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Insufficient Entropy

Draft Base
Structure: Simple
Description

This vulnerability occurs when a system's random number generator or algorithm lacks sufficient unpredictability, creating patterns or predictable outputs that are easier for attackers to guess.

Extended Description

Insufficient entropy means your random values aren't random enough. This often stems from using weak algorithms (like `rand()`), seeding generators with predictable values (like the current time), or drawing from a source with limited possible outcomes. Attackers can exploit these patterns to predict security-critical values like session tokens, cryptographic keys, or password reset codes, effectively bypassing protections that rely on randomness. To prevent this, developers should use cryptographically secure pseudorandom number generators (CSPRNGs) provided by the operating system or language's security libraries. Always ensure your entropy source is robust and unpredictable, especially for initialization vectors, nonces, and key generation. For high-stakes systems, consider using hardware random number generators or dedicated security services to guarantee the quality of your randomness.
Common Consequences 1
Scope: Access ControlOther

Impact: Bypass Protection MechanismOther

An attacker could guess the random numbers generated and could gain unauthorized access to a system if the random numbers are used for authentication and authorization.
Potential Mitigations 1
Phase: Implementation
Determine the necessary entropy to adequately provide for randomness and predictability. This can be achieved by increasing the number of bits of objects such as keys and seeds.
Demonstrative Examples 2

ID : DX-45

This code generates a unique random identifier for a user's session.

Code Example:

Bad
PHP
php
Because the seed for the PRNG is always the user's ID, the session ID will always be the same. An attacker could thus predict any user's session ID and potentially hijack the session.
This example also exhibits a Small Seed Space (Small Seed Space in PRNG).

ID : DX-46

The following code uses a statistical PRNG to create a URL for a receipt that remains active for some period of time after a purchase.

Code Example:

Bad
Java
java
This code uses the Random.nextInt() function to generate "unique" identifiers for the receipt pages it generates. Because Random.nextInt() is a statistical PRNG, it is easy for an attacker to guess the strings it generates. Although the underlying design of the receipt system is also faulty, it would be more secure if it used a random number generator that did not produce predictable receipt identifiers, such as a cryptographic PRNG.
Observed Examples 2
CVE-2001-0950Insufficiently random data used to generate session tokens using C rand(). Also, for certificate/key generation, uses a source that does not block when entropy is low.
CVE-2008-2108Chain: insufficient precision (Insufficient Precision or Accuracy of a Real Number) in random-number generator causes some zero bits to be reliably generated, reducing the amount of entropy (Insufficient Entropy)
References 1
Building Secure Software: How to Avoid Security Problems the Right Way
John Viega and Gary McGraw
Addison-Wesley
2002
ID: REF-207
Applicable Platforms
Languages:
Not Language-Specific : Undetermined
Modes of Introduction
Architecture and Design
Implementation
Related Attack Patterns
Related Weaknesses
ChildOf: Use of Insufficiently Random Values (CWE-330)
ChildOf: Use of Insufficiently Random Values (CWE-330)
Taxonomy Mapping
  • PLOVER
  • WASC
  • CERT C Secure Coding
Notes
MaintenanceAs 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.