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CWE-335 (PRNG种子错误) — Vulnerability Class 13

13 vulnerabilities classified as CWE-335 (PRNG种子错误). AI Chinese analysis included.

CWE-335 represents a critical implementation flaw where developers fail to properly initialize or manage the seeds for a Pseudo-Random Number Generator. Because PRNGs are deterministic algorithms that merely simulate randomness, their security relies entirely on the unpredictability of their starting state. Attackers typically exploit this weakness by predicting the generator’s output sequence if the seed is derived from predictable sources, such as system time or process identifiers. This predictability allows adversaries to bypass security controls, forge session tokens, or crack encryption keys that depend on these flawed random values. To mitigate this risk, developers must ensure that PRNGs are seeded with high-entropy data from cryptographically secure sources, such as operating system-provided random number generators, rather than using easily guessable or static values that compromise the integrity of the entire cryptographic system.

MITRE CWE Description
The product uses a Pseudo-Random Number Generator (PRNG) but does not correctly manage seeds. 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.
Common Consequences (1)
Access Control, OtherBypass Protection Mechanism, Other
If a PRNG is used incorrectly, such as using the same seed for each initialization or using a predictable seed, then an attacker may be able to easily guess the seed and thus the random numbers. This could lead to unauthorized access to a system if the seed is used for authentication and authorizati…
Examples (2)
The following code uses a statistical PRNG to generate account IDs.
private static final long SEED = 1234567890; public int generateAccountID() { Random random = new Random(SEED); return random.nextInt(); }
Bad · Java
Both of these examples use a statistical PRNG seeded with the current value of the system clock to generate a random number:
Random random = new Random(System.currentTimeMillis()); int accountID = random.nextInt();
Bad · Java
srand(time()); int randNum = rand();
Bad · C

Vulnerabilities classified as CWE-335 (PRNG种子错误) represent 13 CVEs. The CWE taxonomy describes the weakness; review individual CVEs for product-specific impact.