docs: update README documentation

Author: Wellington Gonzalez

README.md

@@ -23,7 +23,6 @@
 ![GitHub stars](https://img.shields.io/github/stars/wellingtoong/cloud-security-analyzer?style=social)
 ![GitHub forks](https://img.shields.io/github/forks/wellingtoong/cloud-security-analyzer?style=social)
 
----
 
 A powerful, AI-driven tool for analyzing Terraform Plan JSON files to identify security vulnerabilities and generate actionable recommendations. Built for DevSecOps workflows, it leverages Google Gemini AI to provide intelligent insights into cloud infrastructure configurations, ensuring compliance with best practices like CIS Benchmarks.
 
@@ -46,44 +45,33 @@ This tool is particularly valuable for teams deploying to AWS (with roadmap supp
 
 ## 🎯 Why Cloud Security Analyzer?
 
-- 🛡️ Prevent security misconfigurations before deployment  
-- 🤖 AI-enhanced contextual risk detection  
-- 📊 Executive-ready HTML and JSON reports  
-- 🔄 CI/CD native integration  
-- ☁️ Built for AWS (Azure & GCP roadmap)  
-- 🧱 Designed for scalable DevSecOps environments  
+- Prevent security misconfigurations before deployment  
+- AI-enhanced contextual risk detection  
+- Executive-ready HTML and JSON reports  
+- CI/CD native integration  
+- Built for AWS (Azure & GCP roadmap)  
+- Designed for scalable DevSecOps environments  
 
 
-## 📘 Overview
-
-Infrastructure as Code (IaC) tools like Terraform enable rapid deployment of cloud resources, but misconfigurations can introduce critical security risks. Cloud Security Analyzer addresses this by:
-
-- 🔍 **Static Analysis**: Scanning Terraform plans for vulnerabilities without executing changes.
-- 🤖 **AI-Powered Insights**: Using advanced AI to detect nuanced issues beyond rule-based checks.
-- 📊 **Comprehensive Reporting**: Generating structured JSON outputs and visually appealing HTML reports with severity scores, risk assessments, and remediation steps.
-- 🔄 **CI/CD Integration**: Seamlessly integrating into pipelines for automated security reviews.
-
-This tool is particularly valuable for teams deploying to AWS (with roadmap support for Azure and GCP), helping prevent breaches from exposed databases, overly permissive security groups, unencrypted storage, and more.
-
 ## ⚙️ How It Works
 
-1. 📥 **Input**: Provide a Terraform Plan JSON file (generated via `terraform plan -out=tfplan.binary && terraform show -json tfplan.binary > plan.json`).
-2. 🧠 **Analysis**: The tool sends the plan to Google Gemini AI, guided by a specialized prompt template, to identify vulnerabilities, assign severities (CRITICAL, HIGH, MEDIUM, LOW), and suggest fixes.
-3. 📤 **Output**:
-   - 🧾 **JSON Report**: Structured data for programmatic consumption or further processing.
-   - 🖥️ **HTML Report**: Interactive, Tailwind CSS-styled dashboard with executive summaries, vulnerability cards, code recommendations, and references to AWS documentation.
-4. 🏷️ **Metadata Enrichment**: Automatically captures execution context like branch, timestamp, Terraform version, and environment for traceability.
+1. **Input**: Provide a Terraform Plan JSON file (generated via `terraform plan -out=tfplan.binary && terraform show -json tfplan.binary > plan.json`).
+2. **Analysis**: The tool sends the plan to Google Gemini AI, guided by a specialized prompt template, to identify vulnerabilities, assign severities (CRITICAL, HIGH, MEDIUM, LOW), and suggest fixes.
+3. **Output**:
+   - **JSON Report**: Structured data for programmatic consumption or further processing.
+   - **HTML Report**: Interactive, Tailwind CSS-styled dashboard with executive summaries, vulnerability cards, code recommendations, and references to AWS documentation.
+4. **Metadata Enrichment**: Automatically captures execution context like branch, timestamp, Terraform version, and environment for traceability.
 
 The process is fast, typically completing in seconds, and supports both local execution and containerized runs.
 
 ## 🏗️ Architecture
 
 The project follows a modular Python architecture for maintainability and extensibility:
 
-- 🧠 **`core/`**: Core logic, including the `TerraformAnalyzer` class that interfaces with Google Gemini AI for analysis.
-- 📂 **`data/`**: Data handling modules for loading Terraform plans and prompts.
-- 📝 **`reports/`**: Report generation, featuring Jinja2 templates for HTML rendering and utility functions for severity classification and formatting.
-- 🖥️ **`cli/`**: Command-line interface for user interaction, path resolution, and orchestration.
+- **`core/`**: Core logic, including the `TerraformAnalyzer` class that interfaces with Google Gemini AI for analysis.
+- **`data/`**: Data handling modules for loading Terraform plans and prompts.
+- **`reports/`**: Report generation, featuring Jinja2 templates for HTML rendering and utility functions for severity classification and formatting.
+- **`cli/`**: Command-line interface for user interaction, path resolution, and orchestration.
 
 Key dependencies include `google-generativeai` for AI integration, `jinja2` for templating, and standard libraries for JSON handling. The design emphasizes separation of concerns, making it easy to extend for multi-cloud support or alternative AI models.