XSS filter on Server side

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project for the final year of engineering …

project for the final year of engineering
.to create a signature based model on server side
to prevent XSS attacks

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  • 1. MITIGATION OF XSS USING SIGNATURE BASED MODEL ON SERVER SIDE SEMINAR BY Dhanashree Waikar Abhijeet Kate Shailesh Khachane GUIDED BY Mrs. M.A. Pradhan (Head Of Department)
  • 2. XSS ? ? ? ? (Cross Site Scripting)
    • Allow code injection by malicious web users
    • XSS attacks the end user -- it runs arbitrary code in their browser.
    • The browser is behind your firewall and is acting within the user’s security context
  • 3. JavaScript power
    • JavaScript can control what appears on screen.
    • JavaScript has access to your history.
    • Sites often store session tokens in GET request.
    • JavaScript can intercept cookies.
    • JavaScript can enumerate your network.
  • 4. EXAMPLE
    • Code:- <script>alert(&quot;/XSS&quot;/)</script> <script>alert(&quot;XSS&quot;)</script> <script>alert(&quot;XSS&quot;)</script>; <script>alert(String.fromCharCode(88,83,83))</script>
    • Effect
  • 5. Available options to prevent XSS attacks
    • Signature Based
      • Positive signature
      • Negative signature
    • Behavior based
    • Client side or server side
  • 6. Signature based model
    • Prevention using negative signature based model
    • Configurable black listed tags
    • Placed at the top most layer of the web application.
    • Recognized attacks are blocked
  • 7. Modules for xss prevation
    • Blocker
    • Parser
    • Validator
    • Tag cluster
  • 8.
    • Blocker
      • Checks for the existence of special characters
      • For example ‘<’, ‘>’, ‘%’, ‘&’, ‘, ‘&#’ are few of the special characters used to embed JavaScript functions in the tags
      • Blocker is responsible to allow or to reject the input string from the user
      • According to the status which it receives from validator
  • 9.
    • Parser
      • Called by the Blocker
      • Breaks the input into multiple tokens, as tags and attributes
      • Stores it as a element in a vector object
      • The vector object created by the parser component which invokes the validator
      • For <img src=http://www.sample.com/image1.gif>
      • The vector elements are
        • img, src=http://www.sample.com/image1.gif
  • 10.
    • Validator
      • Checks input for vulnarability by executing the rules using the tag cluster
      • Compares tags or attributes of input script
      • If mached then marked as vulnabrable
      • Verifier()
      • detectMalicious()
  • 11.
    • Tag cluster
      • The prohibited tags and the prohibited attributes of tags are categorized as black listed cluster
      • Rules for vulnerability identification
  • 12.
    • Flow diagram
  • 13. Future Enhancements
    • modular based .
    • Modules for Other web application attacks can be added easily.
    • E.g. sql injection, Buffer-overflow attacks
    • Updates can be provided for the tag cluster
  • 14. Limitations
    • Only known attacks can be blocked
    • Web application’s response performance is reduced.
  • 15. Conclusion
    • The presented server side solution
    • approach meets the need to protect the web
    • Applications with the perspective to improve the response time while addressing the XSS attacks
  • 16. References
    • 1. G. A. Di Lucca, A. R. Fasolino, M. Mastoianni, P. Tramontana, &quot;Identifying Cross Site Scripting Vulnerabilities in Web Applications,&quot; Sixth IEEE International Workshop on Web Site Evolution(WSE'04) , pp. 71-80, , 2004.
    • 2. M. M. Burnett and J. C. Foster, “Hacking the Code: ASP.NET Web Application Security,” Chapter 5 - Filtering User Input, Syngress Publishing © 2004
    • 3. Scott, D., Sharp, R. “Developing Secure Web Applications.” IEEEInternet Computing, 6(6), pp. 38-45, Nov 2002.
    • 4. Jin-Cherng Lin, Jan-Min Chen, &quot;An Automatic Revised Tool for Anti-Malicious Injection,&quot; cit, p. 164, Sixth IEEE International Conference on Computer and Information Technology (CIT'06), 2006.
    • 5. Zhendong Su, Gary Wassermann, “The essence of command injection attacks in web applications,” Annual Symposium on Principles of Programming Languages, Conference record of the 33rd ACM SIGPLAN-SIGACT symposium on Principles
    • 6. Christopher Krugel, G.Vigna, William Robertson, “A multimodel approach to the detection of web based attacks,”Computer Networks 48 (2005) pp.717-738 – ELSEVIER, 2005.
  • 17. Thank you
    • We would like to specially thank
    • Mrs. M. A. Pradhan madam ,
    • Mrs. Vaishali Vairale madam,
    • and all respected teachers for
    • their continuous help and support.
  • 18.
    • THANK YOU
  • 19.
    • QUESTIONS