Difference between revisions of "Category:OWASP AppSensor Project"
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Revision as of 15:40, 12 November 2009
| This project has produced a book that can be downloaded or purchased.|
Feel free to browse the full catalog of available OWASP books.
|Project Name||OWASP AppSensor Project - Detect and Respond to Attacks from Within the Application|
|Short Project Description||
Real Time Application Attack Detection and Response
Article on why Application Based Intrusion Detection is a must for critical applications.
The AppSensor project defines a conceptual framework and methodology that offers prescriptive guidance to implement intrusion detection and automated response into an existing application. Current efforts are underway to create the AppSensor tool which can be utilized by any existing application interested in adding detection and response capabilities.
AppSensor defines over 50 different detection points which can be used to identify a malicious attacker.
AppSensor provides guidance on how to respond once a malicious attacker has been identified. Possible actions include: logging out the user, locking the account or notifying an administrator. More than a dozen response actions are described.
Defending the Application
An attacker often requires numerous probes and attack attempts in order to locate an exploitable vulnerability within the application. By using AppSensor it is possible to identify and eliminate the threat of an attacker before they are able to successfully identify an exploitable flaw.
|Project key Information||Project Leaders:
Creative Commons Attribution Share Alike 3.0
OWASP SoC 08
|Release Status||Main Links||Related Projects|
If you walk into a bank and try opening random doors, you will be identified, led out of the building and possibly arrested. However, if you log into an online banking application and start looking for vulnerabilities no one will say anything. This needs to change!
As critical applications continue to become more accessible and inter-connected, it is paramount that critical information is sufficiently protected. We must also realize that our defenses may not be perfect. Given enough time, attackers can identify security flaws in the design or implementation of an application.
In addition to implementing layers of defense within an application, we must identify malicious individuals before they are able to identify any gaps in our defenses. The best place to identify malicious activity against the application is within the application itself. Network based intrusion detection systems are not appropriate to handle the custom and intricate workings of an enterprise application and are ill-suited to detect attacks focusing on application logic such as authentication, access control, etc. This project will create the framework which can be used to build a robust system of attack detection, analysis, and response within an enterprise application
Is this hard?
No, simple checks are used to detect malicious activity. A security exception is then thrown and the AppSensor/ESAPI framework takes care of the rest.
Download the AppSensor book for free at lulu.com
Order a printed version for under $10 lulu.com
Next Presentation: OWASP AppSec DC - Thursday, November 12, 2009
Demo: The AppSensor project will soon be releasing a working demo. This web application will include a working example of the AppSensor detection points integrated with ESAPI. Stay tuned for more.
Next Presentation: OWASP DC, November 2009
Current: v1.2 in the works, demo application in development
January, 2009 - v1.1 Released - Beta Status
November, 2008 - AppSensor Talk at OWASP Portugal
November, 2008 - v1.0 Released - Beta Status
April 16, 2008 - Project Begins
Below are the primary detection points defined within AppSensor. These are just the titles; the document contains descriptions, examples and considerations for implementing these detection points.
Signature Based Events
RE1 Unexpected HTTP Commands
RE2 Attempts To Invoke Unsupported HTTP Methods
RE3 GET When Expecting POST
RE4 POST When Expecting GET
AE1 Use Of Multiple Usernames
AE2 Multiple Failed Passwords
AE3 High Rate Of Login Attempts
AE4 Unexpected Quantity Of Characters In Username
AE5 Unexpected Quantity Of Characters In Password
AE6 Unexpected Types Of Characters In Username
AE7 Unexpected Types Of Characters In Password
AE8 Providing Only The Username
AE9 Providing Only The Password
AE10 Adding Additional POST Variables
AE11 Removing POST Variables
SE1 Modifying Existing Cookies
SE2 Adding New Cookies
SE3 Deleting Existing Cookies
SE4 Substituting Another User's Valid Session ID Or Cookie
SE5 Source IP Address Changes During Session
SE6 Change Of User Agent Mid Session
ACE1 Modifying URL Arguments Within A GET For Direct Object Access Attempts
ACE2 Modifying Parameters Within A POST For Direct Object Access Attempts
ACE3 Force Browsing Attempts
ACE4 Evading Presentation Access Control Through Custom Posts
IE1 Cross Site Scripting Attempt
IE2 Violations Of Implemented White Lists
EE1 Double Encoded Characters
EE2 Unexpected Encoding Used
CIE1 Blacklist Inspection For Common SQL Injection Values
CIE2 Detect Abnormal Quantity Of Returned Records.
CIE3 Null Byte Character In File Request
CIE4 Carriage Return Or Line Feed Character In File Request
FIO1 Detect Large Individual Files
FIO2 Detect Large Number Of File Uploads
Behavior Based Events
UT1 Irregular Use Of Application
UT2 Speed Of Application Use
UT3 Frequency Of Site Use
UT4 Frequency Of Feature Use
STE1 High Number Of Logouts Across The Site
STE2 High Number Of Logins Across The Site
STE3 High Number Of Same Transaction Across The Site
RE - Request
AE - Authentication
SE - Session
ACE - Acess Control
IE - Input
EE - Encoding
CIE - Command Injection
FIO - File IO
UT - User Trend
STE - System Strend
Video Demos of AppSensor