CWE-335 (PRNG种子错误) — Vulnerability Class 17

17 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, Other Bypass 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

CVE ID	Title	CVSS	Severity	Published
CVE-2026-118765	Botan: AutoSeeded_RNG can become reinitialized from predictable data after clearing state — botan	7.3	High	2026-10-29
CVE-2026-11730	Insufficient session randomness vulnerability exists in certain NETGEAR EX Series Models — EX3700	5.4	Medium	2026-10-13
CVE-2026-11702	Bytes::Random::Secure::Tiny versions through 1.011 for Perl share internal state across forked processes — Bytes::Random::Secure::Tiny	-	-	2026-06-26
CVE-2026-11625	Bytes::Random::Secure versions through 0.29 for Perl share internal state across forked processes — Bytes::Random::Secure	-	-	2026-06-26
CVE-2026-41564	CryptX versions before 0.088 for Perl do not reseed the Crypt::PK PRNG state after forking — CryptX	9.1^AI	Critical ^AI	2026-04-23
CVE-2026-3503	Fault injection attack with ML-DSA and ML-KEM on ARM — wolfSSL (wolfCrypt)	6.1	-	2026-03-19
CVE-2025-52578	Gallagher HBUS Devices 安全漏洞 — High Sec End of Line Module	5.7	Medium	2025-11-18
CVE-2025-27580	NIH BRICS 安全漏洞 — BRICS	7.5	High	2025-04-23
CVE-2025-24783	Apache Cocoon: continuations may not be private — Apache Cocoon	5.3	-	2025-01-27
CVE-2024-55566	ColPack 安全漏洞 — n/a	6.6	Medium	2024-12-09
CVE-2024-1579	Insufficient seeding of random number generator — GateManager	8.1	High	2024-04-29
CVE-2023-4472	Cryptographically weak PRNG in Opinio 7.22 — Opinio	9.8	-	2024-02-01
CVE-2022-39218	Random number seed fixed during compilation — js-compute-runtime	7.5	High	2022-09-20
CVE-2016-3735	Piwigo 安全漏洞 — Piwigo	8.1	-	2022-01-28
CVE-2021-34600	Telenot complex: Insecure AES Key Generation — CompasX	5.5	Medium	2022-01-20
CVE-2021-41117	Insecure random number generation — keypair	8.7	High	2021-10-11
CVE-2020-7010	Elastic Cloud on Kubernetes 安全漏洞 — Elastic Cloud on Kubernetes	7.5	-	2020-06-03

Vulnerabilities classified as CWE-335 (PRNG种子错误) represent 17 CVEs. The CWE taxonomy describes the weakness; review individual CVEs for product-specific impact.