Testing for business logic

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Brief Summary
Testing for business logic flaws in a multi-functional dynamic web application requires thinking in unconventional ways. If an application's authentication mechanism is developed with the intention of performing steps 1,2,3 in order to authenticate, what happens if you go from 1 straight to step 3? In this simplistic example does the application provide provide access by failing open, deny access, or just error out with a 500 message. There are many examples that can be made here but the one constant is thinking outside of conventional wisdom. This type of vulnerability can not be detected by a vulnerability scanner and relies upon the skill and creativity of the penetration tester. In addition this type of vulnerability is usually one of the hardest to detect but at the same standpoint usually one of the most detrimental to the application if exploited.

Business logic type of comprises:
 * Business rules that express business policy (such as channels, location, logistics, prices, and products); and
 * Workflows that are the ordered tasks of passing documents or data from one participant (a person or a software system) to another.

The attacks on the business logic of an application are dangerous, difficult to detect and specific to that application.

Description of the Issue
Business logic can have security flaws that allow a user to do something that isn't allowed by the business. For example, if there is a limit on reimbursement of $1000, could an attacker misuse the system to request more money than is allowed? Or perhaps you are supposed to do operations in a particular order, but an attacker could invoke them out of sequence. Or can a user make a purchase for a negative amount of money? Frequently these business logic security checks simply are not present in the application.

Automated tools find it hard to understand context, hence it's up to a person to perform these kinds of tests.

Business Limits and Restrictions

Consider the rules for the business function being provided by the application. Are there any limits or restrictions on people's behavior? Then consider whether the application enforces those rules. It's generally pretty easy to identify the test and analysis cases to verify the application if you're familiar with the business. If you are a third-party tester, then you're going to have to use your common sense and ask the business if different operations should be allowed by the application.

Example: Setting the quantity of a product on an e-commerce site as a negative number may result in funds being credited to the attacker. The countermeasure to this problem is to implement stronger data validation, as the application permits negative numbers to be entered in the quantity field of the shopping cart.

Black Box Testing and Examples
Although uncovering logical vulnerabilities will probably always remain an art, one can attempt to go about it systematically to a great extent. Here is a suggested approach that consists of:
 * Understanding the application
 * Creating raw data for designing logical tests
 * Designing the logical tests
 * Standard prerequisites
 * Execution of logical tests

Understanding the application
Understanding the application thoroughly is a prerequisite for designing logical tests. To start with:
 * Get any documentation describing the application's functionality. Examples of this include:
 * Application manuals
 * Requirements documents
 * Functional specifications
 * Use or Abuse Cases
 * Explore the application manually and try to understand all the different ways in which the application can be used, the acceptable usage scenarios and the authorization limits imposed on various users

Creating raw data for designing logical tests
In this phase, one should ideally come up with the following data:
 * All application business scenarios. For example, for an e-commerce application this might look like,
 * Product ordering
 * Checkout
 * Browse
 * Search for a product
 * Workflows. This is different from business scenarios since it involves a number of different users. Examples include:
 * Order creation and approval
 * Bulletin board (one user posts an article that is reviewed by a moderator and ultimately seen by all users)
 * Different user roles
 * Administrator
 * Manager
 * Staff
 * CEO
 * Different groups or departments (note that there could be a tree (e.g. the Sales group of the heavy engineering division) or tagged view (e.g. someone could be a member of Sales as well as marketing) associated with this.
 * Purchasing
 * Marketing
 * Engineering
 * Access rights of various user roles and groups - The application allows various users privileges on some resource (or asset) and we need to specify the constraints of these privileges. One simple way to know these business rules/constraints is to make use of the application documentation effectively.  For example, look for clauses like "If the administrator allows individual user access..", "If configured by the administrator.." and you know the restriction imposed by the application.
 * Privilege Table – After learning about the various privileges on the resources along with the constraints, you are all set to create a Privilege Table. Get answers to:
 * What can each user role do on which resource with what constraint? This will help you in deducing who cannot do what on which resource.
 * What are the policies across groups?

