« Back to Home

Advanced AWS S3 Bucket Vulnerability Scanner Python Script

☁️ Cloud Infrastructure & AWS S3 Bucket Security Scanner (Python Tool)

Welcome to Technical AI! In the modern digital landscape, the majority of web applications are hosted on cloud infrastructures like Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure. However, misconfigured Cloud Storage (like AWS S3 Buckets) is the #1 cause of massive enterprise data leaks.

Using our exclusive Ubuntu Terminal Emulator, you can run a simulated Python automation script to audit cloud environments. Detect open storage buckets, exposed API keys, and insecure IAM policies instantly from your browser.

⚡ Features of the Cloud Audit Script

This automated toolkit conducts a deep forensic analysis of cloud environments:

  • Cloud Provider Fingerprinting: Detects whether the infrastructure is hosted on AWS, GCP, or Azure.
  • S3 Bucket Permission Scan: Checks for insecure "Public Read/Write" access on cloud storage.
  • API Key Exposure Check: Audits the environment for leaked configuration endpoints.
  • Zero-Dependency Execution: Runs seamlessly in our web-terminal sandbox.

🚀 How to Run the Cloud Scanner

  1. Click the "Copy Code" button on the Python script box below.
  2. Open the "Ubuntu Terminal" from the top navigation bar.
  3. Right-click (or tap and hold) inside the terminal and select Paste.
  4. Press Enter to initiate the automated cloud vulnerability assessment!
Cloud_Bucket_Auditor.py 
import time

def run_cloud_scanner():
    print("=======================================================")
    print(" ☁️ ADVANCED CLOUD INFRASTRUCTURE & S3 BUCKET AUDITOR")
    print("=======================================================")
    
    target_app = "production-app-server"
    print(f"\n[SYSTEM] Connecting to Cloud API Endpoints for: {target_app}\n")
    time.sleep(1.5)
    
    # CLOUD FINGERPRINTING PHASE
    print("[+] PHASE 1: Cloud Provider Fingerprinting")
    time.sleep(1)
    print("  [*] Analyzing DNS CNAME and Routing Headers...")
    time.sleep(1.5)
    print("  ✅ Infrastructure Detected : Amazon Web Services (AWS)")
    print("  📡 Primary Region         : us-east-1 (N. Virginia)")
    print("  🖥️ EC2 Instance Type      : t3.xlarge (Verified)")
    
    time.sleep(2)

    # S3 BUCKET AUDIT PHASE
    print("\n[+] PHASE 2: AWS S3 Storage Bucket Vulnerability Scan")
    time.sleep(1)
    print("  [*] Probing storage endpoints for Public Access Misconfigurations...")
    time.sleep(2)
    
    buckets = [
        {"name": "assets-prod-bkt", "status": "SECURE (Private)", "color": "✅"},
        {"name": "backup-logs-bkt", "status": "SECURE (Private)", "color": "✅"},
        {"name": "user-uploads-tmp", "status": "VULNERABLE (Public Read/Write)", "color": "🚨"}
    ]
    
    for b in buckets:
        print(f"  {b['color']} Bucket: {b['name'].ljust(20)} -> {b['status']}")
        time.sleep(0.8)

    time.sleep(1.5)
    
    # API KEY EXPOSURE PHASE
    print("\n[+] PHASE 3: Environment Variables & API Key Exposure")
    time.sleep(1)
    print("  [*] Auditing .env files and config endpoints...")
    time.sleep(1.5)
    print("  ✅ AWS_ACCESS_KEY_ID      : Hidden (Secure)")
    print("  ✅ AWS_SECRET_ACCESS_KEY  : Hidden (Secure)")
    print("  🚨 STRIPE_TEST_KEY        : EXPOSED (Information Leak Detected!)")

    time.sleep(1)
    print("\n[+] PHASE 4: Final Security Recommendation")
    print("  [!] CRITICAL: The 'user-uploads-tmp' S3 Bucket is publicly writable.")
    print("  [!] ACTION: Update AWS IAM Policies immediately to prevent data tampering.")

    print("\n✅ CLOUD SECURITY AUDIT COMPLETE. (Terminal Safe Execution)")
    print("=======================================================")

if __name__ == "__main__":
    run_cloud_scanner()

Disclaimer: This is a browser-safe demonstration toolkit strictly for educational and compliance auditing purposes. It operates within simulated parameters to prevent CORS limitations and does not perform actual unauthorized access.