Web Hacking Incidents Revealed: Trends, Stats and How to Defend. Ryan Barnett Senior Security Researcher SpiderLabs Research

Transcription

1 Web Hacking Incidents Revealed: Trends, Stats and How to Defend Ryan Barnett Senior Security Researcher SpiderLabs Research

2 Ryan Barnett - Background Trustwave Senior Security Researcher Web application firewall research/development Virtual patching for web applications Member of the SpiderLabs Research Team Web application firewall signature lead ModSecurity Community Manager Interface with the community on public mail-list Steer the internal development of ModSecurity Author Preventing Web Attacks with Apache

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

4 Session Outline The Challenge of Risk Analysis for Web Applications Risk Rating Methodology How to quantify risk? WASC Web Hacking Incident Database (WHID) What is it? Goals Recent Project Changes and Updates 2010 Semiannual Report (July December) Incidents By Attacked Entity Field Incidents By Outcome Incidents By Attack Methods Incidents By Application Weakness Comparing the OWASP Top 10 vs. the WHID Top 10 Incidents of Interest Conclusion

5 The Challenge of Risk Analysis for Web Application Security

6 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

7 OWASP Risk Rating Methodology

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

9 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)

10 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

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12 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

13 Web Hacking Incident Database (WHID)

14 WASC Web Hacking Incident Database (WHID)

15 Tracking Public Web Compromises

16 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

17 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

18 WHID Data: Community Submittal Form Community incident submission leverages crowdsourcing Project team validation ensures quality

19 WHID Database Content ~222 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

20 Real-Time Statistics Browse real-time data Drill down in to incident details Pivot on key variables (year/vertical market)

21 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

22 Geographic Views

23 Monitoring WHID Updates

24 WHID 2010 Biannual Status Report: July-December

25 What Vertical Markets are Attacked Most Often?

26 What are the Goals for Web Hacking?

27 What Attack Methods do Hackers Use?

28 Which Application Weaknesses are Exploited?

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

30 OWASP vs. WHID Top 10 OWASP Top 10 WHID Top 10 1 Injection Insufficient Anti-Automation (Brute Force and DoS) 2 Cross-site Scripting (XSS) 3 Broken Authentication and Session Management 4 Insecure Direct Object Reference 5 CSRF 6 Security Misconfiguration 7 Insecure Cryptographic Storage Improper Output Handling (XSS and Planting of Malware) Improper Input Handling (SQL Injection) Application Misconfiguration (Detailed error messages) Insufficient Authentication (Stolen Credentials/Banking Trojans) Insufficient Process Validation (CSRF and DNS Hijacking) Insufficient Authorization (Predictable Resource Location/Forceful Browsing) 8 Failure to Restrict URL Access Abuse of Functionality (CSRF/Click-Fraud) 9 Insecure Transport Layer Protection Insufficient Password Recovery (Brute Force) 1 0 Unvalidated Redirects and Forwards Improper Filesystem Permissions (info Leakages)

31 Top Trends

32 Denial of Service

33 Layer 4 DDoS Attacks

34 Layer 4 DDoS Attacks - Botnets Reach bandwidth or connection limits of hosts or networking equipment. Fortunately, current anti- DDOS solutions are effective in handling Layer 4 DDOS attacks. 34

35 Layer 7 DDoS Attacks

36 Layer 7 DDoS Attacks Legitimate TCP or UDP connections. Difficult to differentiate from legitimate users => higher obscurity. Requires lesser number of connections => higher efficiency. Reach resource limits of services. Can deny services regardless of hardware capabilities of host => higher lethality. We will focus on protocol weaknesses of HTTP or HTTPS. HTTP GET => Michal Zalewski, Adrian Ilarion Ciobanu, RSnake (Slowloris) HTTP POST => Wong Onn Chee

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40 Application Performance Monitoring Dashboard

41 Excessive Access Rate Detection

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43 Cross-site Scripting (XSS) Defense

44 Banking Trojans

45 Questions?