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MITRE D3FEND™ Learning Center

D3-WSAA — Web Session Activity Analysis

Monitoring changes in user web session behavior by comparing current web session activity to a baseline behavior profile or a catalog of predetermined malicious behavior.

1Mitigation mapping
1Parent technique
1Related artifact
4Source references

Detect · D3FEND ontology 1.6.0 · Active

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Official D3FEND definition

Definition

Monitoring changes in user web session behavior by comparing current web session activity to a baseline behavior profile or a catalog of predetermined malicious behavior.

Official D3FEND knowledge-base content

How it works

User web session data is collected over a period of time to create a user behavior profile. Data collected includes clicks made on a website, average time between clicks, filling out web forms, order in which pages are viewed, and downloading files. Current user web session behavior is then compared against the use behavior profile to identify anomalies and a likelihood that the current user web session is malicious. Current user web session behavior can also be compared to predetermined known malicious behavior profiles that are developed through analysis of malware in run time at a threat research facility.

Considerations

  • Potential for false positives from anomalies that are not associated with malicious activity.
  • Attackers may not differentiate their web session activity enough to trigger an alert.
Bare Metal Cyber interpretation

Implementation perspective

Web Session Activity 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 the relevant system, activity, and evidence sources.

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

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

analyzesWeb Resource Access
Curated D3FEND mapping

ATT&CK Enterprise mitigation relationships

These links come from the D3FEND ontology’s ATT&CK mitigation mapping. They help users navigate between the knowledge bases and do not guarantee mitigation effectiveness.

Source record

Authoritative sources