Privacy Leak through Data Queries
Weakness ID: 202 (Weakness Variant)Status: Draft
+ Description

Description Summary

When trying to keep information confidential, an attacker can often infer some of the information by using statistics.

Extended Description

In situations where data should not be tied to individual users, but a large number of users should be able to make queries that "scrub" the identity of users, it may be possible to get information about a user -- e.g., by specifying search terms that are known to be unique to that user.

+ Time of Introduction
  • Architecture and Design
  • Implementation
+ Applicable Platforms

Languages

All

+ Common Consequences
ScopeEffect
Confidentiality

Sensitive information may possibly be leaked through data queries accidentally.

+ Likelihood of Exploit

Medium

+ Demonstrative Examples

Example 1

See the book Translucent Databases for examples.

+ Potential Mitigations

This is a complex topic. See the book Translucent Databases for a good discussion of best practices.

+ Relationships
NatureTypeIDNameView(s) this relationship pertains toView(s)
ChildOfWeakness ClassWeakness Class200Information Exposure
Development Concepts (primary)699
ChildOfWeakness ClassWeakness Class359Privacy Violation
Research Concepts (primary)1000
CanAlsoBeWeakness VariantWeakness Variant201Information Leak Through Sent Data
Research Concepts1000
+ Taxonomy Mappings
Mapped Taxonomy NameNode IDFitMapped Node Name
CLASPAccidental leaking of sensitive information through data queries
+ Content History
Submissions
Submission DateSubmitterOrganizationSource
CLASPExternally Mined
Modifications
Modification DateModifierOrganizationSource
2008-07-01Eric DalciCigitalExternal
updated Time of Introduction
2008-09-08CWE Content TeamMITREInternal
updated Common Consequences, Description, Relationships, Taxonomy Mappings
Previous Entry Names
Change DatePrevious Entry Name
2008-04-11Information Leak Through Data Queries
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