Definition
Taking known malicious identifiers and determining if they are present in a system.
How it works
Identifier activity analysis is the process of taking identifiers--typically known malicious identifiers--and determining the artifacts that have interacted with those identifiers.
There are many open and closed source repositories of identifiers that represent indicators of compromise. For example, VirusTotal contains hash signatures of malware and IP Addresses used by threat actors. Defenders can search for these indicators of compromise their own systems to gain context on activity around an identifier.
Considerations
Indicator activity analysis is a good way to gain high precision analysis, but adversaries can modify their own signatures such as hashes quickly to evade detection. This is related to David Bianco’s Pyramid of Pain - Indicators on the lower level (hash values, IP addresses domain names) are easy for adversaries to change.
Identifier activity data of interest for analysis with the identifier might include, but is not limited to:
- network traffic activity where the identifier was used to identify communicating entities or referred to in the communication
- process activity referencing the identifier, especially for resource access
- file activity referencing the identifier
- registry settings referencing the identifier
Implementation perspective
Identifier 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 Identifier.
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.
Technique hierarchy
Top-level family
Parent techniques
Direct child techniques
None listed at this level.
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
Show inferred artifact relationship paths (1)
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 (4)
ATT&CK for ICS (1)
Authoritative sources
- Open this technique on the official D3FEND website ↗
- Open the official ontology resources ↗
- The Pyramid of Pain ↗David Bianco · InternetArticleReference
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