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mailverdict

pantos12/mailverdict · Homepage

Forward an email, get a calibrated phishing verdict.

Classification & Routing94%Runner-up: Content Moderation

What it is

MailVerdict parses an email deterministically, asks a calibrated classifier one question set, and returns a phishing probability plus indicators. It ships as an MCP server for Copilot Studio and a REST endpoint for Power Automate.

How it uses Jev

After deterministic parsing, one Jev call answers independent questions (is_phishing, requests_credentials, requests_payment, impersonates_brand_or_person, urgency_pressure, attack_type) over the ParsedEmail state. JevSignals feed code thresholds: p >= 0.90 is PHISHING, otherwise SUSPICIOUS; an LLM only explains SUSPICIOUS verdicts.

Primitives:choicescorenoul

Technique worth stealing

Use a calibrated classifier for the verdict and reserve the LLM for prose, so the label cannot be prompt-injected.

Try it

npm install; npm run analyze -- tests/fixtures/emails/phishing/01-credential-harvest-lookalike.eml

View on GitHub

judged by Jevjev-1.13.0

Evidence

Each line is one question put to Jev about the README. ≥ 0.60 reads as yes, ≤ 0.40 as no; in between Jev is not making a call.

  • Jev-centricyes0.63
  • Shows a System One patternunclear0.58
  • Handles uncertaintyno0.13
  • Measuredno0.15
  • Runnableyes0.97
  • Worth recommendingno0.29
  • Model replicano0.15
  • Problem scopescore on a 0–2 scale1.55
  • About Jevyes0.97

Signals by Jev jev-1.13.0, card written by DeepSeek V4.1 Flash from the README on 20 Sept 2026.