CWE-501 Detail

CWE-501

Trust Boundary Violation
Draft
2006-07-19 00:00 +00:00
2023-06-29 00:00 +00:00

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Trust Boundary Violation

The product mixes trusted and untrusted data in the same data structure or structured message.

Extended Description

A trust boundary can be thought of as line drawn through a program. On one side of the line, data is untrusted. On the other side of the line, data is assumed to be trustworthy. The purpose of validation logic is to allow data to safely cross the trust boundary - to move from untrusted to trusted. A trust boundary violation occurs when a program blurs the line between what is trusted and what is untrusted. By combining trusted and untrusted data in the same data structure, it becomes easier for programmers to mistakenly trust unvalidated data.

Informations

Modes Of Introduction

Architecture and Design

Applicable Platforms

Language

Class: Not Language-Specific (Undetermined)

Common Consequences

Scope Impact Likelihood
Access ControlBypass Protection Mechanism

Detection Methods

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.)
Effectiveness : High

Vulnerability Mapping Notes

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.

References

REF-6

Seven Pernicious Kingdoms: A Taxonomy of Software Security Errors
Katrina Tsipenyuk, Brian Chess, Gary McGraw.
https://samate.nist.gov/SSATTM_Content/papers/Seven%20Pernicious%20Kingdoms%20-%20Taxonomy%20of%20Sw%20Security%20Errors%20-%20Tsipenyuk%20-%20Chess%20-%20McGraw.pdf

Submission

Name Organization Date Date Release Version
7 Pernicious Kingdoms 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 Demonstrative_Example, Time_of_Introduction
CWE Content Team MITRE 2008-09-08 +00:00 updated Description, Relationships, Other_Notes, Taxonomy_Mappings
CWE Content Team MITRE 2011-06-01 +00:00 updated Common_Consequences
CWE Content Team MITRE 2012-05-11 +00:00 updated Relationships
CWE Content Team MITRE 2014-06-23 +00:00 updated Description, Other_Notes
CWE Content Team MITRE 2014-07-30 +00:00 updated Relationships, Taxonomy_Mappings
CWE Content Team MITRE 2017-11-08 +00:00 updated Applicable_Platforms, Relationships
CWE Content Team MITRE 2020-02-24 +00:00 updated References
CWE Content Team MITRE 2021-10-28 +00:00 updated Relationships
CWE Content Team MITRE 2023-04-27 +00:00 updated Detection_Factors, Relationships
CWE Content Team MITRE 2023-06-29 +00:00 updated Mapping_Notes, Relationships
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