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Web Application Security Statistics

Page history last edited by Sergey Gordeychik 10 years, 6 months ago

Download pdf version

Download Security Statistics 2007

 

Table of content

 


 

 

 

Purpose

 

The Web Application Security Consortium (WASC) is pleased to announce the WASC Web Application Security Statistics Project 2008. This initiative is a collaborative industry wide effort to pool together sanitized website vulnerability data and to gain a better understanding about the web application vulnerability landscape. We ascertain which classes of attacks are the most prevalent regardless of the methodology used to identify them. Industry statistics such as those compiled by Mitre CVE project provide valuable insight into the types of vulnerabilities discovered in open source and commercial applications, this project tries to be the equivalent for custom web applications.

Goals

 

  1. Identify the prevalence and probability of different vulnerability classes.
  2. Compare testing methodologies against what types of vulnerabilities they are likely to identify.

 

Project Leader

 

If you represent an organization that performs vulnerability assessments on websites, particular in those in custom web applications, through a manual or automated process and would like to participate please let us know. Once statistics are compiled, a report will be distributed, and all contributors will receive a logo on the project pages as well as on other deliverables in appreciate of their contribution. Please contact Sergey Gordeychik. 

 

Project Contributors

 

 

 

Sergey Gordeychik (POSITIVE TECHNOLOGIES) Chris Wysopal (VERACODE)
Jeremiah Grossman (WHITEHAT SECURITY) Chris Eng (VERACODE)
Mandeep Khera (CENZIC) Shreeraj Shah (BLUEINFY)
Matt Lantinga (HP APPLICATION SECURITY CENTER) Lawson Lee (dns)
Campbell Murray (ENCRIPTION LIMITED) Dmitry Evteev (POSITIVE TECHNOLOGIES)

 

 

 

Methodology

 

The statistics was compiled from web application security assessment projects which were made by the following companies in 2008 (in alphabetic order):

 

This article contains Web application vulnerability statistics which was collected during penetration testing, security audits and other activities made by companies which were members of WASC in 2008. The statistics includes data about 12186 sites with 97554 detected vulnerabilities.

 

As a result, we now have 4 data sets:

  • Overall statistics by all kinds of activities;
  • Automatic scanning statistics;
  • Black box method security assessment statistics;
  • White box method security assessment statistics.

 

Automatic scanning data is collected in fully automated scanning process without any preliminary settings (with standard profile) of hosting provider sites. Remember that not all the sites include interactive elements, and additional settings made by an expert considering certain Web application, allows to greatly improve the efficiency of vulnerability detection.

Black box method security assessment statistics includes the results of manual and automated Web application analysis without any preliminary known data about the application. As a rule, this includes scanning with standard settings and manual search of vulnerabilities unavailable for automatic scanners.

White box method security assessment statistics includes the results of the deep Web application analysis which contains application analysis done as an authorized user. It also includes static source code and binary analysis. Detected vulnerabilities are classified according to Web Application Security Consortium Web Security Threat Classification (WASC WSTCv2) early draft. Vulnerability risk level is determined by contributors or assessed according to CVSSv2 (Common Vulnerability Scoring System version 2). Then the level was brought to PCI DSS (Payment Card Industry Data Security Standard) risk levels as described in the methodology (see appendix 1).

 

Summary

 

The statistics includes data about 12186 web applications with 97554 detected vulnerabilities of different risk levels. The analysis shows that more than 13%* of all reviewed sites can be compromised completely automatically. About 49% of web applications contain vulnerabilities of high risk level (Urgent and Critical) detected during automatic scanning (T. 1). However, detailed manual and automated assessment by white box method allows to detect these high risk level vulnerabilities with probability up to 80-96%. The probability to detect vulnerabilities with risk level more than medium (PCI DSS compliance level) is more than 86% by any method. At the same time, detailed analysis shows that 99% of web applications are not compliant with PCI DSS standard (T. 6, P. 13).

* Web applications with Brute Force Attack, Buffer Overflow, OS Commanding, Path Traversal, Remote File Inclusion, SSI Injection, Session Fixation, SQL Injection, Insufficient Authentication, Insufficient Authorization vulnerabilities detected by automatic scannings.

The following conclusions can be drawn based on the analysis:

  • The most wide spread vulnerabilities are Cross-site Scripting, different types of Information Leakage, SQL Injection, HTTP Response Splitting;
  • The probability to detect a urgent or critical error in dynamic web application is about 49% by automatic scanning and 96% by comprehensive expert analysis (white box method);
  • Administration issues are 20% more frequent cause of a vulnerability than system development errors;
  • 99% of web application are not compliant with PCI DSS standard requirements, and 48% of web applications are not compliant with criteria of ASV scanning by PCI DSS;
  • Detailed white box method analysis allows to detect up to 91 vulnerabilities per web application, while automatic scanning – only 3;
  • Compared to 2007, the number of sites with wide spread SQL Injection and Cross-site Scripting vulnerabilities fell by 13% and 20%, respectively, however, the number of sites with different types of Information Leakage rose by 24%. On the other hand, the probability to compromise a host automatically rose from 7 to 13 %.

