Exposure of Sensitive Information Through Data Queries

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


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.

Demonstrations

The following examples help to illustrate the nature of this weakness and describe methods or techniques which can be used to mitigate the risk.

Note that the examples here are by no means exhaustive and any given weakness may have many subtle varieties, each of which may require different detection methods or runtime controls.

Example One

See the book Translucent Databases for examples.

See Also

SFP Secondary Cluster: State Disclosure

This category identifies Software Fault Patterns (SFPs) within the State Disclosure cluster.

Comprehensive CWE Dictionary

This view (slice) covers all the elements in CWE.

Weaknesses without Software Fault Patterns

CWE identifiers in this view are weaknesses that do not have associated Software Fault Patterns (SFPs), as covered by the CWE-888 view. As such, they represent gaps in...

Weaknesses Introduced During Implementation

This view (slice) lists weaknesses that can be introduced during implementation.


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