akitaonrails

akitaonrails / frank_fbi

Public

Scam/Phishing email scanner and analyzer

44
4
100% credibility
Found Mar 13, 2026 at 44 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Ruby
AI Summary

Frank FBI analyzes suspicious emails forwarded to a dedicated inbox and automatically replies with a detailed fraud risk assessment including scores, explanations, and safety warnings.

How It Works

1
👀 Spot a suspicious email

You receive a message that looks fishy, like a too-good-to-be-true offer or urgent demand from an unknown sender.

2
📧 Set up your fraud checker inbox

Create a fresh email account just for checking shady messages, keeping your main inbox safe.

3
🔧 Connect and launch your checker

Link the inbox to the fraud checker so it watches for your forwarded emails automatically.

4
📤 Forward the suspicious email

Attach or forward the odd message to your checker inbox, just like sharing with a friend.

5
📊 Receive the safety report

A clear report arrives right back, scoring the risk, explaining why it's safe or scammy, with warnings about links and files.

🛡️ Decide with confidence

You now know if it's legit or a trick, staying protected without opening dangerous stuff.

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Star Growth

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AI-Generated Review

What is frank_fbi?

Frank FBI is a Ruby on Rails app that scans forwarded emails for phishing and scams—like amazon phishing email scams or paypal phishing scam email invoices—using six analysis layers from header checks to LLM consensus across Claude, GPT-4o, and Grok. Forward a suspicious message as an .eml attachment to a dedicated Gmail inbox, and it auto-replies in the same thread with a scored report (0-100, higher means fraud), verdict, key risks, URL scans via VirusTotal/URLhaus, entity verification with web screenshots, and warnings on dangerous attachments. It also triages WhatsApp/Telegram screenshots for quick scam vs phishing email checks.

Why is it gaining traction?

It delivers polished, thread-aware HTML/plaintext reports with visuals like site screenshots and confidence breakdowns, far beyond basic scanners—perfect for real phishing scam email examples from Microsoft or Snapchat phishing scam emails. Docker Compose deploys effortlessly for local/prod, with optional community reporting to AbuseIPDB/ThreatFox, and it builds sender reputation over time for smarter future verdicts. Devs dig the zero-config Gmail IMAP polling and admin commands via email for whitelisting senders.

Who should use this?

Solo security analysts or IT admins flooded with scam phishing emails who want instant reports without manual VirusTotal lookups. Small teams handling internal fraud alerts, like finance ops spotting paypal scam phishing email invoices. Ruby devs building personal honeypots or extending it for custom scam phishing emails triage.

Verdict

Grab it if you're battling phishing scam email reports daily—detailed output and LLM smarts punch above its 44 stars and 1.0% credibility score. Docs are thorough with smoke tests and samples, but low adoption means watch for edge cases; test your traffic first before enabling beta community reporting.

(198 words)

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