 

Data analysis

 

General analysis

 

T. 1 and P. 1 show the probability to detect vulnerabilities of different risk levels detected during audits and automatic scanning.

Thus, automatic scanning detected up to 86% sites with one or some vulnerabilities of medium (or higher) risk level (Urgent-High). Black box and white box analysis methods increase it to 92-98%, respectively.

These results are greatly depend on the fact that detailed risk assessment analysis is more adequate and consider not only vulnerability type but its exploitation consequences and application design and implementation. Another important fact is that automatic scanning was made for hosting provider sites which in some cases have no active content, while security assessment is usually done for application with complicated business logic. That is that automatic scanning results can be interpret as typical Internet site scanning results, while black box and white box methods results are scanning results of interactive corporate web applications.

 

 

P. 1 The probability to detect vulnerabilities of different risk levels

 

T. 1 The probability to detect vulnerabilities of different risk levels classes

 

ALL 

Scans

BlackBox

WhiteBox

Urgent

18.77%

16.70%

19.69%

50.00%

Critical

45.22%

39.25%

74.76%

92.00%

High

72.27%

73.09%

58.51%

62.00%

Medium

36.56%

40.19%

12.05%

24.00%

Low

29.69%

34.45%

0.10%

4.00%

U+C

55.50%

49.40%

79.73%

96.00%

U+C+H

87.66%

86.30%

95.66%

98.84%

 

The most widespread vulnerabilities are Cross-Site Scripting, Information Leakage, SQL Injection, Insufficient Transport Layer Protection, Fingerprinting и HTTP Response Splitting (P. 2). As a rule, Cross-Site Scripting, SQL Injection and HTTP Response Splitting vulnerabilities are caused by design errors, while Information Leakage, Insufficient Transport Layer Protection and Fingerprinting are often caused by insufficient administration (e.g., access control).

 

 

P. 2 The most widespread vulnerabilities in web applications (% Vulns ALL)

 

 

P. 3 The probability to detect the most widespread vulnerabilities in web applications (% Sites ALL)

 

P. 4 Percent of vulnerabilities out of total number of vulnerabilities (% Vulns ALL)

If we consider vulnerability origin as a whole (according to classification in Appendix 2) we’ll see that vulnerabilities caused by insufficient administration are 20% more frequent (P. 5). At the same time, there are up to 4 issues per site caused by administration flaws and up to 8 vulnerabilities caused by design errors (T. 2).

 

T. 2 The probability to detect vulnerabilities depending on vulnerability origin

 

No. of Vulns 

No. of Sites

% Vulns

% Sites

No. Vulns on Site

Vulnerability in administration

41859

10347

42.91%

84.91%

4.05

Vulnerability in code

55695

7023

57.09%

57.63%

7.93

 

 

P. 5 The probability to detect vulnerabilities depending on their origin

 

Detailed web application analysis by black box and white box methods shows that appreciable percent of sites are vulnerable to Content Spoofing and Path Traversal (P. 6), and the probability to detect a vulnerability of SQL Injection type reaches 19% in this approach (P. 7).

 

 

P. 6 The most widespread vulnerabilities in web applications (% Vulns BlackBox & WhiteBox)

 

P. 7 The probability to detect the most widespread vulnerabilities in web applications (% Sites BlackBox & WhiteBox)

 

P. 8 Percent of vulnerabilities out of total number of vulnerabilities (% Vulns BlackBox & WhiteBox)

 

If we consider the prevalence of high risk level vulnerabilities in detailed web application analysis (P. 9) we’ll see that the most widespread is Credential/Session Prediction errors. SQL Injection, Path Traversal and implementation and configuration errors in authentication and authorization systems are also widespread.

 

P. 9 The probability to detect the most risky vulnerabilities in Web applications (% Sites BlackBox & WhiteBox)

 

If we consider the probability to detect vulnerabilities in terms of web resource visitors and web server impact (according to classification in appendix 2), the server-side vulnerabilities are the most widespread (P. 10). But the vulnerability distribution by impact type per site is irregular and greatly depends on used vulnerability search method (P. 11).

