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The Web Hacking Incident Database (WHID) Report for 2010

The Web Hacking Incident Database (WHID) Report for 2010. Ryan Barnett WASC WHID Project Leader Senior Security Researcher. Ryan Barnett - Background. Trustwave SpiderLabs Research Team Web application firewall research/development ModSecurity Community Manager

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The Web Hacking Incident Database (WHID) Report for 2010

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  1. The Web Hacking Incident Database (WHID) Report for 2010 • Ryan Barnett • WASC WHID Project Leader • Senior Security Researcher

  2. Ryan Barnett - Background • Trustwave • SpiderLabs Research Team • Web application firewall research/development • ModSecurity Community Manager • Interface with the community on public mail-list • Steer the internal development of ModSecurity • Author • “Preventing Web Attacks with Apache”

  3. Community Projects • Open Web Application Security Project (OWASP) • Project Leader, ModSecurity Core Rule Set • Project Contributor, OWASP Top 10 • Project Contributor, AppSensor • Web Application Security Consortium (WASC) • Project Leader, Web Hacking Incident Database • Project Leader, Distributed Web Honeypots • Project Contributor, Web Application Firewall Evaluation Criteria • Project Contributor, Threat Classification • The SANS Institute • Courseware Developer/Certified Instructor • Project Contributor, CWE/SANS Top 25 Worst Programming Errors

  4. Session Outline • OWASP Risk Rating Methodology • The Challenge of Risk Analysis for Web Applications • WASC Web Hacking Incident Database (WHID) Overview • 2010 Status Report • Top Trends • Comparing the OWASP Top 10 vs. the WHID Top 10

  5. OWASP Risk Rating Methodology • #Step 1: Identifying a Risk • #Step 2: Factors for Estimating Likelihood • #Step 3: Factors for Estimating Impact • #Step 4: Determining Severity of the Risk • #Step 5: Deciding What to Fix • #Step 6: Customizing Your Risk Rating Model http://www.owasp.org/index.php/OWASP_Risk_Rating_Methodology

  6. OWASP Risk Rating Methodology

  7. The Challenge of Risk Analysis for Web Applications: Analyzing Public Incidents

  8. Risk Rating Problem Instead of being concerned about what CAN happen (theoretical scenarios), perhaps we should first be dealing with what IS happening (analysis of real-world web compromises)…

  9. Publicly Quantifying Web Incidents is Challenging • Incidents are not detected • ~156 day lapse between compromise and detection* • Vast majority of cases the merchant did not identify the intrusion – a 3rd party did based on fraud detection (card brands and banks)* • Logging Issues - poor logging and/or no one reviewing them for signs of compromise https://www.trustwave.com/downloads/whitepapers/Trustwave_WP_Global_Security_Report_2010.pdf

  10. Publicly Quantifying Web Incidents is Challenging • Victims hide breaches • Defacement (visible) and information leakage (regulated) are publicized more than other breaches • Example - Banks are not forced to disclose when individual customer funds are stolen

  11. Web Hacking Incident Database (WHID)

  12. WASC Web Hacking Incident Database (WHID) http://projects.webappsec.org/Web-Hacking-Incident-Database

  13. Tracking Public Web Compromises

  14. WHID Goals • Raise awareness of real-world, web application security incidents • Provide data for the following Risk Rating steps: • #Step 2: Factors for Estimating Likelihood • What application weaknesses are actively being targeted? • #Step 3: Factors for Estimating Impact • What outcome are you worried about? • #Step 5: Deciding What to Fix • Prioritized listing of remediation issues • #Step 6: Customizing Your Risk Rating Model • Customized view based on your vertical-market

  15. WHID Data • Data Samples (statistically insignificant) • Focus on % rather than raw numbers • Inclusion Criteria • Only publicly disclosed, web related incidents • Incidents of interest • Defacements of “High Profile” sites are included • Ensure quality and correctness of incidents • Severely limits the number of incidents that get in

  16. WHID Data: Community Submittal Form • Community incident submission leverages crowdsourcing • Project team validation ensures quality http://projects.webappsec.org/Web-Hacking-Incident-Database#SubmitanIncident

  17. WHID Database Content • ~216 incidents for 2010 • Incidents since 1999 • Each incident is classified • Attack type • Application Weakness • Outcome • Country of organization attacked • Industry segment of organization attacked • Country of origin of the attack (if known) • Vulnerable Software • Additional information: • A unique identifier: WHID 200x-yy • Dates of occurrence and reporting • Description • Internet references

  18. Real-Time Statistics • Browse real-time data • Drill down in to incident details • Pivot on key variables (year/vertical market) http://projects.webappsec.org/Web-Hacking-Incident-Database

  19. Real-time, Searchable DB • WHID data is available year-round • Useful for application developers and researchers • Search by • Attack method • Outcome • Source geography • and many more… http://projects.webappsec.org/Web-Hacking-Incident-Database#SearchtheWHIDDatabase

  20. Geographic Views

  21. Monitoring WHID Updates http://projects.webappsec.org/Web-Hacking-Incident-Database#RSSFeed @wascwhid

  22. WHID 2010 Status Report

  23. What Vertical Markets are Attacked Most Often?

  24. What are the Goals for Web Hacking?

  25. What Attack Methods do Hackers Use?

  26. Which Application Weaknesses are Exploited?

  27. Top Trends

  28. Denial of Service

  29. Banking Trojans

  30. #Step 5: Deciding What to Fix Prioritized listing of remediation issues

  31. OWASP vs. WHID Top 10

  32. Questions? • WASC WHID Project Site • http://projects.webappsec.org/w/page/Web-Hacking-Incident-Database • Email – Ryan.Barnett@owasp.org • Twitter - @ryancbarnett

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