MSC30-J. Generate truly random numbers

John von Neumann's quote is widely known:

 "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 used to generate the next value, and so on.

The Java API provides a PRNG, the java.util.Random class. This PRNG 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

If you use the same seed value, you will always get the same sequence of numbers; thus they will not be "random."

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);
}

There are cases of course, where the same sequence of random numbers is desirable, such as regression tests of program behavior. Otherwise, generating the same sequence of random numbers may cause a vulnerability.

Compliant Solution

Using a null seed value may prevent such problems. Java's default seed uses the system's time in milliseconds.

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

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

For noncritical cases, such as adding some randomness to a game, the Random class is considered fine. However, it is not random enough to be used by more serious applications, such as cryptography.

Compliant Solution

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

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

public static void main (String args[])
{
   try
   {
      SecureRandom number = SecureRandom.getInstance ("SHA1PRNG");
      // ...
      // generate 20 integers 0..20
      for (int i=0; i<20; i++)
      {
         System.out.println(number.nextInt(21));
      }
   }
   catch (NoSuchAlgorithmException nsae) {}
}

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.

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

References

[API 06] Class Random
[API 06] Class SecureRandom
[Find Bugs 08] BC: Random objects created and used only once
[[MITRE 09]] CWE ID 327 , "Use of a Broken or Risky Cryptographic Algorithm," CWE ID 330, "Use of Insufficiently Random Values", CWE ID 333 "Failure to Handle Insufficient Entropy in TRNG", CWE ID 332 "Insufficient Entropy in PRNG", CWE ID 337 "Predictable Seed in PRNG", CWE ID 336 "Same Seed in PRNG"

MSC05-J. Make sensitive classes noncloneable      11. Miscellaneous (MSC)      99. The Void (VOID)