Détail du CWE-477

CWE-477

Use of Obsolete Function
Draft
2006-07-19
00h00 +00:00
2023-06-29
00h00 +00:00
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Nom: Use of Obsolete Function

The code uses deprecated or obsolete functions, which suggests that the code has not been actively reviewed or maintained.

Description du CWE

As programming languages evolve, functions occasionally become obsolete due to:

  • Advances in the language
  • Improved understanding of how operations should be performed effectively and securely
  • Changes in the conventions that govern certain operations

Functions that are removed are usually replaced by newer counterparts that perform the same task in some different and hopefully improved way.

Informations générales

Modes d'introduction

Implementation

Plateformes applicables

Langue

Class: Not Language-Specific (Undetermined)

Conséquences courantes

Portée Impact Probabilité
OtherQuality Degradation

Mesures d’atténuation potentielles

Phases : Implementation
Refer to the documentation for the obsolete function in order to determine why it is deprecated or obsolete and to learn about alternative ways to achieve the same functionality.
Phases : Requirements
Consider seriously the security implications of using an obsolete function. Consider using alternate functions.

Méthodes de détection

Automated Static Analysis - Binary or Bytecode

According to SOAR, the following detection techniques may be useful:

Highly cost effective:
  • Binary / Bytecode Quality Analysis
Cost effective for partial coverage:
  • Bytecode Weakness Analysis - including disassembler + source code weakness analysis

Efficacité : High

Manual Static Analysis - Binary or Bytecode

According to SOAR, the following detection techniques may be useful:

Cost effective for partial coverage:
  • Binary / Bytecode disassembler - then use manual analysis for vulnerabilities & anomalies

Efficacité : SOAR Partial

Dynamic Analysis with Manual Results Interpretation

According to SOAR, the following detection techniques may be useful:

Highly cost effective:
  • Debugger

Efficacité : High

Manual Static Analysis - Source Code

According to SOAR, the following detection techniques may be useful:

Highly cost effective:
  • Manual Source Code Review (not inspections)
Cost effective for partial coverage:
  • Focused Manual Spotcheck - Focused manual analysis of source

Efficacité : High

Automated Static Analysis - Source Code

According to SOAR, the following detection techniques may be useful:

Highly cost effective:
  • Source Code Quality Analyzer
  • Source code Weakness Analyzer
  • Context-configured Source Code Weakness Analyzer

Efficacité : High

Automated Static Analysis

According to SOAR, the following detection techniques may be useful:

Highly cost effective:
  • Origin Analysis

Efficacité : High

Architecture or Design Review

According to SOAR, the following detection techniques may be useful:

Highly cost effective:
  • Formal Methods / Correct-By-Construction
  • Inspection (IEEE 1028 standard) (can apply to requirements, design, source code, etc.)

Efficacité : High

Notes de cartographie des vulnérabilités

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.
Commentaire : 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.

Références

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

Soumission

Nom Organisation Date Date de publication Version
7 Pernicious Kingdoms 2006-07-19 +00:00 2006-07-19 +00:00 Draft 3

Modifications

Nom Organisation Date Commentaire
Eric Dalci Cigital 2008-07-01 +00:00 updated Potential_Mitigations, Time_of_Introduction
CWE Content Team MITRE 2008-09-08 +00:00 updated Relationships, Other_Notes, Taxonomy_Mappings
CWE Content Team MITRE 2009-03-10 +00:00 updated Other_Notes
CWE Content Team MITRE 2009-05-27 +00:00 updated Demonstrative_Examples
CWE Content Team MITRE 2009-07-27 +00:00 updated Demonstrative_Examples
CWE Content Team MITRE 2011-03-29 +00:00 updated Demonstrative_Examples
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 2012-05-11 +00:00 updated Relationships
CWE Content Team MITRE 2012-10-30 +00:00 updated Potential_Mitigations
CWE Content Team MITRE 2014-06-23 +00:00 updated Description, Other_Notes, Potential_Mitigations
CWE Content Team MITRE 2014-07-30 +00:00 updated Detection_Factors, Relationships, Taxonomy_Mappings
CWE Content Team MITRE 2017-11-08 +00:00 updated Applicable_Platforms, Name, Relationships, Taxonomy_Mappings
CWE Content Team MITRE 2019-01-03 +00:00 updated Taxonomy_Mappings, Weakness_Ordinalities
CWE Content Team MITRE 2020-02-24 +00:00 updated References, Relationships
CWE Content Team MITRE 2020-08-20 +00:00 updated Relationships
CWE Content Team MITRE 2021-03-15 +00:00 updated Relationships
CWE Content Team MITRE 2023-04-27 +00:00 updated Relationships
CWE Content Team MITRE 2023-06-29 +00:00 updated Mapping_Notes
Les informations affichées sur CVE Find proviennent de plusieurs sources de référence rigoureusement sélectionnées. Les données CVE sont fournies par MITRE Corporation et la National Vulnerability Database (NVD). Le catalogue des vulnérabilités activement exploitées (KEV) provient de la Cybersecurity and Infrastructure Security Agency (CISA), tandis que les scores EPSS sont issus de FIRST.org. Enfin, les données relatives aux faiblesses logicielles (CWE) et aux schémas d'attaque courants (CAPEC) sont maintenues par MITRE Corporation, et les informations sur les configurations logicielles et matérielles (CPE) proviennent du NVD.