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Google Dorks: Analysis,
Creation, and new Defenses
Flavio Toffalini, University of Verona, IT, flavio.toffalini@gmail.com
Maurizio Abbà, LastLine, UK, mabba@lastline.com
Damiano Carra, University of Verona, IT, damiano.carra@univr.it
Davide Balzarotti, Eurecom, FR, davide.balzarotti@eurecom.fr
2
GOOGLE DORKS
3
MOTIVATION
● Attackers use Dorks to quickly locate targets
● After a new vulnerability is disclosed, one Google query is
sufficient to identify a large amount of vulnerable installations
● No time for sysadmins to apply patches !!
4
MOTIVATION
● Attackers use Dorks to quickly locate targets
● After a new vulnerability is disclosed, one Google query is
sufficient to identify a large amount of vulnerable installations
● No time for sysadmins to apply patches !!
● If we could prevent dorks, attackers would need to
resort to Internet scanning … which is several orders
of magnitude slower
5
GOALS
● Current practices
● Understand which information is used by existing dorks
● Design simple solutions to defeat those dorks
● Future threats
● Test if attackers could move towards new styles of dorks
● Design simple solutions to prevent it
6
GOOGLE DORKS
7
TAXONOMY
● The Exploit-DB database contains over 5143 dorks
● Automated/manual analysis
URL Patterns (44%)
File Extensions (6%)
Content-Based (74%)
8
● The Exploit-DB database contains over 5143 dorks
● Automated/manual analysis
URL Patterns (44%)
File Extensions (6%)
Content-Based
Banners (54%)
Misconfigurations (8%)
Error messages (1%)
Common words (11%)
TAXONOMY
10
DORKS EVOLUTION BY CATEGORY
URL Patterns
Banner
Common words
Misconfiguration
11
KNOWN DEFENSES
URL Patterns
File Extensions
Content-Based
Banners remove banners
Misconfigurations improve system configuration
Error messages proper error handling
Common words
12
CONTRIBUTION
URL Patterns ??
File Extensions
Content-Based
Banners remove banners
Misconfigurations improve system configuration
Error messages proper error handling
Common words
??
13
● Force search engines to index “randomized” URLs
● Let the users navigate and share using cleartext URLs
http://www.web-site.com/wp-content/dimva.html
http://www.web-site.com/HD12DAF35TR/dimva.html
URL-DORKS
14
● XOR (part of) URLs with random seed kept in the server
a = resource a
O(a) = obfuscated resource a
● Redirect 301 to inform search engine that the page is moved
● Canonical URL Tag to delete plain URLs in the results
● Intercept and replace SiteMap
URL-DORKS
15
OBFUSCATION PROTOCOL - CRAWLERS
Crawler URL Obfuscator Web Site
a
a
resp. of a
Redir. 301 to O(a)
O(a)
resp. of a + canonical tag
16
OBFUSCATION PROTOCOL - BROWSER
Browser URL Obfuscator Web Site
O(a)
a
resp. of a
resp. of a
b
resp. of b resp. of b
b
17
URL Patterns
File Extensions
Content-Based
Banners remove banners
Misconfigurations improve system configuration
Error messages proper error handling
Common words
??
18
WORD-BASED DORKS
● Goal
● Using words left by CMSs to create a Google Dork
● Greedy search algorithm to maximizes
● Hit-rank: percentage of web site made by a target technology
● Coverage: number of entries extracted by the Dork
19
WORD-BASED DORKS: CREATION
Joomla!
20
“Category” +
“Submit” +
“....”
Vanilla
installation
WORD-BASED DORKS: CREATION
Categories
SubmitRegister
Contact
Buy
Recent
Users
List
Registration
Compute hit rank
& coverage
22
WORD-BASED DORKS: CREATION
● Gradient Ascent algorithm
● How to add a new word?
