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Học MCSA, CCNA chỉ với 2,200,000 VNĐ Loading
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Web Application Security Statistics
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
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:
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:
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 95.79%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 administration41859 10347 42.91% 84.91% 4.05 Vulnerability in code55695 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 ![]() 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 RiskAbuse 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 codeserver-side Brute Force Attack administrationserver-side Buffer Overflow codeserver-side Content Spoofing codeclient-side Credential/Session Prediction codeserver-side Cross-Site Scripting codeclient-side Cross-Site Request Forgery codeclient-side Denial of Service administrationserver-side Format String Attack codeserver-side HTTP Request Splitting codeclient-side HTTP Response Splitting codeclient-side HTTP Request Smuggling administrationclient-side HTTP Response Smuggling administrationclient-side Integer Overflow codeserver-side LDAP Injection codeserver-side Mail Command Injection codeserver-side OS Commanding codeserver-side Path Traversal codeserver-side Predictable Resource Location administrationserver-side Remote File Inclusion codeserver-side Routing Detour codeserver-side SOAP Array Abuse codeserver-side SSI Injection codeserver-side Session Fixation codeserver-side SQL Injection codeserver-side URL Redirectors codeclient-side XPath Injection codeserver-side XML Attribute Blowup codeserver-side XML External Entity codeserver-side XML Entity Expansion codeserver-side XML Injection codeserver-side XQuery Injection codeserver-side Application Misconfiguration administrationserver-side Directory Indexing administrationserver-side Fingerprinting administrationserver-side Improper Parsing codeserver-side Improper Permissions administrationserver-side Information leakage administrationserver-side Insecure Indexing administrationserver-side Insufficient Anti-automation codeserver-side Insufficient Authentication codeserver-side Insufficient Authorization codeserver-side Insufficient Data Protection administrationserver-side Insufficient Process Validation codeserver-side Insufficient Session Expiration codeserver-side Insufficient Transport Layer Protection administrationclient-side Server Misconfiguration administrationserver-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 153 830.16% 0.68% Brute Force Attack 79 510.08% 0.42% Buffer Overflow 537 840.55% 0.69% Content Spoofing 1564 3041.60% 2.49% Credential/Session Prediction 794 1470.81% 1.21% Cross-Site Scripting 37624 468638.57% 38.45% Cross-Site Request Forgery 285 1610.29% 1.32% Denial of Service 42 360.04% 0.30% Format String Attack 52 430.05% 0.35% HTTP Request Splitting 311 1620.32% 1.33% HTTP Response Splitting 2592 1612.66% 1.32% HTTP Request Smuggling 0 00.00% 0.00% HTTP Response Smuggling 0 00.00% 0.00% Integer Overflow 79 460.08% 0.38% LDAP Injection 41 160.04% 0.13% Mail Command Injection 1 10.00% 0.01% OS Commanding 76 300.08% 0.25% Path Traversal 1563 1391.60% 1.14% Predictable Resource Location 1507 2951.54% 2.42% Remote File Inclusion 99 440.10% 0.36% Routing Detour 0 00.00% 0.00% SOAP Array Abuse 2 10.00% 0.01% SSI Injection 157 330.16% 0.27% Session Fixation 137 1230.14% 1.01% SQL Injection 6345 15556.50% 12.76% URL Redirectors 5 40.01% 0.03% XPath Injection 64 190.07% 0.16% XML Attribute Blowup 0 00.00% 0.00% XML External Entity 0 00.00% 0.00% XML Entity Expansion 0 00.00% 0.00% XML Injection 0 00.00% 0.00% XQuery Injection 0 00.00% 0.00% Application Misconfiguration 85 600.09% 0.49% Directory Indexing 370 1840.38% 1.51% Fingerprinting 3663 36043.75% 29.57% Improper Parsing 1464 5241.50% 4.30% Improper Permissions 4 40.00% 0.03% Information leakage 31527 794232.32% 65.17% Insecure Indexing 8 70.01% 0.06% Insufficient Anti-automation 108 360.11% 0.30% Insufficient Authentication 806 3040.83% 2.49% Insufficient Authorization 615 2860.63% 2.35% Insufficient Data Protection 64 210.07% 0.17% Insufficient Process Validation 52 340.05% 0.28% Insufficient Session Expiration 169 710.17% 0.58% Insufficient Transport Layer Protection 4317 41954.43% 34.42% Server Misconfiguration 193 1130.20% 0.93% Total 97554 12186T. 11 Vulnerabilities distribution by risk Threat rank Threat rank N of Vulns N of Sites N of Sites % Sites Urgent8918 2287 9.14% 18.77% Critical44669 5511 45.79% 45.22% High35375 8807 36.26% 72.27% Medium4908 4455 5.03% 36.56% Low3663 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 N of Sites % Sites Urgent4711 1745 13.27% 16.70% Critical11679 4100 32.89% 39.25% High11257 7636 31.70% 73.09% Medium4294 4199 12.09% 40.19% Low3625 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 N of Sites % Sites Urgent1648 206 9.19% 19.69% Critical13030 782 72.69% 74.76% High3011 612 16.80% 58.51% Medium235 126 1.31% 12.05% Low1 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 N of Sites % Sites Urgent1353 75 4.87% 50.00% Critical12599 138 45.37% 92.00% High13673 93 49.23% 62.00% Medium139 36 0.50% 24.00% Low8 6 0.03% 4.00% Link tham khảo đầy đủ The Web Application Security Consortium / Web Application Security Statistics |
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