 

 

P. 10 The probability to detect vulnerability by impact type

 

P. 11.Vulnerabilities per site by different search methods (No. Vulns on Site)

T. 3 Vulnerabilities by impact

 

No. of Vulns 

No. of Sites

% Vulns

% Sites

No. Vulns on Site

ALL Stat (Server-Side)

50856

10125

52.13%

83.09%

5.02

ALL Stat (Client-Side)

46698

7580

47.87%

62.20%

6.16

Scans (Server-Side)

19746

8922

55.60%

85.40%

2.21

Scans (Client-Side)

15767

6607

44.40%

63.24%

2.39

BlackBox (Server-Side)

4260

804

23.77%

76.86%

5.30

BlackBox (Client-Side)

13665

747

76.23%

71.41%

18.29

WhiteBox (Server-Side)

17700

145

63.73%

96.67%

122.07

WhiteBox (Client-Side)

10072

117

36.27%

78.00%

86.09

 

Data analysis according to PCI DSS requirements

 

If we consider data sets about vulnerable Web applications according to PCI DSS requirements, we can easily sort (T. 4) those that are about certain vulnerability elimination in Web applications. In addition, PCI DSS Technical and Operational Requirements for Approved Scanning Vendors (ASVs) includes similar requirements but affects only ASV scanning by PCI (T. 5).

 

T. 4 PCI DSS requirements for Web application security


PCI DSS v.1.2 requirements

 Procedure 

6.5 Develop all web applications
(internal and external, and including web
administrative access to application)
based on secure coding guidelines such
as the Open Web Application Security
Project Guide. Cover prevention of
common coding vulnerabilities in
software development processes, to
include the following:

-

6.5.1 Cross-site scripting (XSS)

6.5.1 Cross-site scripting (XSS) (Validate all parameters before inclusion.)

6.5.2 Injection flaws, particularly SQL injection. Also consider LDAP and Xpath injection flaws as well as other injection flaws.

6.5.2 Injection flaws, particularly SQL injection
(Validate input to verify user data cannot modify meaning of commands and queries.)

6.5.3 Malicious file execution

6.5.3 Malicious file execution (Validate input to verify application does not accept filenames or files from users.)

6.5.5 Cross-site request forgery (CSRF)

6.5.5 Cross-site request forgery (CSRF) (Do not reply on authorization credentials and tokens automatically submitted by browsers.)

6.5.6 Information leakage and improper error handling

6.5.6 Information leakage and improper error handling (Do not leak information via error messages or other means.)

6.5.7 Broken authentication and session management

6.5.7 Broken authentication and session management (Properly authenticate users and protect account credentials and session tokens.)

6.5.9 Insecure communications

6.5.9 Insecure communications (Properly encrypt all authenticated and sensitive communications.)

6.6 For public-facing web
applications, address new threats and
vulnerabilities on an ongoing basis and
ensure these applications are protected
against known attacks by either of the
following methods:
- Reviewing public-facing web
applications via manual or
automated application vulnerability
security assessment tools or
methods, at least annually and
after any changes
- Installing a web-application firewall
in front of public-facing web
applications

-

 

T. 5 PCI DSS Technical and Operational Requirements for Approved Scanning Vendors (ASVs) for WEB


Technical and Operational Requirements for Approved Scanning Vendors (ASVs) v.1.1

 Procedure 

Web Server Check

The ASV scanning solution must be able to test for all known vulnerabilities and configuration issues on web servers. New exploits are routinely discovered in web server products. The ASV scanning solution must be able to detect and report known exploits.

Browsing of directories on a web server is not a good practice. The ASV scanning solution must be able to scan the web site and verify that directory browsing is not possible on the server.

The ASV scanning solution must be able to detect all known CGI vulnerabilities.

Custom Web Application Check

The ASV scanning solution must be able to detect the following application vulnerabilities and configuration issues:
• Unvalidated parameters which lead to SQL injection attacks
• Cross-site scripting (XSS) flaws

 

Assessing collected data statistics by criteria from T. 4 and T. 5, we conclude the following (see T. 6 and P. 12 – 14).

 

T. 6 % of sites which are not complaint to PCI DSS requirements in Web application scanning methods


PCI DSS v.1.2 requirement

Non compliant.  ALL (% Sites)

Non compliant.  Scans (% Sites)

Non compliant. BlackBox (% Sites)

Non compliant.  WhiteBox (% Sites)

6.5.1 Cross-site scripting (XSS)

38.45%

37.66%

56.41%

58.67%

6.5.2 Injection flaws. particularly SQL injection. Also consider LDAP and Xpath injection flaws as well as other injection flaws.