● At each step, we add the word that provides the highest hit
rank between the ones that have a coverage above the
median of all candidate words
(more details in the paper)
24
Common Words Ground Truth
WordPress 938/1000 967/1000 Hit rank
47.1 M 83.6 M Coverage
Joomla! 878/1000 887/1000 Hit rank
7.24 M 3.73 M Coverage
Drupal 827/1000 997/1000 Hit rank
7.87 M 3.27 M Coverage
Magento 871/1000 852/1000 Hit rank
0.39 M 0.68 M Coverage
OpenCart 891/1000 998/1000 Hit rank
0.59 M 1.42 M Coverage
WORD-BASED DORKS:
25
Common Words Ground Truth
WordPress 938/1000 967/1000 Hit rank
47.1 M 83.6 M Coverage
Joomla! 878/1000 887/1000 Hit rank
7.24 M 3.73 M Coverage
Drupal 827/1000 997/1000 Hit rank
7.87 M 3.27 M Coverage
Magento 871/1000 852/1000 Hit rank
0.39 M 0.68 M Coverage
OpenCart 891/1000 998/1000 Hit rank
0.59 M 1.42 M Coverage
WORD-BASED DORKS:
26
Common Words Ground Truth
WordPress 938/1000 967/1000 Hit rank
47.1 M 83.6 M Coverage
Joomla! 878/1000 887/1000 Hit rank
7.24 M 3.73 M Coverage
Drupal 827/1000 997/1000 Hit rank
7.87 M 3.27 M Coverage
Magento 871/1000 852/1000 Hit rank
0.39 M 0.68 M Coverage
OpenCart 891/1000 998/1000 Hit rank
0.59 M 1.42 M Coverage
WORD-BASED DORKS:
29
Idea: add invisible characters to break words and
prevent them to be indexed.
WORD-BASED DORKS: DEFENSES
Powered by WordPress
Power⁣ed b⁣y Wor⁣dPress
30
DORKS DEFENSES
URL Patterns
File Extensions
Content-Based
Banners remove banners
Misconfigurations improve system configuration
Error messages proper error handling
Common words
31
CONCLUSION
1) Dork classification
2) URL Pattern Dork Defense
3) New type of Dork using common words
4) Defense against common word dorks

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Google Dorks: Analysis, Creation, and new Defenses

  • 1. Google Dorks: Analysis, Creation, and new Defenses Flavio Toffalini, University of Verona, IT, flavio.toffalini@gmail.com Maurizio Abbà, LastLine, UK, mabba@lastline.com Damiano Carra, University of Verona, IT, damiano.carra@univr.it Davide Balzarotti, Eurecom, FR, davide.balzarotti@eurecom.fr
  • 3. 3 MOTIVATION ● Attackers use Dorks to quickly locate targets ● After a new vulnerability is disclosed, one Google query is sufficient to identify a large amount of vulnerable installations ● No time for sysadmins to apply patches !!
  • 4. 4 MOTIVATION ● Attackers use Dorks to quickly locate targets ● After a new vulnerability is disclosed, one Google query is sufficient to identify a large amount of vulnerable installations ● No time for sysadmins to apply patches !! ● If we could prevent dorks, attackers would need to resort to Internet scanning … which is several orders of magnitude slower
  • 5. 5 GOALS ● Current practices ● Understand which information is used by existing dorks ● Design simple solutions to defeat those dorks ● Future threats ● Test if attackers could move towards new styles of dorks ● Design simple solutions to prevent it
  • 7. 7 TAXONOMY ● The Exploit-DB database contains over 5143 dorks ● Automated/manual analysis URL Patterns (44%) File Extensions (6%) Content-Based (74%)
  • 8. 8 ● The Exploit-DB database contains over 5143 dorks ● Automated/manual analysis URL Patterns (44%) File Extensions (6%) Content-Based Banners (54%) Misconfigurations (8%) Error messages (1%) Common words (11%) TAXONOMY
  • 9. 10 DORKS EVOLUTION BY CATEGORY URL Patterns Banner Common words Misconfiguration
  • 10. 11 KNOWN DEFENSES URL Patterns File Extensions Content-Based Banners remove banners Misconfigurations improve system configuration Error messages proper error handling Common words
  • 11. 12 CONTRIBUTION URL Patterns ?? File Extensions Content-Based Banners remove banners Misconfigurations improve system configuration Error messages proper error handling Common words ??
