Same Seed in Pseudo-Random Number Generator (PRNG)
A Pseudo-Random Number Generator (PRNG) uses the same seed each time the product is initialized.
If an attacker can guess (or knows) the seed, then the attacker may be able to determine the random numbers that will be produced from 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.
The following code uses a statistical PRNG to generate account IDs.
Because the program uses the same seed value for every invocation of the PRNG, its values are predictable, making the system vulnerable to attack.
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.