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A

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pseudorandom

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number

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generator

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(PRNG)

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is

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a

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deterministic

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algorithm

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capable

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of

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generating

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sequences

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of

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numbers

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that

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approximate

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the

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properties

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of

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random

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numbers.

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Each

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sequence

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is

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completely

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determined

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by

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the

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initial

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state

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of

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the

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PRNG

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and

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the

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algorithm

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for

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changing

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the

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state.

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Most

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PRNGs

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make

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it

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possible

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to

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set

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the

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initial

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state,

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also called

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the

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seed

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state.

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Setting the

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initial

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state

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is

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called seeding

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the

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PRNG.

Calling a PRNG in the same initial state, either without seeding it explicitly or by seeding it with the same value, results in generating the same sequence of random numbers in different runs of the program. Suppose Consider a PRNG function that is seeded with some initial seed value and is consecutively called 10 times consecutively to produce a sequence of 10 random numbers. Suppose also that this , S. If the PRNG is not subsequently seeded . Running the code for the first time produces the sequence S = <r1, r2, r3, r4, r5, r6, r7, r8, r9, r10>. Running the code a second time produces exactly the same S sequence. Generally, any subsequent runs of the code with the same initial seed value, then it will generate the same sequence S sequence.

As a result, after the first run of the an improperly seeded PRNG, an attacker can predict the sequence of random numbers that will be generated in the future runs. Improperly seeding or failing to seed the PRNG can lead to many vulnerabilities, especially in security protocols.

The solution is to always to ensure that your the PRNG is always properly seeded. Seeding a PRNG means that it A properly seeded PRNG will generate a different sequences sequence of random numbers at any call.each time it is run.

Not It is worth noting that not all random number generators can be seeded. True random number generators that rely on hardware to produce completely unpredictable results do not need to be and cannot be seeded. Some high-quality PRNGs, such as the /dev/random device on some UNIX systems, also cannot be seeded. This rule applies only to algorithmic pseudorandom generators that make seeding possible.

MSC30-C. Do not use the rand() function for generating pseudorandom numbers addresses PRNGs from a different perspective, which is the cycle of the pseudorandom number sequence—that is, during a single run of a PRNG, the time interval after which the PRNG generates the same random numbers. MSC30-C deprecates the rand() function because it generates numbers that have a comparatively short cycle. The same rule proposes the use of the random() function for POSIX and the CryptGenRandom() function for Windows.

This rule examines, in terms of seeding, all three PRNGs mentioned in rule MSC30-C. Noncompliant code examples correspond to the use of a PRNG without a seed, while compliant solutions correspond to the same PRNG being properly seeded. This rule complies with MSC30-C and does not recommend the use of the rand() function. Nevertheless, if it is unavoidable to use rand(), it should at least be properly number generators that can be seeded.

Noncompliant Code Example (POSIX)

This noncompliant code example generates a sequence of 10 pseudorandom numbers using the randrandom() function. When randrandom() is not seeded, it uses 1 as a default seed. No matter how many times this code is executed, it always produces the same sequencebehaves like rand(), producing the same sequence of random numbers each time any program that uses it is run.

#include <stdio.h>
#include <stdlib.h>
 
void func(void) {
  for (unsigned int i = 0; i < 10; ++i) {
    printf("%d, ", rand()); /* Always generates the same sequence */
  }
}

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Noncompliant Code Example

Use srand() before rand() to seed the random sequence generated by rand(). The code produces different random number sequences at different calls.

#include <stdio.h>
#include <stdlib.h>
#include <time.h>
 
void func(void) {
  srand(time(NULL)); /* Create seed based on current time */
  for (int i = 0; i < 10; ++i) {
    printf("%dprintf("%ld, ", randrandom()); /* Generates different sequences at different runs */
  }
}

The output

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is as follows:

1st run: 

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1804289383, 

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846930886, 

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1681692777, 

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1714636915, 

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1957747793, 

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424238335, 

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719885386, 

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1649760492, 

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596516649,

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...

...

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...

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Although the rand() function is now properly seeded, this solution is still noncompliant because the numbers generated by rand() have a comparatively short cycle, and the numbers can be predictable. (See MSC30-C. Do not use the rand() function for generating pseudorandom numbers.)

Noncompliant Code Example (POSIX)

This noncompliant code example generates a sequence of 10 pseudorandom numbers using the random() function. When random() is not seeded, it behaves like rand(), producing the same sequence of random numbers at different calls.