  • 12. 13 ● Force search engines to index “randomized” URLs ● Let the users navigate and share using cleartext URLs http://www.web-site.com/wp-content/dimva.html http://www.web-site.com/HD12DAF35TR/dimva.html URL-DORKS
  • 13. 14 ● XOR (part of) URLs with random seed kept in the server a = resource a O(a) = obfuscated resource a ● Redirect 301 to inform search engine that the page is moved ● Canonical URL Tag to delete plain URLs in the results ● Intercept and replace SiteMap URL-DORKS
  • 14. 15 OBFUSCATION PROTOCOL - CRAWLERS Crawler URL Obfuscator Web Site a a resp. of a Redir. 301 to O(a) O(a) resp. of a + canonical tag
  • 15. 16 OBFUSCATION PROTOCOL - BROWSER Browser URL Obfuscator Web Site O(a) a resp. of a resp. of a b resp. of b resp. of b b
  • 16. 17 URL Patterns File Extensions Content-Based Banners remove banners Misconfigurations improve system configuration Error messages proper error handling Common words ??
  • 17. 18 WORD-BASED DORKS ● Goal ● Using words left by CMSs to create a Google Dork ● Greedy search algorithm to maximizes ● Hit-rank: percentage of web site made by a target technology ● Coverage: number of entries extracted by the Dork
  • 19. 20 “Category” + “Submit” + “....” Vanilla installation WORD-BASED DORKS: CREATION Categories SubmitRegister Contact Buy Recent Users List Registration Compute hit rank & coverage
  • 20. 22 WORD-BASED DORKS: CREATION ● Gradient Ascent algorithm ● How to add a new word? ● At each step, we add the word that provides the highest hit rank between the ones that have a coverage above the median of all candidate words (more details in the paper)
  • 21. 24 Common Words Ground Truth WordPress 938/1000 967/1000 Hit rank 47.1 M 83.6 M Coverage Joomla! 878/1000 887/1000 Hit rank 7.24 M 3.73 M Coverage Drupal 827/1000 997/1000 Hit rank 7.87 M 3.27 M Coverage Magento 871/1000 852/1000 Hit rank 0.39 M 0.68 M Coverage OpenCart 891/1000 998/1000 Hit rank 0.59 M 1.42 M Coverage WORD-BASED DORKS:
  • 22. 25 Common Words Ground Truth WordPress 938/1000 967/1000 Hit rank 47.1 M 83.6 M Coverage Joomla! 878/1000 887/1000 Hit rank 7.24 M 3.73 M Coverage Drupal 827/1000 997/1000 Hit rank 7.87 M 3.27 M Coverage Magento 871/1000 852/1000 Hit rank 0.39 M 0.68 M Coverage OpenCart 891/1000 998/1000 Hit rank 0.59 M 1.42 M Coverage WORD-BASED DORKS:
  • 23. 26 Common Words Ground Truth WordPress 938/1000 967/1000 Hit rank 47.1 M 83.6 M Coverage Joomla! 878/1000 887/1000 Hit rank 7.24 M 3.73 M Coverage Drupal 827/1000 997/1000 Hit rank 7.87 M 3.27 M Coverage Magento 871/1000 852/1000 Hit rank 0.39 M 0.68 M Coverage OpenCart 891/1000 998/1000 Hit rank 0.59 M 1.42 M Coverage WORD-BASED DORKS:
  • 24. 29 Idea: add invisible characters to break words and prevent them to be indexed. WORD-BASED DORKS: DEFENSES Powered by WordPress Power⁣ed b⁣y Wor⁣dPress
  • 25. 30 DORKS DEFENSES URL Patterns File Extensions Content-Based Banners remove banners Misconfigurations improve system configuration Error messages proper error handling Common words
  • 26. 31 CONCLUSION 1) Dork classification 2) URL Pattern Dork Defense 3) New type of Dork using common words 4) Defense against common word dorks