CWE-341 详情

CWE-341

Predictable from Observable State
2006-07-19
00h00 +00:00
Draft
2026-10-28
00h00 +00:00
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随时了解指定 CWE 的变更。
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名称: Predictable from Observable State

A number or object is predictable based on observations that the attacker can make about the state of the system or network, such as time, process ID, etc.

基本信息

引入方式

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

适用平台

编程语言

类: Not Language-Specific (Undetermined)

常见后果

影响范围 影响 可能性
OtherVaries by Context

注意: This weakness could be exploited by an attacker in a number of ways depending on the context. If a predictable number is used to generate IDs or keys that are used within protection mechanisms, then an attacker could gain unauthorized access to the system. If predictable filenames are used for storing sensitive information, then an attacker might gain access to the system and may be able to gain access to the information in the file.

观察示例

参考资料 描述

CVE-2024-48445

Chain: e-commerce app relies on an easily-guessable timestamp (CWE-341) in a weak authentication algorithm (CWE-1390)

CVE-2002-0389

Mail server stores private mail messages with predictable filenames in a world-executable directory, which allows local users to read private mailing list archives.

CVE-2001-1141

PRNG allows attackers to use the output of small PRNG requests to determine the internal state information, which could be used by attackers to predict future pseudo-random numbers.

CVE-2000-0335

DNS resolver library uses predictable IDs, which allows a local attacker to spoof DNS query results.

CVE-2005-1636

MFV. predictable filename and insecure permissions allows file modification to execute SQL queries.

潜在缓解措施

Phases : Implementation
Increase the entropy used to seed a PRNG.
Phases : Architecture and Design // Requirements
Use products or modules that conform to FIPS 140-2 [REF-267] to avoid obvious entropy problems. Consult FIPS 140-2 Annex C ("Approved Random Number Generators").
Phases : Implementation
Use a PRNG that periodically re-seeds itself using input from high-quality sources, such as hardware devices with high entropy. However, do not re-seed too frequently, or else the entropy source might block.

检测方法

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.)

漏洞映射说明

依据 : 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.
备注 : 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.

备注

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.

参考资料

REF-267

FIPS PUB 140-2: SECURITY REQUIREMENTS FOR CRYPTOGRAPHIC MODULES
Information Technology Laboratory, National Institute of Standards and Technology.
https://csrc.nist.gov/files/pubs/fips/140-2/upd2/final/docs/fips1402.pdf

REF-44

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

提交记录

名称 组织 日期 发布日期 Version
PLOVER 2006-07-19 +00:00 2006-07-19 +00:00 Draft 3

修改记录

名称 组织 日期 备注
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 2009-03-10 +00:00 updated Potential_Mitigations
CWE Content Team MITRE 2009-12-28 +00:00 updated Potential_Mitigations
CWE Content Team MITRE 2010-06-21 +00:00 updated Potential_Mitigations
CWE Content Team MITRE 2011-06-01 +00:00 updated Common_Consequences
CWE Content Team MITRE 2011-06-27 +00:00 updated Common_Consequences
CWE Content Team MITRE 2011-09-13 +00:00 updated Potential_Mitigations, References
CWE Content Team MITRE 2012-05-11 +00:00 updated Common_Consequences, Demonstrative_Examples, Observed_Examples, References, Relationships
CWE Content Team MITRE 2012-10-30 +00:00 updated Potential_Mitigations
CWE Content Team MITRE 2017-11-08 +00:00 updated Applicable_Platforms, Modes_of_Introduction, References, Relationships
CWE Content Team MITRE 2020-02-24 +00:00 updated Relationships
CWE Content Team MITRE 2021-07-20 +00:00 updated Maintenance_Notes
CWE Content Team MITRE 2023-04-27 +00:00 updated References, Relationships
CWE Content Team MITRE 2023-06-29 +00:00 updated Mapping_Notes, Relationships
CWE Content Team MITRE 2025-09-09 +00:00 updated References
CWE Content Team MITRE 2025-12-11 +00:00 updated Detection_Factors, Observed_Examples, Weakness_Ordinalities
CWE Content Team MITRE 2026-10-28 +00:00 updated Common_Consequences