CWE - CWE-1241: Use of Predictable Algorithm in Random Number Generator (4.15)

Weakness ID: 1241

Vulnerability Mapping: ALLOWEDThis CWE ID may be used to map to real-world vulnerabilities
Abstraction: BaseBase - a weakness that is still mostly independent of a resource or technology, but with sufficient details to provide specific methods for detection and prevention. Base level weaknesses typically describe issues in terms of 2 or 3 of the following dimensions: behavior, property, technology, language, and resource.

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Description

The device uses an algorithm that is predictable and generates a pseudo-random number.

Extended Description

Pseudo-random number generator algorithms are predictable because their registers have a finite number of possible states, which eventually lead to repeating patterns. As a result, pseudo-random number generators (PRNGs) can compromise their randomness or expose their internal state to various attacks, such as reverse engineering or tampering. It is highly recommended to use hardware-based true random number generators (TRNGs) to ensure the security of encryption schemes. TRNGs generate unpredictable, unbiased, and independent random numbers because they employ physical phenomena, e.g., electrical noise, as sources to generate random numbers.

Common Consequences

This table specifies different individual consequences associated with the weakness. The Scope identifies the application security area that is violated, while the Impact describes the negative technical impact that arises if an adversary succeeds in exploiting this weakness. The Likelihood provides information about how likely the specific consequence is expected to be seen relative to the other consequences in the list. For example, there may be high likelihood that a weakness will be exploited to achieve a certain impact, but a low likelihood that it will be exploited to achieve a different impact.

Scope	Impact	Likelihood
Confidentiality	Technical Impact: Read Application Data	High

Potential Mitigations

Phase: Architecture and Design

A true random number generator should be specified for cryptographic algorithms.

Phase: Implementation

A true random number generator should be implemented for cryptographic algorithms.

Relationships

This table shows the weaknesses and high level categories that are related to this weakness. These relationships are defined as ChildOf, ParentOf, MemberOf and give insight to similar items that may exist at higher and lower levels of abstraction. In addition, relationships such as PeerOf and CanAlsoBe are defined to show similar weaknesses that the user may want to explore.

Relevant to the view "Research Concepts" (CWE-1000)

Nature	Type	ID	Name
ChildOf	Class - a weakness that is described in a very abstract fashion, typically independent of any specific language or technology. More specific than a Pillar Weakness, but more general than a Base Weakness. Class level weaknesses typically describe issues in terms of 1 or 2 of the following dimensions: behavior, property, and resource.	330	Use of Insufficiently Random Values

Relevant to the view "Software Development" (CWE-699)

Nature	Type	ID	Name
MemberOf	Category - a CWE entry that contains a set of other entries that share a common characteristic.	1213	Random Number Issues

Relevant to the view "Hardware Design" (CWE-1194)

Nature	Type	ID	Name
MemberOf	Category - a CWE entry that contains a set of other entries that share a common characteristic.	1205	Security Primitives and Cryptography Issues

Modes Of Introduction

The different Modes of Introduction provide information about how and when this weakness may be introduced. The Phase identifies a point in the life cycle at which introduction may occur, while the Note provides a typical scenario related to introduction during the given phase.

Phase	Note
Architecture and Design
Implementation	In many cases, the design originally defines a cryptographically secure random number generator, but is then changed during implementation due to unforeseen constraints.

Applicable Platforms

This listing shows possible areas for which the given weakness could appear. These may be for specific named Languages, Operating Systems, Architectures, Paradigms, Technologies, or a class of such platforms. The platform is listed along with how frequently the given weakness appears for that instance.

Technologies

Class: System on Chip (Undetermined Prevalence)

Demonstrative Examples

Example 1

Suppose a cryptographic function expects random value to be supplied for the crypto algorithm.

