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it can create Popular buzzwords, including system-oriented architecture, aspect-oriented programming, and dependency injection, all require understanding configuration information to accurately model the behavior of the program Configuration information is useful for another purpose, too For Web-based applications, the program s configuration often specifies the binding between the code and the URIs used to access the code If a static analysis tool understands this binding, its output can include information about which URIs and which input parameters are associated with each vulnerability In some cases, a dynamic testing tool can use this information to create an HTTP request to the Web application that will demonstrate the vulnerability Working in the other direction, when a dynamic testing tool finds a vulnerability, it can use static analysis results to provide a root-cause analysis of the vulnerability Not all static analysis results are easy to generate tests for, however Some depend on very precise timing, and others require manipulation of input sources other than the HTTP request Just because it is hard to generate a dynamic test for a static analysis result does not mean the result is invalid Conversely, if it is easy to generate a dynamic test for a static analysis result, it is reasonable to assume that it would be easy for an attacker to generate the same test Trade-Offs Between Precision, Depth, and Scalability The most precise methods of static analysis, in which all possible values and all eventualities are tracked with unyielding accuracy, are currently capable of analyzing thousands or tens of thousands of lines of code before the amount of memory used and the execution time required become unworkable Modern software systems often involve millions or tens of millions of lines of code, so maximum precision is not a realistic possibility in many circumstances On the other end of the spectrum, a simple static analysis algorithm, such as one that identifies the use of dangerous or deprecated functions, is capable of processing an effectively unlimited amount of code, but the results provide only limited value Most static analysis tools sacrifice some amount of precision to achieve better scalability Cutting-edge research projects often focus on finding better trade-offs They look for ways to gain scalability by sacrificing precision in such a way that it will not be missed The depth of analysis a tool performs is often directly proportional to the scope of the analysis (the amount of the program that the tool examines.

public public public public BoundingBox() BoundingBox(Point3d lower, Point3d upper) BoundingBox(Bounds boundsObject) BoundingBox(Bounds bounds[])

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It s hard to keep a tight lid on secrets For example, if you write a secret to disk on a computer with a journaling le system, there s no easy way to ensure that the secret will ever be deleted But it s just about impossible to prevent secrets from being written to memory presumably, your program needs access to the data at some point This section deals with a challenging problem: minimizing the retention of secrets in memory Our goal is to prevent secrets from being exposed even if an attacker gains access to memory Attackers often glean secrets from memory in the following ways: Remote exploits, such as buffer over ow or format string attacks Physical attacks, such as direct device access or discarded machines Accidental leakage, such as core dumps or page les This problem can be reduced to the concept of data lifetime The longer a secret remains in memory, the greater the risk an attacker will gain access to it Likewise, the more copies of a secret value appear in memory, the greater the value s data lifetime and the greater the risk it will be compromised Minimizing data lifetime is not only an application problem Differences between operating systems, device drivers, and system software also have an impact To demonstrate these differences, Jim Chow and Tal Gar nkel

The rst constructor constructs and initializes a 2X unity BoundingBox about the origin The second constructor constructs and initializes a BoundingBox from the given minimum and maximum in x, y, and z The third constructor constructs and initializes a BoundingBox from a bounding object The fourth constructor constructs and initializes a BoundingBox from an array of bounding objects Methods The BoundingBox object de nes the following methods

public void getLower(Point3d p1) public void setLower(Point3d p1) public void setLower(double xmin, double ymin, double zmin)

performed an experiment that measured the data lifetime of 64MB of sensitive data after the memory they were stored in was freed on three systems under load [Chow et al, 2005] Figure 112 summarizes the results of their experiment

Updates the properties of the associated object Discards any changes made in the window since the last "apply" action The Reset command then refills the window's fields with the values from the associated object Updates the properties of the associated object and then closes the window Closes the property window but not the application If a user has changed the values in the window but has not applied them, the Close button opens an alert box containing the following text: "Your changes have not been saved To save the changes, click Apply To discard the changes, click Discard To cancel your Close request, click Cancel" Works like the Close button, except that the Cancel button does not display an alert box before discarding changes Displays help text in another window while leaving the property window open

public void getUpper(Point3d p1) public void setUpper(Point3d p1) public void setUpper(double xmax, double ymax, double zmax)

Figure 112 The data lifetime of 64MB of sensitive information in freed memory on three active systems

public void set(Bounds boundsObject)

public Object clone()

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