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Testing is a process activity that homes in on product quality: making the product failure free or failure tolerant. Each software problem (especially when it relates to security) has the potential not only for making software fail but also for adversely affecting a business or a life. Thomas Young, head of NASA's investigation of the Mars lander failure, noted that "One of the things we kept in mind during the course of our review is that in the conduct of space missions, you get only one strike, not three. Even if thousands of functions are carried out flawlessly, just one mistake can be catastrophic to a mission" [NAS00]. This same sentiment is true for security: The failure of one control exposes a vulnerability that is not ameliorated by any number of functioning controls. Testers improve software quality by finding as many faults as possible and by writing up their findings carefully so that developers can locate the causes and repair the problems if possible.
Do not ignore a point from Thompson [THO03]: Security testing is hard. Side effects, dependencies, unpredictable users, and flawed implementation bases (languages, compilers, infrastructure) all contribute to this difficulty. But the essential complication with security testing is that we cannot look at just the one behavior the program gets right; we also have to look for the hundreds of ways the program might go wrong.
Testing usually involves several stages. First, each program component is tested on its own, isolated from the other components in the system. Such testing, known as module testing, component testing, or unit testing, verifies that the component functions properly with the types of input expected from a study of the component's design. Unit testing is done in a controlled environment whenever possible so that the test team can feed a predetermined set of data to the component being tested and observe what output actions and data are produced. In addition, the test team checks the internal data structures, logic, and boundary conditions for the input and output data.
When collections of components have been subjected to unit testing, the next step is ensuring that the interfaces among the components are defined and handled properly. Indeed, interface mismatch can be a significant security vulnerability. Integration testing is the process of verifying that the system components work together as described in the system and program design specifications.
Once we are sure that information is passed among components in accordance with the design, we test the system to ensure that it has the desired functionality. A function test evaluates the system to determine whether the functions described by the requirements specification are actually performed by the integrated system. The result is a functioning system.
The function test compares the system being built with the functions described in the developers' requirements specification. Then, a performance test compares the system with the remainder of these software and hardware requirements. It is during the function and performance tests that security requirements are examined, and the testers confirm that the system is as secure as it is required to be.
When the performance test is complete, developers are certain that the system functions according to their understanding of the system description. The next step is conferring with the customer to make certain that the system works according to customer expectations. Developers join the customer to perform an acceptance test, in which the system is checked against the customer's requirements description. Upon completion of acceptance testing, the accepted system is installed in the environment in which it will be used. A final installation test is run to make sure that the system still functions as it should. However, security requirements often state that a system should not do something. As Sidebar 3-7 demonstrates, it is difficult to demonstrate absence rather than presence.
The objective of unit and integration testing is to ensure that the code implemented the design properly; that is, that the programmers have written code to do what the designers intended. System testing has a very different objective: to ensure that the system does what the customer wants it to do. Regression testing, an aspect of system testing, is particularly important for security purposes. After a change is made to enhance the system or fix a problem, regression testing ensures that all remaining functions are still working and that performance has not been degraded by the change.
Each of the types of tests listed here can be performed from two perspectives: black box and clear box (sometimes called white box). Black-box testing treats a system or its components as black boxes; testers cannot "see inside" the system, so they apply particular inputs and verify that they get the expected output. Clear-box testing allows visibility. Here, testers can examine the design and code directly, generating test cases based on the code's actual construction. Thus, clear-box testing knows that component X uses CASE statements and can look for instances in which the input causes control to drop through to an unexpected line. Black-box testing must rely more on the required inputs and outputs because the actual code is not available for scrutiny.
Sidebar 3-7: Absence vs. Presence
Pfleeger [PFL97] points out that security requirements resemble those for any other computing task, with one seemingly insignificant difference. Whereas most requirements say "the system will do this," security requirements add the phrase "and nothing more." As we pointed out in Chapter 1, security awareness calls for more than a little caution when a creative developer takes liberties with the system's specification. Ordinarily, we do not worry if a programmer or designer adds a little something extra. For instance, if the requirement calls for generating a file list on a disk, the "something more" might be sorting the list in alphabetical order or displaying the date it was created. But we would never expect someone to meet the requirement by displaying the list and then erasing all the files on the disk!
If we could determine easily whether an addition was harmful, we could just disallow harmful additions. But unfortunately we cannot. For security reasons, we must state explicitly the phrase "and nothing more" and leave room for negotiation in the requirements definition on any proposed extensions.
It is natural for programmers to want to exercise their creativity in extending and expanding the requirements. But apparently benign choices, such as storing a value in a global variable or writing to a temporary file, can have serious security implications. And sometimes the best design approach for security is counterintuitive. For example, one cryptosystem attack depends on measuring the time to perform an encryption. That is, an efficient implementation can undermine the system's security. The solution, oddly enough, is to artificially pad the encryption process with unnecessary computation so that short computations complete as slowly as long ones.
In another instance, an enthusiastic programmer added parity checking to a cryptographic procedure. Because the keys were generated randomly, the result was that 255 of the 256 encryptions failed the parity check, leading to the substitution of a fixed keyso that 255 of every 256 encryptions were being performed under the same key!
No technology can automatically distinguish between malicious and benign code. For this reason, we have to rely on a combination of approaches, including human-intensive ones, to help us detect when we are going beyond the scope of the requirements and threatening the system's security.
The mix of techniques appropriate for testing a given system depends on the system's size, application domain, amount of risk, and many other factors. But understanding the effectiveness of each technique helps us know what is right for each particular system. For example, Olsen [OLS93] describes the development at Contel IPC of a system containing 184,000 lines of code. He tracked faults discovered during various activities, and found differences:
17.3 percent of the faults were found during inspections of the system design
19.1 percent during component design inspection
15.1 percent during code inspection
29.4 percent during integration testing
16.6 percent during system and regression testing
Only 0.1 percent of the faults were revealed after the system was placed in the field. Thus, Olsen's work shows the importance of using different techniques to uncover different kinds of faults during development; it is not enough to rely on a single method for catching all problems.
Who does the testing? From a security standpoint, independent testing is highly desirable; it may prevent a developer from attempting to hide something in a routine or keep a subsystem from controlling the tests that will be applied to it. Thus, independent testing increases the likelihood that a test will expose the effect of a hidden feature.
One type of testing is unique to computer security: penetration testing. In this form of testing, testers specifically try to make software fail. That is, instead of testing to see that software does do what it is expected to (as is the goal in the other types of testing we just listed), the testers try to see if the software does what it is not supposed to do, which is to fail or, more specifically, fail to enforce security. Because penetration testing usually applies to full systems, not individual applications, we study penetration testing in Chapter 5.
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