- * pseudo-random number generator (PRNG). It uses the Mersenne Twister
- * PRNG, which was originally developed by Makoto Matsumoto and Takuji
- * Nishimura. Further information can be found at
- * <ulink url="http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/emt.html">
- * http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/emt.html</ulink>.
- *
- * If you just need a random number, you simply call the
- * <function>g_random_*</function> functions, which will create a
- * globally used #GRand and use the according
- * <function>g_rand_*</function> functions internally. Whenever you
- * need a stream of reproducible random numbers, you better create a
- * #GRand yourself and use the <function>g_rand_*</function> functions
- * directly, which will also be slightly faster. Initializing a #GRand
- * with a certain seed will produce exactly the same series of random
- * numbers on all platforms. This can thus be used as a seed for e.g.
- * games.
- *
- * The <function>g_rand*_range</function> functions will return high
- * quality equally distributed random numbers, whereas for example the
- * <literal>(g_random_int()%max)</literal> approach often
+ * pseudo-random number generator (PRNG).
+ *
+ * Do not use this API for cryptographic purposes such as key
+ * generation, nonces, salts or one-time pads.
+ *
+ * This PRNG is suitable for non-cryptographic use such as in games
+ * (shuffling a card deck, generating levels), generating data for
+ * a test suite, etc. If you need random data for cryptographic
+ * purposes, it is recommended to use platform-specific APIs such
+ * as `/dev/random` on UNIX, or CryptGenRandom() on Windows.
+ *
+ * GRand uses the Mersenne Twister PRNG, which was originally
+ * developed by Makoto Matsumoto and Takuji Nishimura. Further
+ * information can be found at
+ * [this page](http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/emt.html).
+ *
+ * If you just need a random number, you simply call the g_random_*
+ * functions, which will create a globally used #GRand and use the
+ * according g_rand_* functions internally. Whenever you need a
+ * stream of reproducible random numbers, you better create a
+ * #GRand yourself and use the g_rand_* functions directly, which
+ * will also be slightly faster. Initializing a #GRand with a
+ * certain seed will produce exactly the same series of random
+ * numbers on all platforms. This can thus be used as a seed for
+ * e.g. games.
+ *
+ * The g_rand*_range functions will return high quality equally
+ * distributed random numbers, whereas for example the
+ * `(g_random_int()%max)` approach often