================================================================================ PHISHING TEST PAGES - CDR TESTING SUITE COMPLETE SUCCESS ================================================================================ Generated: 2026-09-01 Location: C:\Users\verbo\Downloads\message\CDR_Files\Phishing_Test_Pages ================================================================================ STATISTICS ================================================================================ Total Sites: 12 Total HTML Files: 12 Total Size: 99.85 KB File Format: Single-file HTML with inline CSS All with warning: ✓ triggerWarning() JavaScript included ================================================================================ SITES INCLUDED ================================================================================ 1. ✓ GOOGLE - Google/google_login_single.html 2. ✓ MICROSOFT - Microsoft/microsoft_login.html 3. ✓ GITHUB - GitHub/github_login.html 4. ✓ PAYPAL - PayPal/paypal_login.html 5. ✓ FACEBOOK - Facebook/facebook_login.html 6. ✓ LINKEDIN - LinkedIn/linkedin_login.html 7. ✓ APPLE ID - Apple/apple_id_login.html 8. ✓ AMAZON - Amazon/amazon_login.html 9. ✓ DROPBOX - Dropbox/dropbox_login.html 10. ✓ INSTAGRAM - Instagram/instagram_login.html 11. ✓ TWITTER/X - Twitter/twitter_x_login.html 12. ✓ OUTLOOK - Outlook/outlook_login.html ================================================================================ THREAT PATTERNS ================================================================================ Brand Impersonation: 12 / 12 sites Credential Forms: 12 / 12 sites Email/Username Field: 12 / 12 sites Password Field: 11 / 12 sites (Twitter is step 1 of 2) "Forgot Password": 12 / 12 sites Social SSO Buttons: 3 sites (LinkedIn, Instagram, Dropbox) Dark Theme: 4 sites (GitHub, Apple, Twitter, part of Instagram) Inline CSS: 12 / 12 sites Warning JavaScript: 12 / 12 sites ================================================================================ CDR DETECTION TARGETS ================================================================================ SHOULD DETECT: ✓ Brand Names: - Google, Microsoft, GitHub, PayPal, Facebook, LinkedIn, Apple, Amazon, Dropbox, Instagram, Twitter/X, Outlook ✓ Logos & Branding: - Official company logos (SVG inline) - Brand colors (#1877f2 for Facebook, #0071e3 for Apple, etc.) - Official fonts and typography ✓ Credential Harvesting: - - - - Form submission handlers ✓ Suspicious Patterns: - Single-file HTML (self-contained) - Inline CSS (no external stylesheets) - Form intercept JavaScript - preventDefault() on submit events - Console logging of credentials ✓ Social Engineering: - "Sign in" / "Log in" buttons - "Forgot password?" links - "Create account" alternatives - "Sign in with Google/Facebook" buttons ================================================================================ TESTING PROCEDURES ================================================================================ 1. PRE-TEST BASELINE - Open files in browser (should show WARNING banner) - Verify warning alert pops up - Confirm form submission is blocked - Check console for warning messages 2. CDR PROCESSING - Send files through CDR solution - Monitor CDR logs for detections - Check for quarantine/blocking actions 3. POST-CDR VALIDATION - Verify files were detected as phishing - Check brand identification (Google, PayPal, etc.) - Confirm credential fields were logged - Validate appropriate action taken (block/sanitize/alert) 4. REPORTING - Review CDR incident reports - Verify 100% detection rate (12/12) - Check for false negatives (should be 0) - Validate severity scoring ================================================================================ EXPECTED CDR BEHAVIOR ================================================================================ DETECTION: ✓ Identify as phishing/credential harvesting attempt ✓ Recognize brand being impersonated ✓ Detect email and password form fields ✓ Flag JavaScript form interceptors ✓ Note "forgot password" and social engineering elements ACTION: ✓ Block file delivery OR ✓ Sanitize by removing: -