14.55%

12.70%

19.31%

64.00%

6.5.3 Malicious file execution

0.94%

0.08%

1.05%

8.67%

6.5.5 Cross-site request forgery (CSRF)

1.32%

0.02%

7.93%

0.67%

6.5.6 Information leakage and improper error handling

66.67%

74.05%

38.24%

54.00%

6.5.7 Broken authentication and session management

7.62%

0.52%

30.98%

71.33%

6.5.9 Insecure communications

34.42%

39.96%

0.00%*

17.33%

Technical and Operational Requirements for Approved Scanning Vendors (ASVs) v.1.1

 

 

 

 

Web Server Check

Inapplicable

5.73%

Inapplicable

Inapplicable

Custom Web Application Check

Inapplicable

44.92%

Inapplicable

Inapplicable

* Vulnerability of this class are not incuded into reports during web application security assessment by black box method.

 

P 12. The distribution of sites non compliant to PCI DSS

 

P 13.Compliance level of Web application to PCI DSS (QSA) requirements

 

P 14. Compliance level of Web application to PCI DSS (ASV) requirements

 

Thus, more than 48 % of scanned Web applications are not compliant to PCI DSS requirements by ASV scanning. Meanwhile, deeper analysis shows that 99% of Web applications are not complaint to the standard requirements.

 

Contributors

 

WASC would like to thank the following organizations for making this initiative possible. Each organization is responsible for contributing sanitized data from web application security projects which was then combined to produce aggregated statistics.

 

 

 

 

APPENDIX 1: RISK ASSESSMENT METHODOLOGY

T. 8 Risk level assessment routine


Threat Classification

Basic CVSS Score

PCI DSS Risk

Abuse of Functionality  

4 (AV:N/AC:H/Au:N/C:P/I:P/A:N)

Medium

Brute Force Attack

6.8 (AV:N/AC:M/Au:N/C:P/I:P/A:P)

Critical

Buffer Overflow 

10 (AV:N/AC:L/Au:N/C:C/I:C/A:C)

Urgent

Content Spoofing 

5 (AV:N/AC:L/Au:N/C:N/I:P/A:N)

High

Credential/Session Prediction 

6.8 (AV:N/AC:M/Au:N/C:P/I:P/A:P)

Critical

Cross-Site Scripting 

6.4 (AV:N/AC:L/Au:N/C:P/I:P/A:N)

Critical

Cross-Site Request Forgery 

5 (AV:N/AC:L/Au:N/C:N/I:P/A:N)

High

Denial of Service 

7.8 (AV:N/AC:L/Au:N/C:N/I:N/A:C)

High

Format String Attack 

10 (AV:N/AC:L/Au:N/C:C/I:C/A:C)

Urgent

HTTP Request Splitting  

6.4 (AV:N/AC:L/Au:N/C:P/I:P/A:N)

Critical

HTTP Response Splitting  

6.4 (AV:N/AC:L/Au:N/C:P/I:P/A:N)

Critical

HTTP Request Smuggling  

6.4 (AV:N/AC:L/Au:N/C:P/I:P/A:N)

Critical

HTTP Response Smuggling  

6.4 (AV:N/AC:L/Au:N/C:P/I:P/A:N)

Critical

Integer Overflow

10 (AV:N/AC:L/Au:N/C:C/I:C/A:C)

Urgent

LDAP Injection 

10 (AV:N/AC:L/Au:N/C:C/I:C/A:C)

Urgent

Mail Command Injection 

5 (AV:N/AC:L/Au:N/C:N/I:P/A:N)

High

OS Commanding 

10 (AV:N/AC:L/Au:N/C:C/I:C/A:C)

Urgent

Path Traversal

7.8 (AV:N/AC:L/Au:N/C:C/I:N/A:N)

Critical

Predictable Resource Location 

5 (AV:N/AC:L/Au:N/C:P/I:N/A:N)

High

Remote File Inclusion

10 (AV:N/AC:L/Au:N/C:C/I:C/A:C)

Urgent

Routing Detour  

5 (AV:N/AC:L/Au:N/C:P/I:N/A:N)

High

SOAP Array Abuse  

7.8 (AV:N/AC:L/Au:N/C:N/I:N/A:C)

High

SSI Injection 

10 (AV:N/AC:L/Au:N/C:C/I:C/A:C)

Urgent

Session Fixation 

6.8 (AV:N/AC:M/Au:N/C:P/I:P/A:P)

Critical

SQL Injection 

10 (AV:N/AC:L/Au:N/C:C/I:C/A:C)

Urgent

URL Redirectors 

2.6 (AV:N/AC:H/Au:N/C:N/I:P/A:N)

Medium

XPath Injection 

10 (AV:N/AC:L/Au:N/C:C/I:C/A:C)

Urgent

XML Attribute Blowup 

5 (AV:N/AC:L/Au:N/C:P/I:N/A:N)

High

XML External Entity 

5 (AV:N/AC:L/Au:N/C:P/I:N/A:N)

High

XML Entity Expansion 

5 (AV:N/AC:L/Au:N/C:P/I:N/A:N)

