A Pseudo-Random Number Generator (PRNG) is initialized from a predictable seed, such as the process ID or system time.
The use of predictable seeds significantly reduces the number of possible seeds that an attacker would need to test in order to predict which random numnbers will be generated by the PRNG.
The table(s) below shows the weaknesses and high level categories that are related to this weakness. These relationships are defined as ChildOf, ParentOf, MemberOf and give insight to similar items that may exist at higher and lower levels of abstraction. In addition, relationships such as PeerOf and CanAlsoBe are defined to show similar weaknesses that the user may want to explore.
Relevant to the view "Research Concepts" (CWE-1000)
Relevant to the view "Architectural Concepts" (CWE-1008)
Relevant to the view "Development Concepts" (CWE-699)
The different Modes of Introduction provide information about how and when this weakness may be introduced. The Phase identifies a point in the software life cycle at which introduction may occur, while the Note provides a typical scenario related to introduction during the given phase.
The listings below show possible areas for which the given weakness could appear. These may be for specific named Languages, Operating Systems, Architectures, Paradigms, Technologies, or a class of such platforms. The platform is listed along with how frequently the given weakness appears for that instance.
Class: Language-Independent (Undetermined Prevalence)
The table below specifies different individual consequences associated with the weakness. The Scope identifies the application security area that is violated, while the Impact describes the negative technical impact that arises if an adversary succeeds in exploiting this weakness. The Likelihood provides information about how likely the specific consequence is expected to be seen relative to the other consequences in the list. For example, there may be high likelihood that a weakness will be exploited to achieve a certain impact, but a low likelihood that it will be exploited to achieve a different impact.
Both of these examples use a statistical PRNG seeded with the current value of the system clock to generate a random number:
Example Language: Java
Random random = new Random(System.currentTimeMillis());
int accountID = random.nextInt();
Example Language: C
int randNum = rand();
An attacker can easily predict the seed used by these PRNGs, and so also predict the stream of random numbers generated. Note these examples also exhibit CWE-338 (Use of Cryptographically Weak PRNG).
This MemberOf Relationships table shows additional CWE Categories and Views that reference this weakness as a member. This information is often useful in understanding where a weakness fits within the context of external information sources.
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