Type-based Dependency Analysis for JavaScript

Dependency analysis is a program analysis that determines potential data flow between program points. While it is not a security analysis per se, it is a viable basis for investigating data integrity, for ensuring confidentiality, and for guaranteeing sanitization. A noninterference property can be stated and proved for the dependency analysis. We have designed and implemented a dependency analysis for JavaScript. We formalize this analysis as an abstraction of a tainting semantics. We prove the correctness of the tainting semantics, the soundness of the abstraction, a noninterference property, and the termination of the analysis.Comment: Technical Repor

A Falsification View of Success Typing

Dynamic languages are praised for their flexibility and expressiveness, but static analysis often yields many false positives and verification is cumbersome for lack of structure. Hence, unit testing is the prevalent incomplete method for validating programs in such languages. Falsification is an alternative approach that uncovers definite errors in programs. A falsifier computes a set of inputs that definitely crash a program. Success typing is a type-based approach to document programs in dynamic languages. We demonstrate that success typing is, in fact, an instance of falsification by mapping success (input) types into suitable logic formulae. Output types are represented by recursive types. We prove the correctness of our mapping (which establishes that success typing is falsification) and we report some experiences with a prototype implementation.Comment: extended versio

Efficient Dynamic Access Analysis Using JavaScript Proxies

JSConTest introduced the notions of effect monitoring and dynamic effect inference for JavaScript. It enables the description of effects with path specifications resembling regular expressions. It is implemented by an offline source code transformation. To overcome the limitations of the JSConTest implementation, we redesigned and reimplemented effect monitoring by taking advantange of JavaScript proxies. Our new design avoids all drawbacks of the prior implementation. It guarantees full interposition; it is not restricted to a subset of JavaScript; it is self-maintaining; and its scalability to large programs is significantly better than with JSConTest. The improved scalability has two sources. First, the reimplementation is significantly faster than the original, transformation-based implementation. Second, the reimplementation relies on the fly-weight pattern and on trace reduction to conserve memory. Only the combination of these techniques enables monitoring and inference for large programs.Comment: Technical Repor

TreatJS: Higher-Order Contracts for JavaScript

TreatJS is a language embedded, higher-order contract system for JavaScript which enforces contracts by run-time monitoring. Beyond providing the standard abstractions for building higher-order contracts (base, function, and object contracts), TreatJS's novel contributions are its guarantee of non-interfering contract execution, its systematic approach to blame assignment, its support for contracts in the style of union and intersection types, and its notion of a parameterized contract scope, which is the building block for composable run-time generated contracts that generalize dependent function contracts. TreatJS is implemented as a library so that all aspects of a contract can be specified using the full JavaScript language. The library relies on JavaScript proxies to guarantee full interposition for contracts. It further exploits JavaScript's reflective features to run contracts in a sandbox environment, which guarantees that the execution of contract code does not modify the application state. No source code transformation or change in the JavaScript run-time system is required. The impact of contracts on execution speed is evaluated using the Google Octane benchmark.Comment: Technical Repor

LJGS: Gradual Security Types for Object-Oriented Languages (Artifact)

JGS-check is the accompanying artifact to "LJGS: Gradual Security Types for Object-Oriented Languages". LJGS is a Java-like language with gradual security typing. It features a constraint based information flow type system that includes a type dynamic and type casts. Dynamically typed fragments are liberally accepted by the type checker and rely on run-time enforcement for security. JGS-check is a type checker for the subset of Java that corresponds to the calculus presented in the paper and that implements the constraint generation and satisfiability checks of LJGS\u27 type system. It\u27s purpose is to illustrate and substantiate the behavior of our gradual security type system. It takes a directory of Java source code as input and reports methods that violate the typing rules. JGS-check is merely a type checker and does not implement code generation. The submission archive includes the compiled type checker, the code of the example section (Section 2) as well additional examples and testcases that did not fit into the paper. The user should also be able to check custom code as long as it corresponds the subset of Java that is covered by LJGS

LJGS: Gradual Security Types for Object-Oriented Languages

LJGS is a lightweight Java core calculus with a gradual security type system. The calculus guarantees secure information flow for sequential, class-based, typed object-oriented programming with mutable objects and virtual method calls. An LJGS program is composed of fragments that are checked either statically or dynamically. Statically checked fragments adhere to a security type system so that they incur no run-time penalty whereas dynamically checked fragments rely on run-time security labels. The programmer marks the boundaries between static and dynamic checking with casts so that it is always clear whether a program fragment requires run-time checks. LJGS requires security annotations on fields and methods. A field annotation either specifies a fixed static security level or it prescribes dynamic checking. A method annotation specifies a constrained polymorphic security signature. The types of local variables in method bodies are analyzed flow-sensitively and require no annotation. The dynamic checking of fields relies on a static points-to analysis to approximate implicit flows. We prove type soundness and non-interference for LJGS