CWE-335 Details

CWE-335

Incorrect Usage of Seeds in Pseudo-Random Number Generator (PRNG)
Draft
2006-07-19
00h00 +00:00
2025-12-11
00h00 +00:00
CWE Mitre.org
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Name: Incorrect Usage of Seeds in Pseudo-Random Number Generator (PRNG)

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

Allgemeine Informationen

Einführungsmodi

Implementation : REALIZATION: This weakness is caused during implementation of an architectural security tactic.

Anwendbare Plattformen

Sprache

Class: Not Language-Specific (Undetermined)

Häufige Konsequenzen

Bereich Auswirkung Wahrscheinlichkeit
Access Control
Other		Bypass Protection Mechanism, Other

Note: 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 authorization.

Beobachtete Beispiele

Referenzen Beschreibung

CVE-2020-7010

Cloud application on Kubernetes generates passwords using a weak random number generator based on deployment time.

CVE-2019-11495

server uses erlang:now() to seed the PRNG, which results in a small search space for potential random seeds

CVE-2018-12520

Product's PRNG is not seeded for the generation of session IDs

CVE-2016-10180

Router's PIN generation is based on rand(time(0)) seeding.

Erkennungsmethoden

Automated Static Analysis

Automated static analysis, commonly referred to as Static Application Security Testing (SAST), can find some instances of this weakness by analyzing source code (or binary/compiled code) without having to execute it. Typically, this is done by building a model of data flow and control flow, then searching for potentially-vulnerable patterns that connect "sources" (origins of input) with "sinks" (destinations where the data interacts with external components, a lower layer such as the OS, etc.)

Hinweise zur Schwachstellen-Zuordnung

Begründung : This CWE entry is at the Base level of abstraction, which is a preferred level of abstraction for mapping to the root causes of vulnerabilities.
Kommentar : Carefully read both the name and description to ensure that this mapping is an appropriate fit. Do not try to 'force' a mapping to a lower-level Base/Variant simply to comply with this preferred level of abstraction.

Hinweise

As of CWE 4.5, terminology related to randomness, entropy, and predictability can vary widely. Within the developer and other communities, "randomness" is used heavily. However, within cryptography, "entropy" is distinct, typically implied as a measurement. There are no commonly-used definitions, even within standards documents and cryptography papers. Future versions of CWE will attempt to define these terms and, if necessary, distinguish between them in ways that are appropriate for different communities but do not reduce the usability of CWE for mapping, understanding, or other scenarios.

Referenzen

REF-44

24 Deadly Sins of Software Security
Michael Howard, David LeBlanc, John Viega.

Einreichung

Name Organisation Datum Veröffentlichungsdatum Version
PLOVER 2006-07-19 +00:00 2006-07-19 +00:00 Draft 3

Änderungen

Name Organisation Datum Kommentar
Eric Dalci Cigital 2008-07-01 +00:00 updated Time_of_Introduction
CWE Content Team MITRE 2008-09-08 +00:00 updated Relationships, Taxonomy_Mappings
CWE Content Team MITRE 2011-06-01 +00:00 updated Common_Consequences
CWE Content Team MITRE 2012-05-11 +00:00 updated Common_Consequences, References, Relationships
CWE Content Team MITRE 2017-11-08 +00:00 updated Applicable_Platforms, Description, Modes_of_Introduction, Name, Relationships, Type
CWE Content Team MITRE 2019-06-20 +00:00 updated Relationships
CWE Content Team MITRE 2020-02-24 +00:00 updated Relationships
CWE Content Team MITRE 2021-07-20 +00:00 updated Description, Maintenance_Notes, Observed_Examples
CWE Content Team MITRE 2021-10-28 +00:00 updated Relationships
CWE Content Team MITRE 2022-10-13 +00:00 updated Observed_Examples
CWE Content Team MITRE 2023-01-31 +00:00 updated Description
CWE Content Team MITRE 2023-04-27 +00:00 updated Relationships, Time_of_Introduction
CWE Content Team MITRE 2023-06-29 +00:00 updated Mapping_Notes
CWE Content Team MITRE 2023-10-26 +00:00 updated Demonstrative_Examples
CWE Content Team MITRE 2025-12-11 +00:00 updated Detection_Factors, Relationships, Weakness_Ordinalities
Die auf CVE Find präsentierten Informationen stammen aus mehreren sorgfältig ausgewählten Referenzquellen. CVE-Daten werden von der MITRE Corporation und der National Vulnerability Database (NVD) bereitgestellt. Der Katalog bekannter ausgenutzter Schwachstellen (KEV) stammt von der Cybersecurity and Infrastructure Security Agency (CISA), während EPSS-Scores von FIRST.org kommen. Darüber hinaus werden Daten zu Software-Schwachstellen (CWE) und häufigen Angriffsmustern (CAPEC) von der MITRE Corporation gepflegt, und Informationen zu Hardware- und Software-Konfigurationen (CPE) werden von der NVD bereitgestellt.