Static Analysis Internals in Java

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Static Analysis Internals
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his chapter is about what makes static analysis tools tick We look at the internal workings of advanced static analysis tools, including data structures, analysis techniques, rules, and approaches to reporting results Our aim is to explain enough about what goes into a static analysis tool that you can derive maximum bene t from the tools you use For readers interested in creating their own tools, we hope to lay enough groundwork to provide a reasonable starting point Regardless of the analysis techniques used, all static analysis tools that target security function in roughly the same way, as shown in Figure 41 They all accept code, build a model that represents the program, analyze that model in combination with a body of security knowledge, and nish by presenting their results back to the user This chapter walks through the process and takes a closer look at each step
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if ( fgets ( buf , sizeof(buf) stdin) == buf ) { strcpy ( othr , buf ); system ( othr );
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Figure 41 A block diagram for a generic static analysis security tool At a high level, almost all static analysis security tools work this way
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4 Static Analysis Internals
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The rst thing a static analysis tool needs to do is transform the code to be analyzed into a program model, a set of data structures that represent the code As you would expect, the model a tool creates is closely linked to the kind of analysis it performs, but generally static analysis tools borrow a lot from the compiler world In fact, many static analysis techniques were developed by researchers working on compilers and compiler optimization problems If you are interested in an in-depth look at compilers, we recommend both the classic textbook Compilers: Principles, Techniques, and Tools (often called the dragon book ), by Aho, Sethi, and Ullman [Aho et al, 2006], and Appel s Modern Compiler Implementation series (often called the tiger books ) [Appel, 1998] We now take a brief tour of the most important techniques and data structures that compilers and static analysis tools share Lexical Analysis Tools that operate on source code begin by transforming the code into a series of tokens, discarding unimportant features of the program text such as whitespace or comments along the way The creation of the token stream is called lexical analysis Lexing rules often use regular expressions to identify tokens Example 41 gives a simple set of lexing rules that could be used to process the following C program fragment:
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This code produces the following sequence of tokens:
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IF LPAREN ID(ret) RPAREN ID(mat) LBRACKET ID(x) RBRACKET LBRACKET ID(y) RBRACKET EQUAL ID(END_VAL) SEMI
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Notice that most tokens are represented entirely by their token type, but to be useful, the ID token requires an additional piece of information: the name of the identi er To enable useful error reporting later, tokens should carry at least one other kind of information with them: their position in the source text (usually a line number and a column number) For the simplest of static analysis tools, the job is nearly nished at this point If all the tool is going to do is match the names of dangerous functions, the analyzer can go through the token stream looking for identi ers,
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match them against a list of dangerous function names, and report the results This is the approach taken by ITS4, RATS, and Flaw nder
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Example 41 Sample lexical analysis rules
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if ( ) [ ] = ; /[ \t\n]+/ /\/\/*/ /[a-zA-Z][a-zA-Z0-9]*"/ { { { { { { { { { { return IF; } return LPAREN; } return RPAREN; } return LBRACKET; } return LBRACKET; } return EQUAL; } return SEMI; } /* ignore whitespace */ } /* ignore comments */ } return ID; }
Parsing A language parser uses a context-free grammar (CFG) to match the token stream The grammar consists of a set of productions that describe the symbols (elements) in the language Example 42 lists a set of productions that are capable of parsing the sample token stream (Note that the de nitions for these productions would be much more involved for a full-blown language parser)