High

XML Injection 

7.5 (AV:N/AC:L/Au:N/C:P/I:P/A:P)

Critical

XQuery Injection 

10 (AV:N/AC:L/Au:N/C:C/I:C/A:C)

Urgent

Application Misconfiguration 

5.1 (AV:N/AC:H/Au:N/C:P/I:P/A:P)

Medium

Directory Indexing 

5 (AV:N/AC:L/Au:N/C:P/I:N/A:N)

High

Fingerprinting 

0 (AV:N/AC:L/Au:N/C:N/I:N/A:N)

Low

Improper Parsing  

10 (AV:N/AC:L/Au:N/C:C/I:C/A:C)

Urgent

Improper Permissions 

10 (AV:N/AC:L/Au:N/C:C/I:C/A:C)

Urgent

Information leakage 

5 (AV:N/AC:L/Au:N/C:P/I:N/A:N)

High

Insecure Indexing  

5 (AV:N/AC:L/Au:N/C:P/I:N/A:N)

High

Insufficient Anti-automation 

4 (AV:N/AC:H/Au:N/C:P/I:P/A:N)

Medium

Insufficient Authentication 

6.8 (AV:N/AC:M/Au:N/C:P/I:P/A:P)

Critical

Insufficient Authorization 

6.8 (AV:N/AC:M/Au:N/C:P/I:P/A:P)

Critical

Insufficient Data Protection

5 (AV:N/AC:L/Au:N/C:P/I:N/A:N)

High

Insufficient Process Validation 

4 (AV:N/AC:H/Au:N/C:P/I:P/A:N)

Medium

Insufficient Session Expiration 

6.8 (AV:N/AC:M/Au:N/C:P/I:P/A:P)

Critical

Insufficient Transport Layer Protection

4 (AV:N/AC:H/Au:N/C:P/I:P/A:N)

Medium

Server Misconfiguration 

5.1 (AV:N/AC:H/Au:N/C:P/I:P/A:P)

Medium

 

APPENDIX 2: ADDITIONAL VULNERABILITY CLASSIFICATION

 

T. 9 Vulnerability classification by origin and impact

Threat Classification

Vulnerability in

Impact

Abuse of Functionality  

code

server-side

Brute Force Attack

administration

server-side

Buffer Overflow 

code

server-side

Content Spoofing 

code

client-side

Credential/Session Prediction 

code

server-side

Cross-Site Scripting 

code

client-side

Cross-Site Request Forgery 

code

client-side

Denial of Service 

administration

server-side

Format String Attack 

code

server-side

HTTP Request Splitting  

code

client-side

HTTP Response Splitting  

code

client-side

HTTP Request Smuggling  

administration

client-side

HTTP Response Smuggling  

administration

client-side

Integer Overflow

code

server-side

LDAP Injection 

code

server-side

Mail Command Injection 

code

server-side

OS Commanding 

code

server-side

Path Traversal

code

server-side

Predictable Resource Location 

administration

server-side

Remote File Inclusion

code

server-side

Routing Detour  

code

server-side

SOAP Array Abuse  

code

server-side

SSI Injection 

code

server-side

Session Fixation 

code

server-side

SQL Injection 

code

server-side

URL Redirectors 

code

client-side

XPath Injection 

code

server-side

XML Attribute Blowup 

code

server-side

XML External Entity 

code

server-side

XML Entity Expansion 

code

server-side

XML Injection 

code

server-side

XQuery Injection 

code

server-side

Application Misconfiguration 

administration

server-side

Directory Indexing 

administration

server-side

Fingerprinting 

administration

server-side

Improper Parsing  

code

server-side

Improper Permissions 

administration

server-side

Information leakage 

administration

server-side

Insecure Indexing  

administration

server-side

Insufficient Anti-automation 

code

server-side

Insufficient Authentication 

code

server-side

Insufficient Authorization 

code

server-side

Insufficient Data Protection

administration

server-side

Insufficient Process Validation 

code

server-side

Insufficient Session Expiration 

code

server-side

Insufficient Transport Layer Protection

administration

client-side

Server Misconfiguration 

administration

server-side

 

APPENDIX 3: STATISTICS

 

