Consider what we mean when we say that a program is "secure." We saw in Chapter 1 that security implies some degree of trust that the program enforces expected confidentiality, integrity, and availability. From the point of view of a program or a programmer, how can we look at a software component or code fragment and assess its security? This question is, of course, similar to the problem of assessing software quality in general. One way to assess security or quality is to ask people to name the characteristics of software that contribute to its overall security. However, we are likely to get different answers from different people. This difference occurs because the importance of the characteristics depends on who is analyzing the software. For example, one person may decide that code is secure because it takes too long to break through its security controls. And someone else may decide code is secure if it has run for a period of time with no apparent failures. But a third person may decide that any potential fault in meeting security requirements makes code insecure.
An assessment of security can also be influenced by someone's general perspective on software quality. For example, if your manager's idea of quality is conformance to specifications, then she might consider the code secure if it meets security requirements, whether or not the requirements are complete or correct. This security view played a role when a major computer manufacturer delivered all its machines with keyed locks, since a keyed lock was written in the requirements. But the machines were not secure, because all locks were configured to use the same key! Thus, another view of security is fitness for purpose; in this view, the manufacturer clearly had room for improvement.
In general, practitioners often look at quantity and types of faults for evidence of a product's quality (or lack of it). For example, developers track the number of faults found in requirements, design, and code inspections and use them as indicators of the likely quality of the final product. Sidebar 3-1 explains the importance of separating the faultsthe causes of problemsfrom the failures, the effects of the faults.
One approach to judging quality in security has been fixing faults. You might argue that a module in which 100 faults were discovered and fixed is better than another in which only 20 faults were discovered and fixed, suggesting that more rigorous analysis and testing had led to the finding of the larger number of faults. Au contraire, challenges your friend: a piece of software with 100 discovered faults is inherently full of problems and could clearly have hundreds more waiting to appear. Your friend's opinion is confirmed by the software testing literature; software that has many faults early on is likely to have many others still waiting to be found.
Sidebar 3-1: IEEE Terminology for Quality
Frequently, we talk about "bugs" in software, a term that can mean many different things depending on context. A bug can be a mistake in interpreting a requirement, a syntax error in a piece of code, or the (as-yet-unknown) cause of a system crash. The IEEE has suggested a standard terminology (in IEEE Standard 729) for describing bugs in our software products [IEEE83].
When a human makes a mistake, called an error, in performing some software activity, the error may lead to a fault, or an incorrect step, command, process, or data definition in a computer program. For example, a designer may misunderstand a requirement and create a design that does not match the actual intent of the requirements analyst and the user. This design fault is an encoding of the error, and it can lead to other faults, such as incorrect code and an incorrect description in a user manual. Thus, a single error can generate many faults, and a fault can reside in any development or maintenance product.
A failure is a departure from the system's required behavior. It can be discovered before or after system delivery, during testing, or during operation and maintenance. Since the requirements documents can contain faults, a failure indicates that the system is not performing as required, even though it may be performing as specified.
Thus, a fault is an inside view of the system, as seen by the eyes of the developers, whereas a failure is an outside view: a problem that the user sees. Not every fault corresponds to a failure; for example, if faulty code is never executed or a particular state is never entered, then the fault will never cause the code to fail.
Early work in computer security was based on the paradigm of "penetrate and patch," in which analysts searched for and repaired faults. Often, a top-quality "tiger team" would be convened to test a system's security by attempting to cause it to fail. The test was considered to be a "proof" of security; if the system withstood the attacks, it was considered secure. Unfortunately, far too often the proof became a counterexample, in which not just one but several serious security problems were uncovered. The problem discovery in turn led to a rapid effort to "patch" the system to repair or restore the security. (See Schell's analysis in [SCH79].) However, the patch efforts were largely useless, making the system less secure rather than more secure because they frequently introduced new faults. There are at least four reasons why.
· The pressure to repair a specific problem encouraged a narrow focus on the fault itself and not on its context. In particular, the analysts paid attention to the immediate cause of the failure and not to the underlying design or requirements faults.
· The fault often had nonobvious side effects in places other than the immediate area of the fault.
· Fixing one problem often caused a failure somewhere else, or the patch addressed the problem in only one place, not in other related places.
· The fault could not be fixed properly because system functionality or performance would suffer as a consequence.
The inadequacies of penetrate-and-patch led researchers to seek a better way to be confident that code meets its security requirements. One way to do that is to compare the requirements with the behavior. That is, to understand program security, we can examine programs to see whether they behave as their designers intended or users expected. We call such unexpected behavior a program security flaw; it is inappropriate program behavior caused by a program vulnerability. Unfortunately, the terminology in the computer security field is not consistent with the IEEE standard described in Sidebar 3-1; the terms "vulnerability" and "flaw" do not map directly to the characterization of faults and failures. A flaw can be either a fault or failure, and a vulnerability usually describes a class of flaws, such as a buffer overflow. In spite of the inconsistency, it is important for us to remember that we must view vulnerabilities and flaws from two perspectives, cause and effect, so that we see what fault caused the problem and what failure (if any) is visible to the user. For example, a Trojan horse may have been injected in a piece of codea flaw exploiting a vulnerabilitybut the user may not yet have seen the Trojan horse's malicious behavior. Thus, we must address program security flaws from inside and outside, to find causes not only of existing failures but also of incipient ones. Moreover, it is not enough just to identify these problems. We must also determine how to prevent harm caused by possible flaws.
