Pattern language for a universal signature-based code analyzer

The process of signature-based code analysis in PT Application Inspector is divided into the following stages:
  1. Parsing into a language dependent representation (abstract syntax tree, AST).
  2. Converting an AST to a language (agnostic) unified format.
  3. A direct comparison with patterns described in the DSL.
The present article focuses on the third stage, namely: ways of describing patterns, development of a custom DSL language, which allows to describe patterns, and patterns written in this language.

Ways of describing patterns

  • Hardcoded patterns
  • JSON, XML or some other markup language
  • DSL, domain-specific language

Hardcoded patterns

Patterns can be manually written directly inside the code. There is no need to develop a parser. This approach is not suitable for non-developers, though it can be used for writing unit tests. Addition of new patterns requires recompilation of the whole program.

JSON, XML or some other markup language

Parts of the compared AST can be stored and retrieved directly from JSON or other data formats. This approach allows to load patterns from an external source; however, syntax will be bulky and unsuitable for editing by the user. Still, this method can be used for serialization of tree structures. (The next article in the series will present methods for serialization and bypassing of tree structures in .NET).

Custom language for pattern description, DSL

The third approach is the development of a special domain-specific language that will be easily editable, concise, but still having sufficient expressive power to describe existing and future patterns. A limitation to this approach is the need to develop the syntax and parser.


As mentioned in the first article, we can not simply describe all the patterns using regular expressions. The DSL is a mix of regular expressions and frequently used structures of programming languages. In addition, this language is designed for some particular domain knowledge and it is not expected to be used as some kind of a standard.


The second article in the series discusses the fact that the basic constructs in imperative programming languages are literals, expressions, and statements. We used a similar approach for the development of a DSL language. Examples of expressions:
  • expr(args); (method call)
  • Id expr = expr; (variable initialization)
  • expr + expr; (concatenation)
  • new Id(args); (object creation)
  • expr[expr]; (accessing an index or key).
Instructions are created by adding a semicolon at the end of the expression.
Literals are the primitive types, such as:
  • Id (an identifier)
  • String (a string enclosed in double quotes)
  • Int (an integer number)
  • Bool (a boolean value)
These literals allow you to describe simple constructs, but you can not describe a range of numbers or regular expressions using them. The advanced constructs (PatternStatement, PatternExpression, and PatternLiteral) were introduced to handle more complex cases. Such constructs are enclosed in special brackets. The syntax was borrowed from Nemerle language  (this language uses these special brackets for quasi-quotation, i.e. transforming the code in these brackets to an AST tree).
Examples of the supported advanced structures are presented in the list below. Syntactic sugar, that makes things easier to read or to express, has been introduced for some structures:
  • ; an extended expression operator (e.g., or )
  • # or ; any Expression
  • … or ; an arbitrary number of arguments of any kind
  • (expr.)?expr; is equivalent to expr.expr or expr
  • expr — expression negation;
  • expr ( expr)* — union of several expressions (logical OR)
  • Comment: \”regex\” — search through the comments

Examples of patterns

Hardcoded password (all languages)

(#.)? =
  • (#.)?; any expression, potentially absent
  • ; a regular expression for Id types, case insensitive
  • ; a regular expression for String types

Weak random number generator (C#, Java)

new Random(…)
The lack is caused by using an insecure algorithm for generating random numbers. Yet the standard Random class constructor is used to monitor such cases.

Debug information leak (PHP)

Configure.(\”debug\”, )
  • ;a regular expression for Id types, case insensitive and defines exact occurrences only
  • (\”debug\”, ); function arguments
  • ; a range of integers from 1 to 9

Insecure SSL connection (Java)

new AllowAllHostnameVerifier(…) SSLSocketFactory.ALLOW_ALL_HOSTNAME_VERIFIER
Using a \”logical OR\” with syntax structures. Matching both left (constructor invocation) and right (using a constant) part of a structure.

Password in comments (all languages)

Search for comments in the source code. Single-line comments begin with a double slash // in C#, Java, and PHP; while a double hyphen — is used in SQL-like languages.

SQL Injection (C#, Java, and PHP)

A simple SQL injection is the concatenation of any string beginning with SELECT and containing a non-string expression on the right side.
A cookie has been set without the Secure flag, which is configured in the fourth argument.

An empty try catch block (all languages)

try {…} catch { }
An empty exception handling block. If Pattern Matching module analyzes C# source code, the following code will be matched:
The matching result for T-SQL source code:
SELECT 1/0 AS DivideByZero
The matching result for PL/SQL source code:
PROCEDURE empty_default_exception_handler IS
INSERT INTO table1 VALUES(1, 2, 3, 4);
Cookie = new Cookie(…);
Adding a cookie without the Secure flag. Despite the fact that this pattern is better to implement using a taint analysis, we also managed to implement it using a more primitive matching algorithm. This algorithm uses a pinned @cookie variable (by analogy with back references in regex), negation of an expression, and an arbitrary number of statements.

Cursor Snarfing (PL/SQL, T-SQL)

A dangling cursor can be exploited by a less privileged user. Moreover, most unreleased resource issues result in general software reliability problems.
If Pattern Matching module analyzes T-SQL source code, the following code will be matched:

SELECT EmployeeID, Title FROM AdventureWorks2012.HumanResources.Employee;
OPEN Employee_Cursor;
FETCH NEXT FROM Employee_Cursor;
FETCH NEXT FROM Employee_Cursor;
--DEALLOCATE Employee_Cursor; is missing

Excessively granted privileges (PL/SQL, T-SQL)

This flaw may result in inappropriate and excessive privileges assigned to a user. Although the grant all phrase actually is an SQL query, it is converted into a function call, as the pattern matching module doesn\’t have a notion of a \”query\”.
The following code will be matched: GRANT ALL ON employees TO john_doe;


We’ve prepared a video to demonstrate the functionality of our Pattern Matching module in PT Application Inspector. This video explains the process of matching against certain patterns of the source code written in different programming languages (C#, Java, PHP). We also show you the proper way to handle syntax errors, which was discussed in the first article in this series.
Next time we will tell you about:
  • Matching, serialization and tree structures bypassing in .NET
  • Building the CFG, DFG and taint analysis
Author: Ivan Kochurkin, Positive Technologies

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