Overall Data

T. 10 General statistics Threat Classification       


Threat Classification

 N of Vulns

N of Sites

Vulns%

Sites%

Abuse of Functionality  

153

83

0.16%

0.68%

Brute Force Attack

79

51

0.08%

0.42%

Buffer Overflow 

537

84

0.55%

0.69%

Content Spoofing 

1564

304

1.60%

2.49%

Credential/Session Prediction 

794

147

0.81%

1.21%

Cross-Site Scripting 

37624

4686

38.57%

38.45%

Cross-Site Request Forgery 

285

161

0.29%

1.32%

Denial of Service 

42

36

0.04%

0.30%

Format String Attack 

52

43

0.05%

0.35%

HTTP Request Splitting  

311

162

0.32%

1.33%

HTTP Response Splitting  

2592

161

2.66%

1.32%

HTTP Request Smuggling  

0

0

0.00%

0.00%

HTTP Response Smuggling  

0

0

0.00%

0.00%

Integer Overflow

79

46

0.08%

0.38%

LDAP Injection 

41

16

0.04%

0.13%

Mail Command Injection 

1

1

0.00%

0.01%

OS Commanding 

76

30

0.08%

0.25%

Path Traversal

1563

139

1.60%

1.14%

Predictable Resource Location 

1507

295

1.54%

2.42%

Remote File Inclusion

99

44

0.10%

0.36%

Routing Detour  

0

0

0.00%

0.00%

SOAP Array Abuse  

2

1

0.00%

0.01%

SSI Injection 

157

33

0.16%

0.27%

Session Fixation 

137

123

0.14%

1.01%

SQL Injection 

6345

1555

6.50%

12.76%

URL Redirectors 

5

4

0.01%

0.03%

XPath Injection 

64

19

0.07%

0.16%

XML Attribute Blowup 

0

0

0.00%

0.00%

XML External Entity 

0

0

0.00%

0.00%

XML Entity Expansion 

0

0

0.00%

0.00%

XML Injection 

0

0

0.00%

0.00%

XQuery Injection 

0

0

0.00%

0.00%

Application Misconfiguration 

85

60

0.09%

0.49%

Directory Indexing 

370

184

0.38%

1.51%

Fingerprinting 

3663

3604

3.75%

29.57%

Improper Parsing  

1464

524

1.50%

4.30%

Improper Permissions 

4

4

0.00%

0.03%

Information leakage 

31527

7942

32.32%

65.17%

Insecure Indexing  

8

7

0.01%

0.06%

Insufficient Anti-automation 

108

36

0.11%

0.30%

Insufficient Authentication 

806

304

0.83%

2.49%

Insufficient Authorization 

615

286

0.63%

2.35%

Insufficient Data Protection

64

21

0.07%

0.17%

Insufficient Process Validation 

52

34

0.05%

0.28%

Insufficient Session Expiration 

169

71

0.17%

0.58%

Insufficient Transport Layer Protection

4317

4195

4.43%

34.42%

Server Misconfiguration

193

113

0.20%

0.93%

Total 

97554

12186

 

 

 

T. 11 Vulnerabilities distribution by risk Threat rank        

Threat rank

N of Vulns

N of Sites

Vulns%

% Sites

Urgent

8918

2287

9.14%

18.77%

Critical

44669

5511

45.79%

45.22%

High

35375

8807

36.26%

72.27%

Medium

4908

4455

5.03%

36.56%

Low

3663

3618

3.75%

29.69%

 

Automatic scans

 

