diff --git a/utilities/tools/platform/Parse-WAF-Security-Recommendations.py b/utilities/tools/platform/Parse-WAF-Security-Recommendations.py
new file mode 100644
index 000000000..2885d05aa
--- /dev/null
+++ b/utilities/tools/platform/Parse-WAF-Security-Recommendations.py
@@ -0,0 +1,157 @@
+import requests
+import yaml
+import csv
+import markdown
+from bs4 import BeautifulSoup
+import re
+import time
+
+def parse_toc(url):
+    try:
+        response = requests.get(url)
+        response.raise_for_status()
+        content = response.text
+        toc = yaml.safe_load(content)
+
+        def find_recommendations(items):
+            results = []
+            for item in items:
+                if 'items' in item:
+                    results.extend(find_recommendations(item['items']))
+                elif 'href' in item and item['href'].startswith('recommendations-reference'):
+                    results.append(item)
+            return results
+
+        recommendations = find_recommendations(toc)
+        print(f"Found {len(recommendations)} recommendation items in TOC")
+        return recommendations
+    except Exception as e:
+        print(f"Error parsing TOC: {str(e)}")
+        return []
+
+def parse_recommendation_page(url):
+    try:
+        print(f"Fetching page: {url}")
+        response = requests.get(url)
+        response.raise_for_status()
+        content = response.text
+        
+        # Convert Markdown to HTML
+        html_content = markdown.markdown(content)
+        
+        soup = BeautifulSoup(html_content, 'html.parser')
+        
+        # Find all h2 tags that contain "Azure"
+        azure_h2_tags = [h2 for h2 in soup.find_all('h2') if 'Azure' in h2.text]
+        
+        if not azure_h2_tags:
+            print("No h2 tag with 'Azure' found")
+            return None
+
+        recommendations = []
+        
+        for h2 in azure_h2_tags:
+            name = h2.text.strip()
+            print(f"Found name: {name}")
+            
+            # Find all h3 tags that follow this h2 until the next h2
+            h3_tags = []
+            next_element = h2.next_sibling
+            while next_element and next_element.name != 'h2':
+                if next_element.name == 'h3':
+                    h3_tags.append(next_element)
+                next_element = next_element.next_sibling
+            
+            for h3 in h3_tags:
+                description = h3.text.strip()
+                print(f"Found description: {description}")
+                
+                # Find the next sibling elements until the next h3 or h2
+                next_element = h3.next_sibling
+                policy_url = ''
+                severity = ''
+                type_info = ''
+                additional_info = []
+                
+                while next_element and next_element.name not in ['h3', 'h2']:
+                    if isinstance(next_element, str):
+                        text = next_element.strip()
+                        if text:
+                            additional_info.append(text)
+                    elif next_element.name in ['p', 'li']:
+                        text = next_element.text.strip()
+                        if text:
+                            additional_info.append(text)
+                    
+                    next_element = next_element.next_sibling
+                
+                # Join additional info and search for severity, type, and policy URL
+                additional_text = ' '.join(additional_info)
+                
+                severity_match = re.search(r'Severity:\s*(\w+)', additional_text)
+                if severity_match:
+                    severity = severity_match.group(1)
+                    print(f"Found severity: {severity}")
+                
+                type_match = re.search(r'Type:\s*(.+?)(?=\n|$)', additional_text)
+                if type_match:
+                    type_info = type_match.group(1).strip()
+                    print(f"Found type: {type_info}")
+                
+                # Extract policy URL
+                policy_match = re.search(r'Related policy: \[.+?\]\((https://portal\.azure\.com/#blade/Microsoft_Azure_Policy/PolicyDetailBlade/definitionId/[^)]+)\)', additional_text)
+                if policy_match:
+                    policy_url = policy_match.group(1)
+                    print(f"Found policy URL: {policy_url}")
+                
+                recommendations.append({
+                    'name': name,
+                    'description': description,
+                    'policy_url': policy_url,
+                    'severity': severity,
+                    'type': type_info
+                })
+        
+        return recommendations
+    except Exception as e:
+        print(f"Error parsing page {url}: {str(e)}")
+        return None
+
+# URL of the TOC.yml file
+toc_url = "https://raw.githubusercontent.com/MicrosoftDocs/azure-security-docs/refs/heads/main/articles/defender-for-cloud/TOC.yml"
+
+# Parse the TOC and get recommendations
+recommendation_items = parse_toc(toc_url)
+
+if not recommendation_items:
+    print("No recommendation items found. Exiting.")
+    exit()
+
+# Prepare CSV file
+csv_filename = 'recommendations.csv'
+csv_headers = ['Name', 'Description', 'Policy URL', 'Severity', 'Type']
+
+with open(csv_filename, 'w', newline='', encoding='utf-8') as csvfile:
+    writer = csv.DictWriter(csvfile, fieldnames=csv_headers)
+    writer.writeheader()
+
+    for item in recommendation_items:
+        page_url = f"https://raw.githubusercontent.com/MicrosoftDocs/azure-security-docs/refs/heads/main/articles/defender-for-cloud/{item['href']}"
+        page_data = parse_recommendation_page(page_url)
+        
+        if page_data:
+            for recommendation in page_data:
+                writer.writerow({
+                    'Name': recommendation['name'],
+                    'Description': recommendation['description'],
+                    'Policy URL': recommendation['policy_url'],
+                    'Severity': recommendation['severity'],
+                    'Type': recommendation['type']
+                })
+                print(f"Processed and wrote to CSV: {recommendation['description']}")
+        else:
+            print(f"Failed to process: {item['name']}")
+        
+        time.sleep(1)
+
+print(f"CSV file '{csv_filename}' has been created with the extracted information.")