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Like most file formats, .crx files start out with a signature, CrYpTeX9 in this case, followed by what looks like several data fields, and continuing into an apparently random byte sequence starting at address 0x18. If you look at the rest of the file, it all contains similarly unreadable junk. This indicates that the entire contents of the file have been encrypted, including the file table. As expected, none of the key strings such as the password, the asterisks.txt file name, or the actual asterisks can be found within this file. As further evidence that the file has been encrypted, we can use the Character Distribution feature in Hex Workshop to get an overview of the data within the file. Interestingly, we discover that the file contains seemingly random data, with an almost equal character distribution of about 0.4 percent for each of the 256 characters. It looks like the encryption algorithm applied by Cryptex has completely eliminated any obvious resemblance between the encrypted data and the password, file name, or file contents. At this point, it becomes clear that you re going to have to dig into the program in order to truly decipher the .crx file format. This is exactly where conventional code reversing and data reversing come together: you must look inside the program in order to see how it manages its data. Granted, this program is an extreme example because the data is encrypted, but even with programs that don t intentionally hide the contents of their file formats, it is often very difficult to decipher a file format by merely observing the data.

Special considerations were made for corners in the walls, or other places where wall geometry deviated from a straight line. These considerations were made by numerically solving the geometrical averaging of spatial variation for the particular geometries. 8 describes the importance of spatial and systematic uncertainty. Spatial correlations and systematic uncertainty in soil properties also affected the degree of correlation among the failures of multiple tanks, re wall segments, and revetment segments. First, the uncertainty in soil properties has both a systematic and a spatial component. The systematic component comprises estimation error in the mean and bias error in the geotechnical model used to interpret test results. This affects all the tanks, walls, etc. the same way. If the mean is in error under one tank, it is in error under all. Thus, to the extent that the probabilities of failure of the tanks, walls, etc. depend upon systematic uncertainty, they are perfectly correlated. At the same time, to the extent that the probabilities of failure depend on spatial variation, they are independent, but only if the individual facilities are widely separated in space. Adjacent tanks rest on soils which, given the autocovariance of the soil properties, have average properties that are to some degree correlated, and thus the probabilities of failure of the adjacent tanks must be to some degree correlated. Therefore, in calculating probabilities of failure, both the effects of systematic error and spatial correlation must be accommodated in inferring the degree of correlation among the failure probabilities of tanks, wall segments, and revetment segments.

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overcome the hurdles imposed by nonexecutable memory systems, as long as a vulnerable piece of code is found [Designer, Wojtczuk]. The most popular strategy (often called return-to-libc) is to modify the function s return address to point to a well-known function (such as a runtime library function or a system API) that helps attackers gain control over the process. This completely avoids the problem of having a nonexecutable stack, but requires a slightly more involved exploit.

Another type of overflow that can be used for taking control of a program or of the entire system is the malloc exploit or heap overflow [anonymous], [Kaempf], [jp] The general idea is the same as a stack overflow: programs receive data of an unexpected length and copy it into a buffer that s too small to contain it This causes the program to overwrite whatever it is that follows the heap block in memory Typically, heaps are arranged as linked lists, and the pointers to the next and previous heap blocks are placed either right before or right after the actual block data This means that writing past the end of a heap block would corrupt that linked list in some way.

Table 14.1 Soil pro le and ll property uncertainties for reliability analysis. (Christian, J. T., Ladd, C. C. and Baecher, G. B., 1994, Reliability Applied to Slope Stability Analysis, Journal of Geotechnical Engineering, ASCE, Vol. 120, No. 12, pp. 2180 2207, reproduced by permission of the American Society of Civil Engineers) Variance Variable Depth of crust Depth to till Fill density Fill friction Expected value 4m 18.5 m 20 kN/m3 30 Spatial 0.96 0.0 1.0 1.0 Systematic 0.04 1.0 1.0 3.0 Total 1.0 1.0 2.0 4.0

Usually, this causes the program to crash as soon as the heap manager traverses the linked list (in order to free a block for example), but when done carefully a heap overflow can be used to take over a system The idea is that attackers can take advantage of the heap s linked-list structure in order to overwrite some memory address in the process s address space Implementing such attacks can be quite complicated, but the basic idea is fairly straightforward Because each block in the linked list has next and prev members, it is possible to overwrite these members in a way that would allow the attacker to write an arbitrary value into an arbitrary address in memory Think of what takes place when an element is removed from a doubly linked list.

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