Figure 48 Three data ow rules work together to detect a command injection vulnerability in Java

Encoder USS Code 39 in Java Figure 48 Three data ow rules work together to detect a command injection vulnerability
Figure 48 Three data ow rules work together to detect a command injection vulnerability
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Rules
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In its simplest form, taint is a binary attribute of a piece of data the value is either tainted or untainted In reality, input validation problems are not nearly so clear cut Input can be trusted for some purposes, but not for others For example, the argument parameters passed to a C program s main() function are not trustworthy, but most operating systems guarantee that the strings in the argv array will be null-terminated, so it is safe to treat them as strings To represent the fact that data can be trusted for some purposes but not for others, different varieties of tainted data can be modeled as carriers of different taint ags Taint ags can be applied in a number of different ways First, different source rules can introduce data with different taint ags Data from the network could be marked FROM_NETWORK, and data from a con guration le might be marked FROM_CONFIGURATION If these taint ags are carried over into the static analysis output, they allow an auditor to prioritize output based on the source of the untrusted data Second, sink functions might be dangerous only when reached by data carrying a certain type of taint A cross-site scripting sink is vulnerable when it receives arbitrary user-controlled data, but not when it receives only numeric data Source, sink, and pass-through rules can manipulate taint in either an additive or a subtractive manner We have seen successful implementations of both approaches In the subtractive case, source rules introduce data carrying all the taint ags that might possibly be of concern Input validation functions are modeled with pass-through rules that strip the appropriate taint ags, given the type of validation they perform Sink rules check for dangerous operations on tainted data or for tainted data escaping from the application tier (such as passing from business logic to back-end code) and trigger if any of the offending taint ags are still present In the additive case, source rules introduce data tainted in a generic fashion, and inputvalidation functions add taint ags based on the kind of validation they perform, such as VALIDATED_XSS for a function that validates against crosssite scripting attacks Sinks ll the same role as in the subtractive case, ring either when a dangerous operation is performed on an argument that does not hold an appropriate set of taint ags or when data leave the application tier without all the necessary taint ags Rules in Print Throughout Part II, Pervasive Problems, and Part III, Features and Flavors, we discuss techniques for using static analysis to identify speci c security problems in source code These discussions take the form of
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specially formatted callouts labeled Static Analysis Many of these sections include a discussion of speci c static analysis rules that you can use to solve the problem at hand For the most part, formats that are easy for a computer to understand, such as the XML rule de nition that appears earlier in this chapter, are not ideal for human consumption For this reason, we introduce a special syntax here for de ning rules This is the rule syntax we use for the remainder of the book Con guration Rules We specify con guration rules for XML documents with XPath expressions The rule de nitions also include a le pattern to control which les the static analysis tool applies the XPath expression to, such as webxml or *xml Model Checking Rules Instead of giving their de nitions textually, we present model checking rules using state machine diagrams similar to the one found earlier in this chapter Each model checking diagram includes an edge labeled start that indicates the initial state the rule takes on, and has any number of transitions leading to other states that the analysis algorithm will follow whenever it encounters the code construct associated with the transition Structural Rules We describe structural rules using the special language introduced in the sidebar earlier this chapter Properties in the language correspond to common properties in source code, and most rules are straightforward to understand without any existing knowledge of the language Taint Propagation Rules Taint propagation rules in the book include a combination of the following elements: Method or function De nes the method or function that the rule will match All aspects of the rule are applied only to code constructs that match this element, which can include special characters, such as the wildcard (*) or the logical or operator (|) Precondition De nes conditions on the taint propagation algorithm s state that must be met for the rule to trigger Precondition statements typically specify which arguments to a function must not be tainted or which taint ags must or must not be present, so preconditions stand for
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