Incorrect Usage of Seeds in Pseudo-Random Number Generator (PRNG)

The software uses a Pseudo-Random Number Generator (PRNG) but does not correctly manage seeds.


Description

PRNGs are deterministic and, while their output appears random, they cannot actually create entropy. They rely on cryptographically secure and unique seeds for entropy so proper seeding is critical to the secure operation of the PRNG.

Management of seeds could be broken down into two main areas:

(1) protecting seeds as cryptographic material (such as a cryptographic key);

(2) whenever possible, using a uniquely generated seed from a cryptographically secure source

PRNGs require a seed as input to generate a stream of numbers that are functionally indistinguishable from random numbers. While the output is, in many cases, sufficient for cryptographic uses, the output of any PRNG is directly determined by the seed provided as input. If the seed can be ascertained by a third party, the entire output of the PRNG can be made known to them. As such, the seed should be kept secret and should ideally not be able to be guessed. For example, the current time may be a poor seed. Knowing the approximate time the PRNG was seeded greatly reduces the possible key space.

Seeds do not necessarily need to be unique, but reusing seeds may open up attacks if the seed is discovered.

See Also

Random Number Issues

Weaknesses in this category are related to a software system's random number generation.

Encrypt Data

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....

SFP Primary Cluster: Predictability

This category identifies Software Fault Patterns (SFPs) within the Predictability cluster.

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