#include <stdio.h>
#include <stdlib.h>
 
void func(void) {
  for (int i = 0; i < 10; ++i) {
    printf("%ld, ", random()); /* Always generates the same sequence */
  }
}

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1189641421,
2nd run: 1804289383, 846930886, 1681692777, 1714636915, 1957747793, 424238335, 719885386, 1649760492, 596516649

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,

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1189641421,
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nth run: 1804289383, 846930886, 1681692777, 1714636915, 1957747793, 424238335, 719885386, 1649760492, 596516649,
         1189641421,

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Compliant Solution (POSIX)

Use Call srandom() before invoking random() to seed the random sequence generated by random(). The code This compliant solution produces different random number sequences at different calls.each time the function is called, depending on the resolution of the system clock:

#include <stdio.h>
#include <stdlib.h>
#include <time.h>
 
void func(void) {
  srandom(time(NULL));struct timespec ts;
  if (timespec_get(&ts, TIME_UTC) == 0) {
    /* Create seed based on current time counted as seconds from 01/01/1970 */
  for (Handle error */
  } else {
    srandom(ts.tv_nsec ^ ts.tv_sec);
    for (unsigned int i = 0; i < 10; ++i) {
    printf("%ld, ", random()); /* Generates different sequences at different runs */
      printf("%ld, ", random());
    }
  }
}

The output

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is as follows:

1st run: 198682410, 2076262355, 910374899, 428635843, 2084827500, 1558698420, 4459146, 733695321, 2044378618, 1649046624,
2nd run: 1127071427, 252907983, 1358798372, 2101446505, 1514711759, 229790273, 954268511, 1116446419, 368192457,
         1297948050,
3rd run: 2052868434, 1645663878, 731874735, 1624006793, 938447420, 1046134947, 1901136083, 418123888, 836428296,
         2017467418,

...

This may not be sufficiently random for concurrent execution, which may lead to correlated generated series in different threadsIn the previous examples, seeding in rand() and random() is done using the time() function, which returns the current time calculated as the number of seconds that have passed since January 1, 1970. Depending on the application and the desirable desired level of security, a programmer may choose alternative ways to seed PRNGs. In general, hardware is more capable than humans software of generating real random numbers (for example, by generating a sequence of bits by sampling the thermal noise of a diode and using the result as a seed).

Compliant Solution (Windows)

CryptGenRandomThe BCryptGenRandom() function does not run the risk of not being properly seeded because its arguments serve as seeders.:

#include <stdio.h>
#include <Windows.h>
#include <wincrypt<Bcrypt.h>
#include <Ntstatus.h>
#include <stdio<Wincrypt.h>
 
void func(void) {
  HCRYPTPROV hCryptProvBCRYPT_ALG_HANDLE hAlgorithm = NULL;
  long rand_buf;
  /*PUCHAR AnpbBuffer example= of instantiating the CSP */
  if (CryptAcquireContext(&hCryptProv, NULL, NULL, PROV_RSA_FULL, 0)) {
    printf("CryptAcquireContext succeeded.\n");
  } else {
    printf("Error during CryptAcquireContext!\n");
  }

(PUCHAR) &rand_buf;
  ULONG cbBuffer = sizeof(rand_buf);
  ULONG dwFlags = BCRYPT_USE_SYSTEM_PREFERRED_RNG;
  NTSTATUS status;
  for (unsigned int i = 0; i < 10; ++i) {
    ifstatus = (!CryptGenRandom(hCryptProv, sizeof(rand_buf), (BYTE *)&rand_buf))BCryptGenRandom(hAlgorithm, pbBuffer, cbBuffer, dwFlags);
    if (status == STATUS_SUCCESS) {
      printf("Error\n"%ld, ", rand_buf);
    } else {
       printf("%ld, ", rand_buf.li);/* Handle Error */
    }
  }
}

The output

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is as follows:

1st run: -

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683378946, 

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1957231690, 

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1933176011, 

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-1745403355, -

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883473417, 

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882992405, 

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169629816, 

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1824800038, 

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899851668, 

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1702784647, 
2nd run: 

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-58750553, -

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1921870721, -

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1973269161, 

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1512649964, -

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673518452, 

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234003619, -

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1622633366, 1312389688, -

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2125631172, 

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2067680022, 

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3rd run: 

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-189899579, 

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1220698973, 

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752205360, -

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1826365616, 

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79310867, 

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1430950090, 

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-283206168, -

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941773185, 

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129633665, 

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543448789, 

Risk Assessment

Automated Detection

Related Vulnerabilities

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

Related Guidelines

Key here (explains table format and definitions)

CERT-CWE Mapping Notes

Key here for mapping notes

CWE-327 and MSC32-C

• Intersection( MSC30-C, MSC32-C) = Ø

• MSC32-C says to properly seed pseudorandom number generators. For example, if you call rand(), make sure to seed it properly by calling srand() first. So far, we haven’t found any calls to rand().

• Failure to seed a

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• PRNG causes it to produce reproducible (hence insecure) series of random numbers.

• CWE-327 = Union( MSC32-C, list) where list =

• Invocation of broken/risky crypto algorithms that are not properly seeded

CWE-330

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and MSC32-C

Independent( MSC30-C, MSC32-C, CON33-C)

CWE-330 = Union( MSC30-C, MSC32-C, CON33-C, list) where list = other improper use or creation of random values. (EG the would qualify)

MSC30-C, MSC32-C and CON33-C are independent, they have no intersections. They each specify distinct errors regarding PRNGs.

Bibliography

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