Predictable Seed in Pseudo-Random Number Generator (PRNG)
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 numbers will be generated by the PRNG.
The following examples help to illustrate the nature of this weakness and describe methods or techniques which can be used to mitigate the risk.
Note that the examples here are by no means exhaustive and any given weakness may have many subtle varieties, each of which may require different detection methods or runtime controls.
Both of these examples use a statistical PRNG seeded with the current value of the system clock to generate a random number:
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).
Weaknesses in this category are related to the rules and recommendations in the Miscellaneous (MSC) section of the SEI CERT Oracle Secure Coding Standard for Java.
Weaknesses in this category are related to the design and architecture of data confidentiality in a system. Frequently these deal with the use of encryption libraries....
This category identifies Software Fault Patterns (SFPs) within the Predictability cluster.
This view (slice) covers all the elements in CWE.
CWE identifiers in this view are weaknesses that do not have associated Software Fault Patterns (SFPs), as covered by the CWE-888 view. As such, they represent gaps in...
This view (slice) lists weaknesses that can be introduced during implementation.