will be unique.

Note the line increases the likelihood that the result will be unique and not that is will guarantee uniqueness.

You can 'endlessly' strive for uniqueness, up to a point, and enhance using any number of encryption routines, adding salts and the like- it depends on the purpose.

I'd recommend looking at the comments on the main PHP topic, notably:

http://www.php.net/manual/en/function.uniqid.php#96898

http://www.php.net/manual/en/function.uniqid.php#96549

http://www.php.net/manual/en/function.uniqid.php#95001

What I'd recommend is working out why you need uniqueness, is it for security (i.e. to add to an encryption/scrambling routine)? Also, How unique does it need to be? Finally, look at the speed consideration. Suitability will change with the underlying considerations.

Monday, November 7, 2022
5

Here's what worked best for me when trying to script this (in case anyone else comes across this like I did):

$ pecl -d php_suffix=5.6 install <package>
$ pecl uninstall -r <package>

$ pecl -d php_suffix=7.0 install <package>
$ pecl uninstall -r <package>

$ pecl -d php_suffix=7.1 install <package>
$ pecl uninstall -r <package>

The -d php_suffix=<version> piece allows you to set config values at run time vs pre-setting them with pecl config-set. The uninstall -r bit does not actually uninstall it (from the docs):

vagrant@homestead:~$ pecl help uninstall
pecl uninstall [options] [channel/]<package> ...
Uninstalls one or more PEAR packages.  More than one package may be
specified at once.  Prefix with channel name to uninstall from a
channel not in your default channel (pecl.php.net)

Options:
  ...
  -r, --register-only
        do not remove files, only register the packages as not installed
  ...

The uninstall line is necessary otherwise installing it will remove any previously installed version, even if it was for a different PHP version (ex: Installing an extension for PHP 7.0 would remove the 5.6 version if the package was still registered as installed).

Monday, December 12, 2022
2

Very safe:

the annual risk of a given person being hit by a meteorite is estimated to be one chance in 17 billion, which means the probability is about 0.00000000006 (6 × 10?11), equivalent to the odds of creating a few tens of trillions of UUIDs in a year and having one duplicate. In other words, only after generating 1 billion UUIDs every second for the next 100 years, the probability of creating just one duplicate would be about 50%.

Caveat:

However, these probabilities only hold when the UUIDs are generated using sufficient entropy. Otherwise, the probability of duplicates could be significantly higher, since the statistical dispersion might be lower. Where unique identifiers are required for distributed applications, so that UUIDs do not clash even when data from many devices is merged, the randomness of the seeds and generators used on every device must be reliable for the life of the application. Where this is not feasible, RFC4122 recommends using a namespace variant instead.

Source: The Random UUID probability of duplicates section of the Wikipedia article on Universally unique identifiers (link leads to a revision from December 2016 before editing reworked the section).

Also see the current section on the same subject on the same Universally unique identifier article, Collisions.

Tuesday, September 20, 2022
 
alt-cat
 
3

As others have pointed out, uniqueness is not guaranteed. However you are probably seeing repeated numbers because you are using srand() and rand() incorrectly.

srand() is used to seed the random number generator. that means a series of calls to rand() after a call to srand will produce a particular series of values. If you call srand() with the same value then rand() will produce the same series of values (for a given implementation, there's no guarantee between different implementations)

int main() {
    srand(100);
    for(int i = 0; i<5; ++i)
        printf("%dn",rand());

    printf("nresetnn");

    srand(100);
    for(int i = 0; i<5; ++i)
        printf("%dn",rand());

}

for me this produces:

365
1216
5415
16704
24504

reset

365
1216
5415
16704
24504

time() and clock() return the time, but if you call them quickly enough then the value returned will be the same, so you will get the same series of values out of rand().

Additionally rand() is generally not a very good random number generator and using it usually means you have to transform the series of numbers to the distribution you actually need. You should find a different source of randomness and either learn the proper ways to produce the distribution you want or use a library that can do it for you. (for example one common method of producing a 'random' number between 0 and N is to do rand() % N but this is not really the best method.

C++ provides a much better random number library in <random>. It provides different PRNG algorithms, such as linear_congruential, mersennne_twister, and possibly even a cryptographically secure RNG (depending on the implementation). It also provides objects for producing a variety of distributions, such as uniform_int_distribution which should avoid the mistake make in rand() % N.

Monday, August 1, 2022
 
marijne
 
4

Never used any of those, but they look interesting..

Take a look at Gearman as well.. more overhead in systems like these but you get other cool stuff :) Guess it depends on your needs ..

Friday, November 11, 2022
 
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