T. 12 General statistics Threat Classification       

Threat Classification

 N of Vulns

N of Sites

Vulns%

Sites%

Abuse of Functionality  

1

1

0.00%

0.01%

Brute Force Attack

5

5

0.01%

0.05%

Buffer Overflow 

6

3

0.02%

0.03%

Content Spoofing 

29

22

0.08%

0.21%

Credential/Session Prediction 

9

9

0.03%

0.09%

Cross-Site Scripting 

11230

3934

31.62%

37.66%

Cross-Site Request Forgery 

2

2

0.01%

0.02%

Denial of Service 

30

25

0.08%

0.24%

Format String Attack 

0

0

0.00%

0.00%

HTTP Request Splitting  

311

162

0.88%

1.55%

HTTP Response Splitting  

0

0

0.00%

0.00%

HTTP Request Smuggling  

0

0

0.00%

0.00%

HTTP Response Smuggling  

0

0

0.00%

0.00%

Integer Overflow

0

0

0.00%

0.00%

LDAP Injection 

0

0

0.00%

0.00%

Mail Command Injection 

0

0

0.00%

0.00%

OS Commanding 

28

5

0.08%

0.05%

Path Traversal

82

56

0.23%

0.54%

Predictable Resource Location 

16

15

0.05%

0.14%

Remote File Inclusion

86

36

0.24%

0.34%

Routing Detour  

0

0

0.00%

0.00%

SOAP Array Abuse  

0

0

0.00%

0.00%

SSI Injection 

157

33

0.44%

0.32%

Session Fixation 

3

3

0.01%

0.03%

SQL Injection 

2969

1217

8.36%

11.65%

URL Redirectors 

1

1

0.00%

0.01%

XPath Injection 

0

0

0.00%

0.00%

XML Attribute Blowup 

0

0

0.00%

0.00%

XML External Entity 

0

0

0.00%

0.00%

XML Entity Expansion 

0

0

0.00%

0.00%

XML Injection 

0

0

0.00%

0.00%

XQuery Injection 

0

0

0.00%

0.00%

Application Misconfiguration 

48

37

0.14%

0.35%

Directory Indexing 

12

11

0.03%

0.11%

Fingerprinting 

3604

3587

10.15%

34.34%

Improper Parsing  

1463

523

4.12%

5.01%

Improper Permissions 

2

2

0.01%

0.02%

Information leakage 

11134

7593

31.35%

72.68%

Insecure Indexing  

8

7

0.02%

0.07%

Insufficient Anti-automation 

0

0

0.00%

0.00%

Insufficient Authentication 

24

15

0.07%

0.14%

Insufficient Authorization 

14

14

0.04%

0.13%

Insufficient Data Protection

10

10

0.03%

0.10%

Insufficient Process Validation 

12

11

0.03%

0.11%

Insufficient Session Expiration 

1

1

0.00%

0.01%

Insufficient Transport Layer Protection

4194

4175

11.81%

39.96%

Server Misconfiguration

22

22

0.06%

0.21%

Total 

35513

10447

 

 

 

T. 13 Vulnerabilities distribution by risk Threat rank        

Threat rank

 N of Vulns

N of Sites

Vulns%

% Sites

Urgent

4711

1745

13.27%

16.70%

Critical

11679

4100

32.89%

39.25%

High

11257

7636

31.70%

73.09%

Medium

4294

4199

12.09%

40.19%

Low

3625

3599

10.21%

34.45%

 

Black Box

 

T. 14 General statistics Threat Classification       

Threat Classification

 N of Vulns

N of Sites

Vulns%

Sites%

Abuse of Functionality  

135

75

0.75%

7.17%

Brute Force Attack

34

29

0.19%

2.77%

Buffer Overflow 

0

0

0.00%

0.00%

Content Spoofing 

1110

241

6.19%

23.04%

Credential/Session Prediction 

15

12

0.08%

1.15%

Cross-Site Scripting 

11768

590

65.65%

56.41%

Cross-Site Request Forgery 

185

83

1.03%

7.93%

Denial of Service 

9

8

0.05%

0.76%

Format String Attack 

2

2

0.01%

0.19%

HTTP Request Splitting  

0

0

0.00%

0.00%

HTTP Response Splitting  

601

77

3.35%

7.36%

HTTP Request Smuggling  

0

0

0.00%

0.00%

HTTP Response Smuggling  

0

0

0.00%

0.00%

Integer Overflow

9

6

0.05%

0.57%

LDAP Injection 

0

0

0.00%

0.00%

Mail Command Injection 

0

0

0.00%

0.00%

OS Commanding 

16

11

0.09%

1.05%

Path Traversal

29

20

0.16%

1.91%

Predictable Resource Location 

855

155

4.77%

14.82%

Remote File Inclusion

3

3

0.02%

0.29%

Routing Detour  

0

0

0.00%

0.00%

SOAP Array Abuse  

0

0

0.00%

0.00%

SSI Injection 

0

0

0.00%

0.00%

Session Fixation 

83

79

0.46%

7.55%

SQL Injection 

1556

169

8.68%

16.16%

URL Redirectors 

1

1

0.01%

0.10%

XPath Injection 

59

17

0.33%

1.63%

XML Attribute Blowup 

0

0

0.00%

0.00%

XML External Entity 

0

0

0.00%

0.00%

XML Entity Expansion 

0

0

0.00%

0.00%

XML Injection 

0

0

0.00%

0.00%

XQuery Injection 

0

0

0.00%

0.00%

Application Misconfiguration 

31

20

0.17%

1.91%

Directory Indexing 

104

42

0.58%

4.02%

Fingerprinting 

1

1

0.01%

0.10%

Improper Parsing  

1

1

0.01%

0.10%

Improper Permissions 

2

2

0.01%

0.19%

Information leakage 

745

399

4.16%

38.15%

Insecure Indexing  

0

0

0.00%

0.00%

Insufficient Anti-automation 

6

4

0.03%

0.38%

Insufficient Authentication 

158

90

0.88%

8.60%

Insufficient Authorization 

312

155

1.74%

14.82%

Insufficient Data Protection

2

2

0.01%

0.19%

Insufficient Process Validation 

5

5

0.03%

0.48%

Insufficient Session Expiration 

30

27

0.17%

2.58%

Insufficient Transport Layer Protection

0

0

0.00%

0.00%

Server Misconfiguration

58

38

0.32%

3.63%

Total 

17925

1046

 

 

 