Consider the following privileges: "Approve expense report", "Book a conference room", "Transfer money from own account to another user's account". A privilege could be thought of as a combination of a verb (e.g. Approve, Book, Withdraw) and one or more nouns (Expense report, conference room, account). The output of this activity is a grid with the various privileges forming the leftmost column while all user roles and groups would form the column headings of other columns. There would also be a “Comments” column that qualifies data in this grid.



This data is a key input for designing logical tests.

Developing logical tests
Here are several guidelines to designing logical tests from the raw data gathered.


 * Privilege Table - Make use of the privilege table as a reference while creating application specific logical threats. In general, develop a test for each admin privilege to check if it could be executed illegally by a user role with minimum privileges or no privilege. For example:
 * Privilege: Operations Manager cannot approve a customer order
 * Logical Test: Operations Manager approves a customer order


 * Improper handling of special user action sequences - Navigating through an application in a certain way or revisiting pages out of synch can cause logical errors which may cause the application to do something it's not meant to. For example:
 * A wizard application where one fills in forms and proceeds to the next step. One cannot in any normal way (according to the developers) enter the wizard in the middle of the process. Bookmarking a middle step (say step 4 of 7), then continuing with the other steps until completion or form submission, then revisiting the middle step that was bookmarked may "upset" the backend logic due to a weak state model.


 * Cover all business transaction paths - While designing tests, check for all alternative ways to perform the same business transaction. For example, create tests for both cash and credit payment modes.


 * Client-side validation - Look at all client side validations and see how they could be the basis for designing logical tests. For example, a funds transfer transaction has a validation for negative values in the amount field.  This information can be used to design a logical test such as "A user transfers negative amount of money".

Standard prerequisites
Typically, some initial activities useful as setup are:
 * Create test users with different permissions
 * Browse all the important business scenarios/workflows in the application

Execution of logical tests
Pick up each logical test and do the following:
 * Analyze the HTTP/S requests underlying the acceptable usage scenario corresponding to the logical test
 * Check the order of HTTP/S requests
 * Understand the purpose of hidden fields, form fields, query string parameters being passed
 * Try and subvert it by exploiting the known vulnerabilities
 * Verify that the application fails for the test

A real world example
In order to provide the reader with a better understanding of this issue and how to test it, we describe a real world case that was investigated by one of the authors in 2006. At that time, a mobile telecom operator (we'll call it FlawedPhone.com) launched a webmail+SMS service for its customers, with the following characteristics:


 * New customers, when buying a SIM card, can open a free, permanent email account with the flawedphone.com domain
 * The email is preserved even if the customers “transfers” the SIM card to another telecom operator
 * However, as long as the SIM card is registered to FlawedPhone, each time an email is received, a SMS message is sent to the customer, including sender and subject
 * The SMS application checks that the target phone number is a legitimate customer from its own copy of the FlawedPhone customers list, which is automatically updated every ~8 hours.

The application had been developed following security best practices but it suffered from a business logic flaw and FlawedPhone was soon targeted by the following fraud attack:


 * The attacker bought a new FlawedPhone SIM card
 * The attacker immediately requested to transfer the SIM card to another mobile carrier, which credits 0.05 € for each received SMS message
 * As soon as the SIM card was “transferred” to the new provider, the attacker started sending hundreds of emails to her FlawedPhone email account
 * The attacker had a ~8 hours window before the email+SMS application had its list updated and stopped delivering messages
 * By that time, the attacker had ~50-100 € in the card, and proceeded to sell it on eBay

The developers thought that SMS messages delivered during the 8 hours period would have introduced a negligible cost but failed to consider the likelihood of an automated attack like the one described. As we can see, the synchronization time, combined with the lack of a limit to the number of messages that could be delivered in a given period of time, introduced a critical flaw in the system that was soon exploited by malicious users.