CWE-341 Detail

CWE-341

Name

Predictable from Observable State

Status

Draft

Published

2006-07-19
00h00 +00:00

Modified

2023-06-29
00h00 +00:00

Official links

CWE Mitre.org

Notifications for a CWE

Stay informed of any changes for a specific CWE.

Notifications manage

List of Notifications

Notifications for a CWE

Stay informed of any changes for a specific CWE.

Parameters

You can specify a title that will be retrieved in the alerts that will be sent out.

Specify the CWE ID you wish to monitor.

Planning

Month

Next run calculation

Day

Weekday

Hour

Minute

Creation date

Last execution

Next execution

Functionality requiring a connection

This feature, which allows you to receive alerts, is only active when you are logged into your account.

Name: 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.

General Informations

Modes Of Introduction

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

Applicable Platforms

Language

Class: Not Language-Specific (Undetermined)

Common Consequences

Scope	Impact	Likelihood
Other	Varies by Context Note: This weakness could be exploited by an attacker in a number 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.

Observed Examples

References	Description
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.

Potential Mitigations

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.

Vulnerability Mapping Notes

Justification : 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.
Comment : 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.

NotesNotes

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.

References

REF-267

SECURITY REQUIREMENTS FOR CRYPTOGRAPHIC MODULES
Information Technology Laboratory, National Institute of Standards and Technology.
https://csrc.nist.gov/csrc/media/publications/fips/140/2/final/documents/fips1402.pdf

REF-44

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

Submission

Name	Organization	Date	Date release	Version
PLOVER		2006-07-19 +00:00	2006-07-19 +00:00	Draft 3

Modifications

Name	Organization	Date	Comment
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