CWE-497 Detalhe

CWE-497

Exposure of Sensitive System Information to an Unauthorized Control Sphere
Incomplete
2006-07-19
00h00 +00:00
2025-12-11
00h00 +00:00
CWE Mitre.org
Notificações para um CWE
Fique informado sobre quaisquer alterações para um CWE específico.
Gerenciar notificações

Nome: Exposure of Sensitive System Information to an Unauthorized Control Sphere

The product does not properly prevent sensitive system-level information from being accessed by unauthorized actors who do not have the same level of access to the underlying system as the product does.

Informações Gerais

Modos de Introdução

Implementation

Plataformas Aplicáveis

Linguagem

Class: Not Language-Specific (Undetermined)

Tecnologias

Class: Not Technology-Specific (Undetermined)
Class: Web Based (Undetermined)

Consequências Comuns

Escopo Impacto Probabilidade
ConfidentialityRead Application Data

Exemplos Observados

Referências Descrição

CVE-2021-32638

Code analysis product passes access tokens as a command-line parameter or through an environment variable, making them visible to other processes via the ps command.

Mitigações Potenciais

Phases : Architecture and Design // Implementation
Production applications should never use methods that generate internal details such as stack traces and error messages unless that information is directly committed to a log that is not viewable by the end user. All error message text should be HTML entity encoded before being written to the log file to protect against potential cross-site scripting attacks against the viewer of the logs

Métodos de Detecção

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.)
Eficácia : High

Notas de Mapeamento de Vulnerabilidade

Justificativa : 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.
Comentário : 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.

Padrões de Ataque Relacionados

CAPEC-ID Nome do Padrão de Ataque
CAPEC-170 Web Application Fingerprinting
An attacker sends a series of probes to a web application in order to elicit version-dependent and type-dependent behavior that assists in identifying the target. An attacker could learn information such as software versions, error pages, and response headers, variations in implementations of the HTTP protocol, directory structures, and other similar information about the targeted service. This information can then be used by an attacker to formulate a targeted attack plan. While web application fingerprinting is not intended to be damaging (although certain activities, such as network scans, can sometimes cause disruptions to vulnerable applications inadvertently) it may often pave the way for more damaging attacks.
CAPEC-694 System Location Discovery

Referências

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

Submissão

Nome Organização Data Data de lançamento Version
7 Pernicious Kingdoms 2006-07-19 +00:00 2006-07-19 +00:00 Draft 3

Modificações

Nome Organização Data Comentário
Eric Dalci Cigital 2008-07-01 +00:00 updated Time_of_Introduction
CWE Content Team MITRE 2008-09-08 +00:00 updated Relationships, Other_Notes, Taxonomy_Mappings, Type
CWE Content Team MITRE 2009-03-10 +00:00 updated Demonstrative_Examples
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 2009-10-29 +00:00 updated Description, Other_Notes
CWE Content Team MITRE 2009-12-28 +00:00 updated Description, Name
CWE Content Team MITRE 2011-06-01 +00:00 updated Common_Consequences, Relationships, Taxonomy_Mappings
CWE Content Team MITRE 2011-09-13 +00:00 updated Relationships, Taxonomy_Mappings
CWE Content Team MITRE 2012-05-11 +00:00 updated Related_Attack_Patterns, Relationships
CWE Content Team MITRE 2012-10-30 +00:00 updated Potential_Mitigations
CWE Content Team MITRE 2014-07-30 +00:00 updated Relationships, Taxonomy_Mappings
CWE Content Team MITRE 2017-05-03 +00:00 updated Related_Attack_Patterns
CWE Content Team MITRE 2017-11-08 +00:00 updated Applicable_Platforms, Taxonomy_Mappings
CWE Content Team MITRE 2019-01-03 +00:00 updated Taxonomy_Mappings
CWE Content Team MITRE 2019-06-20 +00:00 updated Related_Attack_Patterns
CWE Content Team MITRE 2020-02-24 +00:00 updated Description, Name, References, Relationships, Type
CWE Content Team MITRE 2021-03-15 +00:00 updated Demonstrative_Examples
CWE Content Team MITRE 2021-10-28 +00:00 updated Relationships
CWE Content Team MITRE 2022-10-13 +00:00 updated Related_Attack_Patterns
CWE Content Team MITRE 2023-01-31 +00:00 updated Description, 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
CWE Content Team MITRE 2023-10-26 +00:00 updated Observed_Examples
CWE Content Team MITRE 2025-04-03 +00:00 updated Demonstrative_Examples, Relationships
CWE Content Team MITRE 2025-12-11 +00:00 updated Applicable_Platforms, Relationships, Weakness_Ordinalities
As informações apresentadas no CVE Find originam-se de várias fontes de referência cuidadosamente selecionadas. Os dados CVE são fornecidos pela MITRE Corporation e pelo National Vulnerability Database (NVD). O catálogo de Vulnerabilidades Conhecidas Exploradas (KEV) é proveniente da Cybersecurity and Infrastructure Security Agency (CISA), enquanto as pontuações EPSS vêm do FIRST.org. Além disso, os dados sobre fraquezas de software (CWE) e padrões de ataque comuns (CAPEC) são mantidos pela MITRE Corporation, e as informações sobre configurações de hardware e software (CPE) são fornecidas pelo NVD.