CWE

Predictable Value Range from Previous Values

ID: 343		Date: (C)2012-05-14   (M)2022-10-10
Type: weakness		Status: DRAFT
Abstraction Type: Base

Description

The software's random number generator produces a series of values which, when observed, can be used to infer a relatively small range of possibilities for the next value that could be generated.

Extended Description

The output of a random number generator should not be predictable based on observations of previous values. In some cases, an attacker cannot predict the exact value that will be produced next, but can narrow down the possibilities significantly. This reduces the amount of effort to perform a brute force attack. For example, suppose the product generates random numbers between 1 and 100, but it always produces a larger value until it reaches 100. If the generator produces an 80, then the attacker knows that the next value will be somewhere between 81 and 100. Instead of 100 possibilities, the attacker only needs to consider 20.

Applicable Platforms
Language Class: All

Time Of Introduction

• Architecture and Design
• Implementation

Common Consequences

Scope	Technical Impact	Notes
Other	Varies by context

Detection Methods
None

Potential Mitigations

Phase	Strategy	Description	Effectiveness	Notes
		Increase the entropy used to seed a PRNG.
Architecture and Design Requirements	Libraries or Frameworks	Use products or modules that conform to FIPS 140-2 [R.343.1] to avoid obvious entropy problems. Consult FIPS 140-2 Annex C ("Approved Random Number Generators").
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.

Relationships

Related CWE	Type	View	Chain
CWE-343 ChildOf CWE-905	Category	CWE-888

Demonstrative Examples
None

White Box Definitions
None

Black Box Definitions
None

Taxynomy Mappings

Taxynomy	Id	Name	Fit
PLOVER		Predictable Value Range from Previous Values

References:

1. Information Technology Laboratory, National Institute of Standards and Technology .SECURITY REQUIREMENTS FOR CRYPTOGRAPHIC MODULES. 2001-05-25.
2. Michal Zalewski .Strange Attractors and TCP/IP Sequence Number Analysis. Published on 2001.
3. Michael Howard David LeBlanc John Viega .24 Deadly Sins of Software Security. McGraw-Hill. Section:'"Sin 20: Weak Random Numbers." Page 299'. Published on 2010.