feat: Add User-specific Sender Whitelisting and Blacklisting

[onkar0127]

Description:

Feature Summary

To give users more control over their spam detection settings, we should implement a user-level Blacklist & Whitelist rules manager. This allows users to manually specify email addresses or domains that should:

• Whitelist: Always be marked as safe (bypassing the ML model predictions).
• Blacklist: Always be flagged as spam/malicious (bypassing the ML model predictions).

---

Proposed Scope of Integration

• Node.js Gateway Router: server.js
• Frontend Rules Management Interface: App.jsx

---

Suggested Implementation Plan

1. Database Schema (MongoDB)

Create a new Rule mongoose schema to map rules to specific users:

// backend/models/Rule.js
const mongoose = require('mongoose');

const ruleSchema = new mongoose.Schema({
  user: { type: mongoose.Schema.Types.ObjectId, ref: 'User', required: true },
  type: { type: String, enum: ['blacklist', 'whitelist'], required: true },
  pattern: { type: String, required: true }, // e.g. "friend@trusted.com" or "@trusted.com"
}, { timestamps: true });

module.exports = mongoose.model('Rule', ruleSchema);

2. API Gateway Logic in server.js

Before making a prediction request to the Flask ML service inside the /predict route, query the database for matching user-defined rules:

// backend/server.js
const Rule = require('./models/Rule');

app.post("/predict", protect, async (req, res) => {
  const { text, type, sender } = req.body; // e.g. sender email passed from client
  
  if (sender) {
    // Check for matching rules
    const rule = await Rule.findOne({ user: req.user.id, pattern: sender });
    if (rule) {
      const isSpam = rule.type === 'blacklist';
      return res.json({
        prediction: isSpam ? "spam" : "ham",
        confidence: 1.0,
        rule_applied: rule.type
      });
    }
  }
  
  // Otherwise, fallback to the Flask ML model prediction
  // const response = await axios.post(...)
});

3. Frontend UI Settings Tab

Add a "Rule Manager" view to the frontend where users can:

• View their existing blacklist/whitelist entries.
• Add new rules (e.g., input field for email/domain + dropdown for type).
• Delete existing rules.

[github-actions]

👋 Welcome back! Thanks for your continued contribution. Your issue/PR is received and waiting for maintainer review.

[github-actions]

The text proposes a feature to enhance a spam detection system by allowing users to manually create email sender whitelists and blacklists at the account level. Users can specify email addresses or domains to always classify as either safe (whitelisted) or spam/malicious (blacklisted), bypassing the machine learning predictions. The implementation involves changes across the backend (MongoDB schema for user-specific rules and adjustments to the API gateway logic in Node.js) and the frontend (a new Rule Manager interface for managing whitelist/blacklist entries).

[onkar0127]

@Userunknown84 Please let me know if you need any additional context or code snippets to help resolve this. Happy to assist under SSOC!!

[Userunknown84]

Good approach . If mail is safe later on then it removed from blacklist or not. Whitelist can be true but if they become blaclist then they gone be blacklist or change on after safe.

[Userunknown84]

Idea is good but generally blacklist mail is there then they become blacklist so what we gonna do in that case.