During the implementation phase, due to space constraint, a cryptographically secure random-number-generator could not be used, and instead of using a TRNG (True Random Number Generator), a LFSR (Linear Feedback Shift Register) is used to generate a random value. While an LFSR will provide a pseudo-random number, its entropy (measure of randomness) is insufficient for a cryptographic algorithm.

Example 2

The example code is taken from the PRNG inside the buggy OpenPiton SoC of HACK@DAC'21 [REF-1370]. The SoC implements a pseudo-random number generator using a Linear Feedback Shift Register (LFSR).

An example of LFSR with the polynomial function P(x) = x⁶+x⁴+x³+1 is shown in the figure.

(bad code)

Example Language: Verilog

reg in_sr, entropy16_valid;
reg [15:0] entropy16;

assign entropy16_o = entropy16;
assign entropy16_valid_o = entropy16_valid;

always @ (*)
begin

in_sr = ^ (poly_i [15:0] & entropy16 [15:0]);

end

A LFSR's input bit is determined by the output of a linear function of two or more of its previous states. Therefore, given a long cycle, a LFSR-based PRNG will enter a repeating cycle, which is predictable.

Observed Examples

Reference	Description
CVE-2021-3692	PHP framework uses mt_rand() function (Marsenne Twister) when generating tokens

Memberships

This MemberOf Relationships table shows additional CWE Categories and Views that reference this weakness as a member. This information is often useful in understanding where a weakness fits within the context of external information sources.

Nature	Type	ID	Name
MemberOf	Category - a CWE entry that contains a set of other entries that share a common characteristic.	1414	Comprehensive Categorization: Randomness

Vulnerability Mapping Notes

Usage: ALLOWED

(this CWE ID could be used to map to real-world vulnerabilities)

Reason: Acceptable-Use

Rationale:

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.

Comments:

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.

Notes

Maintenance

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.

Related Attack Patterns

CAPEC-ID	Attack Pattern Name
CAPEC-97	Cryptanalysis

References

[REF-1370] "rng_16.v". 2021. <https://github.com/HACK-EVENT/hackatdac21/blob/main/piton/design/chip/tile/ariane/src/rand_num/rng_16.v#L12-L22>. URL validated: 2023-07-15.

Content History

Submissions
Submission Date	Submitter	Organization
2020-02-10 (CWE 4.0, 2020-02-24)	Arun Kanuparthi, Hareesh Khattri, Parbati Kumar Manna, Narasimha Kumar V Mangipudi	Intel Corporation
2020-02-10 (CWE 4.0, 2020-02-24)
Contributions
Contribution Date	Contributor	Organization
2023-06-21	Chen Chen, Rahul Kande, Jeyavijayan Rajendran	Texas A&M University
2023-06-21	suggested demonstrative example
2023-06-21	Shaza Zeitouni, Mohamadreza Rostami, Ahmad-Reza Sadeghi	Technical University of Darmstadt
2023-06-21	suggested demonstrative example
Modifications
Modification Date	Modifier	Organization
2020-06-25	CWE Content Team	MITRE
2020-06-25	updated Common_Consequences, Demonstrative_Examples, Modes_of_Introduction
2020-08-20	CWE Content Team	MITRE
2020-08-20	updated Common_Consequences, Demonstrative_Examples, Description, Maintenance_Notes, Modes_of_Introduction, Potential_Mitigations, Related_Attack_Patterns, Research_Gaps
2021-03-15	CWE Content Team	MITRE
2021-03-15	updated Maintenance_Notes, Research_Gaps
2021-07-20	CWE Content Team	MITRE
2021-07-20	updated Maintenance_Notes
2023-04-27	CWE Content Team	MITRE
2023-04-27	updated Relationships
2023-06-29	CWE Content Team	MITRE
2023-06-29	updated Mapping_Notes
2023-10-26	CWE Content Team	MITRE
2023-10-26	updated Demonstrative_Examples, Description, Observed_Examples, References


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Common Weakness Enumeration

CWE-1241: Use of Predictable Algorithm in Random Number Generator

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