Definition
Comparing strings using a variety of techniques to determine if a deceptive or malicious string is being presented to a user.
How it works
A homoglyph, in this context, is a deceptive string or word which looks like a trusted word, but is composed of different characters, for example: goooogle.com versus google.com. This is commonly found in phishing and typo squatting attacks where a human exploiting through a social engineering campaign.
Considerations
- In very large environments processing DNS queries can be computationally expensive due to the amount of traffic that is generated
- Legitimate companies and products use non-dictionary words in their names that could result in many false positives
Implementation perspective
Homoglyph Detection 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 Email, URL.
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 (2)
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 (7)
ATT&CK for ICS (2)
Authoritative sources
- Open this technique on the official D3FEND website ↗
- Open the official ontology resources ↗
- Computer-implemented methods and systems for identifying visually similar text character strings ↗Greathorn Inc · Raymond W. Wallace, III · PatentReference
- System and method for detecting homoglyph attacks with a siamese convolutional neural network ↗Endgame Inc · Jonathan Woodbridge; Anjum Ahuja; Daniel Grant · PatentReference
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