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MITRE D3FEND™ Learning Center

D3-DQSA — Database Query String Analysis

Analyzing database queries to detect [SQL Injection](https://capec.mitre.org/data/definitions/66.html).

1Enterprise inferred
1Parent technique
1Related artifact
1Source reference

Detect · D3FEND ontology 1.6.0 · Active

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Official D3FEND definition

Definition

Analyzing database queries to detect [SQL Injection](https://capec.mitre.org/data/definitions/66.html).

Official D3FEND knowledge-base content

How it works

Some implementations use software hooks to intercept function calls related to database query operations. Other implementations might intercept or collect network traffic. The database query string is then extracted and analyzed with various methods, for example:

  • Detecting specific administrative SQL commands
  • Anomalous sequences of commands when compared to a statistical baseline.
  • Anomalous commands for a given user role.

Considerations

Some capabilities sanitize queries before permitting them to be transmitted to the database. This incurs risks such altering data in an undesired way or breaking application functionality.

Bare Metal Cyber interpretation

Implementation perspective

Database Query String Analysis should be treated as a technical defensive capability rather than a product checkbox. In practice, teams should define the protected scope, the conditions under which the technique acts, and the observable evidence that demonstrates the intended behavior. For this technique, likely engineering context includes Database Query.

Use the technique to identify suspicious, unauthorized, or abnormal activity through observable evidence and repeatable analysis.

Questions to ask

  • Which events, states, or artifacts must be observed for the analysis to work?
  • What analytic logic, threshold, comparison, or signature turns observations into a finding?
  • How are expected false positives, blind spots, and environmental variations documented?
  • Who receives the result, and what action is expected when the technique produces a finding?

Evidence and validation

  • Telemetry and data-source configuration records
  • Analytic logic, thresholds, signatures, and version history
  • Test cases demonstrating expected positive and negative results
  • Alert, triage, escalation, and tuning records

Common failure patterns

  • Required telemetry is missing, delayed, or transformed in a way that invalidates the analysis.
  • The technique produces alerts without an accountable triage and response process.
  • Detection coverage is claimed from product deployment without testing the relevant analytic behavior.

This implementation perspective is original Bare Metal Cyber educational content. It does not replace the official D3FEND definition or establish that a specific product implements the technique.

Ontology hierarchy

Technique hierarchy

Top-level family

Parent techniques

Direct child techniques

None listed at this level.

D3FEND graph relationships

Artifacts and ontology entities

These relationships describe how D3FEND connects a defensive technique to artifacts or other ontology entities. They describe graph semantics, not a product certification.

Explicit technique relationships

analyzesDatabase Query
Show inferred artifact relationship paths (1)
Database Query String AnalysisanalyzesDatabase Query
Inferred and experimental

Offensive-technique relationships

These relationships are generated from D3FEND graph paths and are explicitly experimental. They should be treated as hypotheses for defensive analysis—not as proof that the technique prevents, detects, or removes an offensive behavior.

ATT&CK Enterprise (1)
Source record

Authoritative sources