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Project Title\n**phishAlert** – A Browser Extension to Detect Phishing and Spam Emails\n\n## 2. Objective\nTo develop a browser-based extension that automatically analyzes email content in real-time and flags potential phishing and spam emails to protect users from cyber threats.\n\n## 3. Target Users\n- General Gmail users (initially)\n- Non-technical individuals vulnerable to phishing\n- Small businesses without dedicated cybersecurity tools\n\n## 4. Core Problem Statement\nPhishing and spam emails are becoming increasingly sophisticated and frequent. Many users unknowingly fall victim due to a lack of awareness or proper detection tools. Current email platforms do not always detect every malicious email.\n\n## 5. Proposed Solution (MVP Scope)\nA Chrome browser extension that:\n- Scans the content of opened Gmail emails.\n- Detects phishing or spam content using AI or heuristic techniques.\n- Displays a visual warning if the email is suspicious.\n- Operates locally with minimal permissions.\n\n## 6. Key MVP Features\n\n| Feature | Description |\n|--------|-------------|\n| **Email DOM Extraction** | Extract subject, body, sender from opened Gmail emails. |\n| **Phishing/Spam Detection Engine** | Run AI-based or regex-based checks for known patterns (e.g., fake links, urgent language, spoofed addresses). |\n| **Real-Time Warning Display** | Show warning banner or icon if email is suspicious. |\n| **User Feedback Option** | Allow users to confirm or correct detection (optional for MVP). |\n| **Background Script** | Handles API communication and permission management. |\n\n## 7. Non-MVP (Future) Features\n- Integration with external APIs (e.g., VirusTotal, Google Safe Browsing)\n- Detailed phishing/spam explanation to user\n- Dashboard with statistics\n- Multi-email provider support (Outlook, Yahoo)\n- User training or reporting module\n\n## 8. Technology Stack\n\n| Layer | Tool/Framework |\n|-------|----------------|\n| **Frontend** | JavaScript, HTML/CSS, Chrome Extension APIs |\n| **AI/Detection** | OpenAI API / Custom ML Model (fallback to regex rules) |\n| **Backend (optional)** | Firebase/Supabase for feedback logging (optional) |\n| **Communication** | `chrome.runtime` for background-foreground messaging |\n\n## 9. User Flow (MVP)\n1. User opens Gmail.\n2. Extension detects email opened.\n3. Extension extracts email data.\n4. AI/regex engine processes the data.\n5. If threat is found, warning banner appears.\n6. User closes or ignores the warning.\n\n## 10. Success Criteria\n- Can detect basic phishing patterns with \u003e70% accuracy.\n- Seamless integration into Gmail UI.\n- No lag or blocking behavior in Gmail.\n- Warning is visible and understandable by general users.\n\n## 11. Constraints and Assumptions\n- Gmail DOM structure may change—must be flexible.\n- Users will grant minimal permissions.\n- Limited usage of OpenAI or external APIs due to cost (can fall back to regex).\n\n## 12. Initial Development Timeline\n\n| Week | Milestone |\n|------|-----------|\n| 1 | Setup basic Chrome extension structure |\n| 2 | DOM scraping and Gmail email detection |\n| 3 | Implement AI-based or regex-based detection logic |\n| 4 | Display phishing warning UI |\n| 5 | Test across email scenarios |\n| 6 | Final bug fixing, packaging, and documentation |\n\n## 13. Open Questions\n- Should detection happen entirely client-side or also involve a backend?\n- What fallback detection to use if AI fails?\n- What metrics/logs should be collected for improvement?\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsumamarahim%2Fphishalert","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsumamarahim%2Fphishalert","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsumamarahim%2Fphishalert/lists"}