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JEV-Dual-Spectrum-Phishing-Guardian

YuyaForest/JEV-Dual-Spectrum-Phishing-Guardian

Dual-spectrum phishing detection using TypeSafe AI JEV for traditional and AI-generated threats.

Content Moderation0.61Runner-up: Classification & RoutingTraffic light
Automated README summary

Automatically summarized from the README on 29 Oct 2026; not a run by jevbooks. Run instructions and author-reported outcomes still need verification.

What it is

A TypeScript/React web app that analyzes messages and call transcripts for phishing risk, covering traditional social engineering (V-Triad) and generative AI spoofing, for users who need fast threat scoring.

How it uses Jev

JEV scores and chooses across Spectrum 1 (authority, fear, urgency, broken language) and Spectrum 2 (vanilla tone, structural rigidity, temporal blindness, emotional inflation) from the input text. Its probabilities feed a 0-100 threat score and per-vector breakdowns; raw responses are shown in a diagnostics drawer.

Primitives:scorechoicenoul

Technique worth stealing

Splitting detection into two independent spectra: traditional social engineering vectors and generative-AI stylistic anomalies.

Try it

Clone, npm install, set TYPESAFE_API_KEY in .env, then npm run dev and open http://localhost:3000.

View on GitHub

Start using Jev: API key and your first request →

Model judgments from README excerpts

Project signals use repository metadata, an existing summary and the first 700 README characters, not the full project. “Not found” means not detected in that material; it does not establish absence. These are the original judgments with recorded models and dates, not source audits or run results.

Models & evaluation dates

Inclusion gate
jev-1.14.0
Project signals
jev-1.14.0
Category
jev-1.14.0
Pattern tags
jev-1.14.0

Evidence

These signals use repository metadata, an existing summary and at most 700 cleaned README characters. ≥ 0.60 means reported in that excerpt; ≤ 0.40 means not found there. The middle band is inconclusive. None is a source-code audit or a test result. The runnable-tool question excludes research experiments; the recommendation question asks for a learning shortlist, not a quality verdict.

  • Jev is core to the projectunclear0.53
  • Shows a System One patternnot found in the excerpt0.09
  • Describes handling uncertaintynot found in the excerpt0.03
  • Reports measured numbersnot found in the excerpt0.03
  • Is a runnable toolunclear0.54
  • Top-10 learning shortlist signalnot found in the excerpt0.09
  • Is a replica of the modelnot found in the excerpt0.18
  • Solves a common problem (0–2)score on a 0–2 scale1.62 / 2
  • About JevFound in material0.98
Signals
Jev is core to the project0.53Shows a System One pattern0.09Describes handling uncertainty0.03Reports measured numbers0.03Is a runnable tool0.54Top-10 learning shortlist signal0.09Is a replica of the model0.1800.51Solves a common problem (0–2)1.62 / 2012

no-judgment band (0.40–0.60)

Design patterns
Traffic light0.93Scorecard0.2300.51

no-judgment band (0.40–0.60)

The Jev model and date for each judgment stage are listed above. Card written by DeepSeek V4.1 Flash from the README on 29 Oct 2026.