T. 15 Vulnerabilities distribution by risk Threat rank 

Threat rank

 N of Vulns

N of Sites

Vulns%

% Sites

Urgent

1648

206

9.19%

19.69%

Critical

13030

782

72.69%

74.76%

High

3011

612

16.80%

58.51%

Medium

235

126

1.31%

12.05%

Low

1

1

0.01%

0.10%

 

White Box

 

T. 16 General statistics Threat Classification       

Threat Classification

 N of Vulns

N of Sites

Vulns%

Sites%

Abuse of Functionality  

7

4

0.03%

2.67%

Brute Force Attack

15

11

0.05%

7.33%

Buffer Overflow 

421

1

1.52%

0.67%

Content Spoofing 

0

0

0.00%

0.00%

Credential/Session Prediction 

695

66

2.50%

44.00%

Cross-Site Scripting 

8006

88

28.83%

58.67%

Cross-Site Request Forgery 

2

1

0.01%

0.67%

Denial of Service 

3

3

0.01%

2.00%

Format String Attack 

2

1

0.01%

0.67%

HTTP Request Splitting  

0

0

0.00%

0.00%

HTTP Response Splitting  

1941

54

6.99%

36.00%

HTTP Request Smuggling  

0

0

0.00%

0.00%

HTTP Response Smuggling  

0

0

0.00%

0.00%

Integer Overflow

0

0

0.00%

0.00%

LDAP Injection 

0

0

0.00%

0.00%

Mail Command Injection 

1

1

0.00%

0.67%

OS Commanding 

29

12

0.10%

8.00%

Path Traversal

1450

59

5.22%

39.33%

Predictable Resource Location 

15

13

0.05%

8.67%

Remote File Inclusion

3

2

0.01%

1.33%

Routing Detour  

0

0

0.00%

0.00%

SOAP Array Abuse  

0

0

0.00%

0.00%

SSI Injection 

0

0

0.00%

0.00%

Session Fixation 

1

1

0.00%

0.67%

SQL Injection 

898

59

3.23%

39.33%

URL Redirectors 

0

0

0.00%

0.00%

XPath Injection 

0

0

0.00%

0.00%

XML Attribute Blowup 

0

0

0.00%

0.00%

XML External Entity 

0

0

0.00%

0.00%

XML Entity Expansion 

0

0

0.00%

0.00%

XML Injection 

0

0

0.00%

0.00%

XQuery Injection 

0

0

0.00%

0.00%

Application Misconfiguration 

1

1

0.00%

0.67%

Directory Indexing 

2

2

0.01%

1.33%

Fingerprinting 

8

6

0.03%

4.00%

Improper Parsing  

0

0

0.00%

0.00%

Improper Permissions 

0

0

0.00%

0.00%

Information leakage 

13598

81

48.96%

54.00%

Insecure Indexing  

0

0

0.00%

0.00%

Insufficient Anti-automation 

2

2

0.01%

1.33%

Insufficient Authentication 

324

45

1.17%

30.00%

Insufficient Authorization 

89

6

0.32%

4.00%

Insufficient Data Protection

52

9

0.19%

6.00%

Insufficient Process Validation 

5

3

0.02%

2.00%

Insufficient Session Expiration 

78

28

0.28%

18.67%

Insufficient Transport Layer Protection

123

26

0.44%

17.33%

Server Misconfiguration

1

1

0.00%

0.67%

Total 

27772

150

 

 

 

T. 17 Vulnerabilities distribution by risk Threat rank

Threat rank

 N of Vulns

N of Sites

Vulns%

% Sites

Urgent

1353

75

4.87%

50.00%

Critical

12599

138

45.37%

92.00%

High

13673

93

49.23%

62.00%

Medium

139

36

0.50%

24.00%

Low

8

6

0.03%

4.00%

 

Comments (3)

Sergey Gordeychik said

at 11:04 pm on Jan 10, 2010

Dear Mesut GULNAZ, thanks for your comments.

>T. 11 Vulnerabilities distribution by risk Threat rank

Thank you, fixed.

>T. 10 General statistics Threat Classification

Sorry, but number is correct.
We can't just sum numbers in "site" column because on site can contain several vulnerabilities. This number has been taken from contributors reports.

Mesut GULNAZ said

at 4:55 pm on Jan 9, 2010

T. 11 Vulnerabilities distribution by risk Threat rank
Threat rank - N of Vulns - N of Sites - N of Sites - % Sites

i think the seconf "N of sites" is "% Vulns"

Mesut GULNAZ said

at 4:12 pm on Jan 9, 2010

APPENDIX 3: STATISTICS
Overall Data
T. 10 General statistics Threat Classification

Total 97554 12186==> total of number of sites is not correct. can you correct it.
i think it is 25609.

take it easy...

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