VIPERAI INBOX – Email & Phishing Analyzer

1. Snapshot

Environment

Suspicious Emails / Forwarded Messages

Purpose

AI-Assisted Phishing Analysis

Planned Tech

Python / LLM API / Web UI

Status

In Progress (Design Phase)

2. Why I'm Building This

❌ The Constant Question: "Is This Email Legit?"

Users and help desk staff ask this question dozens of times per day, but existing tools are either:

Overly simplistic checklists that don't catch sophisticated phishing
Enterprise-grade solutions too expensive for MSP/SMB environments
Require tying directly into production mailboxes (privacy and access concerns)
Provide technical data without user-friendly explanations

ViperAI INBOX exists to provide a middle ground: accept pasted or uploaded email content, analyze it using AI-assisted techniques, and generate both technical findings and user-friendly explanations.

Goals:

Accept suspicious emails without requiring mailbox access
Analyze sender authenticity, link destinations, language cues, and attachment indicators
Provide risk ratings and explanations in plain language
Generate actionable recommendations (block sender, verify via phone, etc.)
Make phishing analysis accessible to non-technical users and help desk staff

3. Planned Behavior

ViperAI INBOX will provide a simple workflow for email analysis:

📥

Input: Email Content

Users paste raw email text, upload .eml/.msg files, or provide email headers. No direct mailbox integration required.

🔍

Parsing & Analysis

Extract sender information, reply-to addresses, domains, embedded links, and language patterns. Check against known indicators.

🤖

AI-Assisted Detection

Use LLM to identify social engineering tactics: urgency language, scare tactics, credential harvest attempts, impersonation signals.

📊

Risk Assessment

Generate risk score (Likely Legit / Suspicious / High-Risk) based on multiple indicators and context analysis.

📝

User-Friendly Explanation

Provide clear explanation of why the email is risky, what the sender is trying to accomplish, and recommended next steps.

✅

Actionable Recommendations

Suggest specific actions: "Do not click links", "Verify sender via known phone number", "Forward to IT security team", etc.

4. Current State

ViperAI INBOX is in the design and planning phase:

✅ Concept and workflow defined
✅ Core feature set identified
🔄 Technical architecture being designed
🔄 Evaluating LLM APIs and parsing libraries
⏳ UI mockups in progress
⏳ Initial prototype development not yet started

Once a working prototype is complete, this page will be updated with screenshots and a link to try the tool. Status will change from "In Progress" to "Active" when a first version is publicly available.

5. Screenshots / Development Preview

ViperAI INBOX Start Screen - Email Analysis Interface

Analysis Results - Suspicious Email Findings & Risk Assessment

Early development screenshots showing the Avalonia UI interface for email analysis. Final version will include: drag-and-drop .eml/.msg support, comprehensive header analysis, local AI-powered risk assessment, and professional export formats.

6. Links

🔒 Private Repository

ViperAI INBOX is currently in private development. The repository will be made public once the initial release is ready. Tech stack: .NET 8, Avalonia UI, MimeKit for email parsing, with embedded local AI (Llama 3.2) for privacy-first analysis.

🔗 GitHub Profile (Repository Coming Soon)

Planned Features: .eml/.msg/.mime support, SPF/DKIM/DMARC validation, URL analysis, attachment scanning, local AI explanations (privacy-first), portable USB deployment, batch processing, and professional export formats (JSON/MD/HTML). Check GitHub for public release announcements.