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It is widely known John von Neumann's quote:

 "Anyone who considers arithmetical methods of producing random digits is, of course, in a state of sin."

Pseudorandom number generators (PRNGs) use deterministic mathematical algorithms  to produce a sequence of numbers with good statistical properties, but the numbers produced are not genuinely random. PRNGs usually start with an arithmetic seed value. The algorithm uses this seed in order to generate an output value and a new seed as well which is going to be used to generate the next value and so on.

The Java API provides a PRNG, the java.util.Random class. This PRNG built is portable and repeatable. As a consequence of that, if two Random instances are created using the same seed, they will generate identical sequences of numbers in all Java implementations.

Noncompliant Code Example

In case you use the same seed value, you will always get the same sequence of numbers, thus they will not be so "random" ones.

import java.util.Random;
// ...

Random number = new Random(123L);
//...
for (int i=0; i<20; i++)
{
   // generate another random integer in the range [0,20]
   int n = number.nextInt(21);
   System.out.println(n);
}

Noncompliant Code Example

 Using a null seed value may prevent such problems. Java's default seed uses system's time in milliseconds. However, you should neither use two different generators with a null seed value nor "resetting" generator's instance more than once (using new Random() multiple times) as you may get identical numbers in the former case and number not actually random in the latter one.

import java.util.Random;
// ...

Random number = new Random();
//...
for (int i=0; i<20; i++)
{
   // re-seed generator
   number = new Random();
   // generate another random integer in the range [0,20]
   int n = number.nextInt(21);
   System.out.println(n);
}

For non-critical cases, e.g. adding some randomness to a game, Random class is considered fine. However, it is not random enough to be used by more serious applications, e.g. cryptography.

Compliant Solution

This compliant solution uses java.security.SecureRandom class in order to produce high quality random numbers.

import java.security.SecureRandom;
// ...

static SecureRandom number = SecureRandom.getInstance ("SHA-1");
// ...
// generate 20 integers 0..20
for (int i=0; i<20; i++)
{
  System.out.println(number.nextInt(21));
}

Risk Assessment

Automated Detection

TODO

Related Vulnerabilities

Search for vulnerabilities resulting from the violation of this rule on the CERT website.

Other Languages

This rule appears in the C++ Secure Coding Standard as MSC30-C. Do not use the rand() function for generating pseudorandom numbers.

References

\[[API 06|https://www.securecoding.cert.org/confluence/display/java/AA.+Java+References#AA.JavaReferences-API06]\] [Class Random|http://java.sun.com/javase/6/docs/api/java/util/Random.html]

\[[API 06|https://www.securecoding.cert.org/confluence/display/java/AA.+Java+References#AA.JavaReferences-API06]\] [Class SecureRandom|http://java.sun.com/javase/6/docs/api/java/security/SecureRandom.html]

\[[Find Bugs 08|https://www.securecoding.cert.org/confluence/display/java/AA.+Java+References#AA.JavaReferences-FindBugs08]\] BC: Random objects created and uses only once