### Network Segmentation Example Structure

Source: https://github.com/microsoft/security-101/blob/main/_autodocs/NETWORKING_SECURITY.md

Illustrates a typical network segmentation structure using firewalls to isolate different zones.

```text
Internet → Perimeter Firewall → DMZ (public services)
                              → Internal Firewall → User Network
                                                  → Data Network
                                                  → Admin Network
```

--------------------------------

### Allowlist Example for Countries

Source: https://github.com/microsoft/security-101/blob/main/_autodocs/APPLICATION_SECURITY.md

This example demonstrates an allowlist approach for validating country codes. It accepts only predefined values to ensure data integrity.

```plaintext
Allowed countries: ["US", "CA", "MX", "UK", "DE"]
Accept only values in this list
```

--------------------------------

### Add New Lesson to Security 101 Project

Source: https://github.com/microsoft/security-101/blob/main/AGENTS.md

Follow these steps to add a new lesson. This involves creating a Markdown file, adding content, updating README and module tables, and committing changes.

```bash
# 1. Create new Markdown file with proper naming
touch "[Module].[Lesson] [Title].md"

# 2. Add content following template structure
# 3. Update README.md module table with new entry
# 4. Add entry to module overview table
# 5. Ensure quiz file numbering is correct

# 6. Commit changes
git add "[Module].[Lesson] [Title].md" README.md
git commit -m "Add: [Module].[Lesson] - [Title]"
git push
```

--------------------------------

### Blocklist Example for Malicious Strings

Source: https://github.com/microsoft/security-101/blob/main/_autodocs/APPLICATION_SECURITY.md

This example shows a blocklist approach to reject known malicious strings. It is less secure than an allowlist and should be used with caution.

```plaintext
Reject values containing: " OR ", "--", "/*", "*/", ";", "DROP"
```

--------------------------------

### Clone Security 101 Repository

Source: https://github.com/microsoft/security-101/blob/main/AGENTS.md

Use this command to clone the project repository. Navigate into the directory and serve the content locally.

```bash
# Clone the repository
git clone https://github.com/microsoft/Security-101.git
cd Security-101

# View content locally - any Markdown viewer works
# OR serve with a simple HTTP server to use Docsify rendering
python -m http.server 8000
# Then visit http://localhost:8000 in your browser
```

--------------------------------

### Serve Security 101 Content Locally

Source: https://github.com/microsoft/security-101/blob/main/AGENTS.md

Options for serving the project content locally for preview. Choose between Python's built-in server or Node.js http-server.

```bash
# Option 1: Use Python's built-in HTTP server
python -m http.server 8000
```

```bash
# Option 2: Use Node.js http-server (if available)
npx http-server -p 8000
```

```bash
# Option 3: View Markdown files directly in any Markdown editor
```

--------------------------------

### HTML Output Encoding Example

Source: https://github.com/microsoft/security-101/blob/main/_autodocs/APPLICATION_SECURITY.md

Illustrates encoding special characters for HTML context to prevent Cross-Site Scripting (XSS) attacks. For example, '<' is converted to '&lt;'.

```plaintext
< becomes &lt;
```

--------------------------------

### Adversarial Attack Examples

Source: https://github.com/microsoft/security-101/blob/main/_autodocs/AI_SECURITY.md

Provides examples of adversarial attacks across different AI applications, including facial recognition, email classification, and autonomous vehicles. These attacks involve subtle input modifications to cause mispredictions.

```text
Facial Recognition:
- Adding subtle changes to face to fool recognition
- Could bypass biometric authentication

Email Classification:
- Adding benign text to malicious email
- Makes classifier think email is legitimate

Autonomous Vehicle:
- Physical alterations to stop sign
- Vehicle interprets as speed limit sign
```

--------------------------------

### Preview Content Locally with Node.js http-server

Source: https://github.com/microsoft/security-101/blob/main/translations/en/AGENTS.md

Alternatively, use Node.js's http-server to preview the project's content locally. Ensure Node.js and npm are installed.

```bash
npx http-server -p 8000
```

--------------------------------

### Serve Documentation Locally with Python HTTP Server

Source: https://github.com/microsoft/security-101/blob/main/AGENTS.md

Serve the documentation locally to test rendering and links using Python's built-in HTTP server. Visit http://localhost:8000 in your browser to preview changes.

```bash
# Serve locally to test Docsify rendering
python -m http.server 8000

# Visit http://localhost:8000
# Click through navigation to verify all links work
# Check that images load properly
# Verify Markdown formatting renders correctly
```