Definition
Ascertaining sender reputation based on information associated with a message (e.g. email/instant messaging).
How it works
Sender trust rating can be considered an indicator of the level of security risk and/or a trust level associated with a sender. The features considered in determining the trust rating include:
Higher values for the number of recipients the sender has interacted with or the number of emails received from the sender, for example, results in a higher trust rating. The trust rating can categorize the sender as unrated, neutral, trusted, suspicious, or malicious.
- Length of time sender has sent emails to the enterprise
- Number of recipients in the enterprise the sender interacts with
- Sender vs. enterprise originated message ratio
- Sender messages opened vs. not-opened ratio
- Number of emails received from this sender
- Number of emails replied to this sender
- Number of emails from this sender not opened
- Number of emails from this sender not opened that contain an attachment
- Number of emails from this sender not opened that contain a URL
- Number of emails sent to this sender
- Number of email replies received from this sender.
Considerations
Legitimate emails from a sender may receive a lower trust rating over time if the sender's domain gets spoofed and is used to send unauthorized emails.
Implementation perspective
Sender Reputation 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 Email.
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 ↗
- Systems and methods for detecting and/or handling targeted attacks in the email channel ↗Graphus Inc · Manoj Kumar Srivastava · PatentReference
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