Build a Custom Phishing Detector With the Platform API
Phishing detection becomes more effective when it evaluates several trust signals together instead of relying on a single blocklist or keyword rule. The Trusted Sender Score API can help applications inspect domains, email authentication, and reputation indicators as part of an automated security workflow.
A custom detector may sit inside a mail gateway, security dashboard, help desk tool, or account-registration process. Its job is to turn API results into a practical decision: allow, review, quarantine, or block.
The most reliable design separates data collection from policy enforcement. This makes it easier to update thresholds, investigate false positives, and adapt the detector as attackers change their techniques.
Define The Detection Workflow
Start by identifying where suspicious messages or domains enter your system. An inbound email gateway may analyze the sender domain and links, while a support application may check a domain copied from a reported message. Each use case can require different response times and risk thresholds.
Create a normalized input model before calling the API. Useful fields may include the sender domain, return-path domain, visible link domains, message identifiers, and the source of the report. Store the original values separately so analysts can review exactly what the detector received.
The output should use clear risk states rather than exposing raw technical details to every user. For example, “trusted,” “needs review,” and “high risk” can map to different actions while the underlying signals remain available to security staff.
Prepare Authentication And API Handling
Review the platform’s API documentation for authentication requirements, request formats, response fields, usage limits, and error behavior. Keep API credentials in a secrets manager or protected environment variable. Never place a key in browser JavaScript, public repositories, or client-side mobile code.
Use a dedicated service layer between your application and the API. This layer can validate domains, remove accidental whitespace, apply timeouts, and translate provider responses into your internal schema. It can also prevent a temporary API failure from being mistaken for a trusted result.
Caching is useful for repeated domain checks, especially when many messages come from the same sender. Set an expiration period appropriate to your risk model, and provide a way to force a fresh lookup when an analyst is investigating an active campaign.
Collect And Normalize Evidence
A phishing detector should inspect more than the display name shown in an inbox. Compare the visible sender domain with the actual authenticated or return-path domain when those values are available. Extract domains from links, normalize case, and handle internationalized domains carefully.
DKIM and DMARC results can add important context. A message that fails authentication deserves closer attention, although authentication alone does not prove that a sender is safe. Attackers can send from newly registered domains that authenticate correctly.
For guidance on spoofing indicators and defensive checks, consult these anti-spoofing resources. Use the resulting principles to decide which fields your parser should preserve and which mismatches should increase risk.
Combine Signals Into A Risk Score
Treat the API response as evidence for a decision engine rather than a final verdict. A low reputation signal, failed DMARC alignment, and a misleading lookalike domain may each carry moderate weight, but together they can justify quarantine.
Keep scoring rules configurable. Security teams may want stricter handling for finance-related mailboxes than for general correspondence. Log each contributing signal and the applied rule so analysts can explain why a message was blocked or escalated.
| Signal | Example Interpretation | Typical Response |
|---|---|---|
| Domain reputation | Established trust or suspicious history | Allow or review |
| DMARC status | Alignment passes or fails | Increase scrutiny when failing |
| DKIM status | Signature validates or is absent | Use as supporting evidence |
| Domain mismatch | Visible and authenticated domains differ | Review or quarantine |
| API availability | Lookup succeeds or times out | Fail safely and retain for review |
A score should not conceal uncertainty. If the API is unavailable, mark the result as “indeterminate” rather than “trusted.” This prevents an operational outage from creating a security bypass.
Add Testing And Analyst Feedback
Build a test set containing legitimate newsletters, transactional messages, spoofed sender examples, lookalike domains, and known phishing samples handled according to your organization’s security policy. Test each parser and scoring rule independently before running the complete workflow.
Measure false positives as carefully as missed threats. A detector that blocks invoices from legitimate suppliers may encourage users to bypass it, while a detector that allows too many suspicious messages will lose credibility.
When analyzing social-platform alerts or account notifications, the social notification guide can help shape validation logic. Record analyst decisions and use them to tune thresholds, but preserve human review for ambiguous cases.
Recommendations For A Safer Implementation
- Validate and normalize every domain before submitting it to the API.
- Keep credentials server-side and rotate them through your secrets-management process.
- Cache repeat lookups while allowing analysts to request fresh results.
- Log raw evidence, normalized fields, API status, and the final policy decision.
- Treat timeouts, malformed responses, and quota errors as indeterminate states.
A practical rollout begins in monitor-only mode. Let the detector produce scores and alerts without blocking messages, then compare its decisions with analyst findings. Once the signal quality is understood, introduce quarantine rules for high-confidence cases and retain an appeal path for legitimate senders.
Use the platform API as one component of layered email security. Combine sender reputation with authentication checks, domain similarity analysis, URL inspection, user reporting, and safe handling of suspicious attachments. Begin by creating a small authenticated service, test it against representative traffic, and expand the workflow as its results become measurable.