Program security flaws can derive from any kind of software fault. That is, they cover everything from a misunderstanding of program requirements to a one-character error in coding or even typing. The flaws can result from problems in a single code component or from the failure of several programs or program pieces to interact compatibly through a shared interface. The security flaws can reflect code that was intentionally designed or coded to be malicious or code that was simply developed in a sloppy or misguided way. Thus, it makes sense to divide program flaws into two separate logical categories: inadvertent human errors versus malicious, intentionally induced flaws.
These categories help us understand some ways to prevent the inadvertent and intentional insertion of flaws into future code, but we still have to address their effects, regardless of intention. That is, in the words of Sancho Panza in Man of La Mancha, "it doesn't matter whether the stone hits the pitcher or the pitcher hits the stone, it's going to be bad for the pitcher." An inadvertent error can cause just as much harm to users and their organizations as can an intentionally induced flaw. Furthermore, a system attack often exploits an unintentional security flaw to perform intentional damage. From reading the popular press (see Sidebar 3-2), you might conclude that intentional security incidents (called cyber attacks) are the biggest security threat today. In fact, plain, unintentional human errors are more numerous and cause much more damage.
Sidebar 3-2: Continuing Increase in Cyber Attacks
Carnegie Mellon University's Computer Emergency Response Team (CERT) tracks the number and kinds of vulnerabilities and cyber attacks reported worldwide. Part of CERT's mission is to warn users and developers of new problems and also to provide information on ways to fix them. According to the CERT coordination center, fewer than 200 known vulnerabilities were reported in 1995, and that number ranged between 200 and 400 from 1996 to 1999. But the number increased dramatically in 2000, with over 1,000 known vulnerabilities in 2000, almost 2,420 in 2001, and 4,129 in 2002. Then the trend seemed to taper off slightly with 3,784 in 2003 and 3,780 in 2004, but the count shot up again with 5,990 in 2005 and 1,597 in the first quarter of 2006 alone. (For current statistics, see http://www.cert.org/stats/cert_stats.html#vulnerabilities.)
How does that translate into cyber attacks? CERT reported over 137,000 incidents in 2003 and 319,992 total for the years 19882003. Because the number of incidents had become so large, the attacks so widespread, and the reporting structure so widely used, CERT stopped publishing a count of incidents in 2004, arguing that more significant metrics were needed.
Moreover, as of June 2006, Symantec's Norton antivirus software checked for over 72,000 known virus patterns. The Computer Security Institute and the FBI cooperate to take an annual survey of approximately 500 large institutions: companies, government organizations, and educational institutions [CSI05]. The response from 1999 through 2005 has been fairly constant: In each year approximately 40 percent of respondents reported from one to five incidents, 20 percent six to ten, and 10 percent more than ten. The respondents reported total losses exceeding $42 million due to virus attacks.
It is clearly time to take security seriously, both as users and developers.
Regrettably, we do not have techniques to eliminate or address all program security flaws. As Gasser [GAS88] notes, security is fundamentally hard, security often conflicts with usefulness and performance, there is no ""silver bullet" to achieve security effortlessly, and false security solutions impede real progress toward more secure programming. There are two reasons for this distressing situation.
Program controls apply at the level of the individual program and programmer. When we test a system, we try to make sure that the functionality prescribed in the requirements is implemented in the code. That is, we take a "should do" checklist and verify that the code does what it is supposed to do. However, security is also about preventing certain actions: a "shouldn't do" list. A system shouldn't do anything not on its "should do" list. It is almost impossible to ensure that a program does precisely what its designer or user intended, and nothing more. Regardless of designer or programmer intent, in a large and complex system, the pieces that have to fit together properly interact in an unmanageably large number of ways. We are forced to examine and test the code for typical or likely cases; we cannot exhaustively test every state and data combination to verify a system's behavior. So sheer size and complexity preclude total flaw prevention or mediation. Programmers intending to implant malicious code can take advantage of this incompleteness and hide some flaws successfully, despite our best efforts.
Programming and software engineering techniques change and evolve far more rapidly than do computer security techniques. So we often find ourselves trying to secure last year's technology while software developers are rapidly adopting today'sand next year'stechnology.
Still, the situation is far from bleak. Computer security has much to offer to program security. By understanding what can go wrong and how to protect against it, we can devise techniques and tools to secure most computer applications.
Types of Flaws
To aid our understanding of the problems and their prevention or correction, we can define categories that distinguish one kind of problem from another. For example, Landwehr et al. [LAN94] present a taxonomy of program flaws, dividing them first into intentional and inadvertent flaws. They further divide intentional flaws into malicious and nonmalicious ones. In the taxonomy, the inadvertent flaws fall into six categories:
· validation error (incomplete or inconsistent): permission checks
· domain error: controlled access to data
· serialization and aliasing: program flow order
· inadequate identification and authentication: basis for authorization
· boundary condition violation: failure on first or last case
· other exploitable logic errors
Other authors, such as Tsipenyuk et al. , the OWASP project , and Landwehr , have produced similar lists. This list gives us a useful overview of the ways in which programs can fail to meet their security requirements. We leave our discussion of the pitfalls of identification and authentication for Chapter 4, in which we also investigate separation into execution domains. In this chapter, we address the other categories, each of which has interesting examples.