Design Phishing Detection

Hard45 min
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understanding7 min read

Problem Statement: Phishing Link Detection at Scale

Problem Statement: Phishing Link Detection at Scale — phishing detection system design section.

Problem Statement: Phishing Link Detection at Scale

Enterprise security teams need deterministic, explainable decisions on billions of links embedded in email and chat—not opaque block lists that break payroll and investor updates.

Design anchors (1)

  • Intercept email, chat, and webmail HTML before users click weaponized URLs.
  • Combine fast reputation lookups with selective headless-browser sandbox for unknown destinations.
  • Support link rewriting so every click passes through a policy-enforced reverse proxy.

Failure drills

If threat-intel feed stalls, continue with cached tiers but downgrade unknown links to WARN+rewrite instead of ALLOW. If sandbox pool is saturated, enqueue with SLA 30s and hold message delivery for high-risk tenants only.

Cost and capacity

SignalTarget
Enterprise tenants12K
Inbound links/day2.4B
Peak link/s85K
Target scan p95120ms
javaOne Dark Pro
1public record LinkObservation(String urlHash, String tenantId, Instant seenAt) {}
pythonOne Dark Pro
1def registrable_domain(host: str) -> str:
2 return host.split(".")[-2:] # simplified eTLD+1
typescriptOne Dark Pro
1export interface PhishingContext { channel: "email" | "chat"; tenantId: string; }

Deep dive notes

Phishing kits rotate faster than batch intel feeds. Combine delivery-time reputation with click-time rewrite so a link that was benign at SMTP accept cannot silently harvest credentials later. Appeals must reference immutable ledger rows keyed by policy hash—SOC analysts need to answer why a CFO's wire-transfer email was quarantined without hand-waving.

Operational guardrails

Shadow new rules for 48 hours logging would-block counts. Auto-disable any rule whose FP rate exceeds tenant budget within a sliding hour. Never stamp high-cardinality URL paths into metrics labels; aggregate per tenant and per verdict tier only.

Why interviewers care

Phishing Detection interviews reward crisp scope, explicit trade-offs, and failure stories—not generic microservice diagrams.

Interview checkpoint

Name one failure story for Problem Statement: Phishing Link Detection at Scale that proves you understand real outages, not happy-path diagrams.

Key Highlights

  • Intercept email, chat, and webmail HTML before users click weaponized URLs.
  • Combine fast reputation lookups with selective headless-browser sandbox for unknown destin
  • Support link rewriting so every click passes through a policy-enforced reverse proxy.
Say this clearly
When discussing Problem Statement: Phishing Link Detection at Scale, tie verdicts to policy version and measurable FP budget—not generic "AI will catch phishing."
Avoid
Skipping URL normalization or click-time rescans—interviewers treat that as missing the core threat model.

Section Rescue Kit

Buzzwords to use:

eTLD+1Click-time proxy

Safe statements:

  • "For Problem Statement: Phishing Link Detection at Scale, I would quantify p95 scan latency and sandbox lag before naming vendors."
  • "If time is short, I will sketch normalize → reputation → optional sandbox → rewrite."
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