Java Bytecode Verification Research Articles

Java Bytecode Verification with OCL Why, How and Whenc.

Java Bytecode Verification with OCL Why, How and Whenc.

Using Contour Marking Bytecode Verification Algorithm on the Java Card

Java bytecode verification could not be well performed in the smart card due to the resource usage especially in the resource-constrained devices. Currently, on the card there are several bytecode verifications which exist kinds of problems, in order to be better and be better adapt to the environment, such as a smart card platform, raised using the contour subroutine labeled bytecode verification algorithm on a card. First, through the analysis of existing card byte code verification algorithm to determine the imperfections and difficulties in the judgment and the verification of subroutine, and then propose a method for marking the subroutine in the place of the jump to it. Thus not only get the program structure and enhance the effectiveness and efficiency of the validation. The feasibility of the method is demonstrated by simulating typical examples verification.

Java bytecode verification via static single assignment form

Java Virtual Machines (JVMs) traditionally perform bytecode verification by way of an iterative dataflow analysis. Bytecode verification is necessary to ensure type safety because temporary variables in the JVM are not statically typed. We present an alternative verification mechanism that transforms JVM bytecode into Static Single Assignment Form (SSA) and thereby propagates definitions directly to uses. Type checking at control flow merge points can then be performed in a single pass. Our prototype implementation of the new algorithm is faster than the standard JVM bytecode verifier. It has the additional benefit of generating SSA as a side effect, which may be immediately useful for a subsequent dynamic compilation stage.

Instruction-level security typing by abstract interpretation

We present a method based on abstract interpretation to check secure information flow in programs with dynamic structures where input and output channels are associated with security levels. In the concrete operational semantics each value is annotated by a security level dynamically taking into account both the explicit and the implicit information flows. We define a collecting semantics which associates with each program point the set of concrete states of the machine when the point is reached. The abstract domains are obtained from the concrete ones by keeping the security levels and forgetting the actual values. Using this framework, we define an abstract semantics, called instruction-level security typing, that allows us to certify a larger set of programs with respect to the typing approaches to check secure information flow. An efficient implementation is shown, operating a fixpoint iteration similar to that of the Java bytecode verification.

Kleene Algebra and Bytecode Verification

Most standard approaches to the static analysis of programs, such as the popular worklist method, are first-order methods that inductively annotate program points with abstract values. In [6] we introduced a second-order approach based on Kleene algebra. In this approach, the primary objects of interest are not the abstract data values, but the transfer functions that manipulate them. These elements form a left-handed Kleene algebra. The dataflow labeling is not achieved by inductively labeling the program with abstract values, but rather by computing the star (Kleene closure) of a matrix of transfer functions. In this paper we show how this general framework applies to the problem of Java bytecode verification. We show how to specify transfer functions arising in Java bytecode verification in such a way that the Kleene algebra operations (join, composition, star) can be computed efficiently. We also give a hybrid dataflow analysis algorithm that computes the closure of a matrix on a cutset of the control flow graph, thereby avoiding the recalculation of dataflow information when there are cycles in the graph. This method could potentially improve the performance over the standard worklist algorithm when a small cutset can be found.

Memory Requirements of Java Bytecode Verification on Limited Devices

Bytecode verification forms the corner stone of the Java security model that ensures the integrity of the runtime environment even in the presence of untrusted code. Limited devices, like Java smart cards, lack the necessary amount of memory to verify the type-safety of Java bytecode on their own. Proof carrying code techniques compute, outside the device, tamper-proof certificates which simplify bytecode verification and pass them along with the code. Rose has developed such an approach for a small subset of the Java bytecode language.In this paper, we extend this approach to real world Java software and develop a precise model of the memory requirements on the device. We use a variant of interval graphs to model liveness of memory regions in the checking step. Based on this model, memory-optimal checking strategies are computed outside the device and attached to the certificate.The underlying type system of the bytecode verifier has been augmented with multi-dimensional arrays and recognizes references to uninitialized Java objects.Our detailed measurements, based on real world Java libraries, demonstrate that the approach offers a substantial improvement in size of certificate over the similar approach taken by the KVM verifier. Worst case memory consumption on the device is examined as well and it turns out that the refinements based on our model save a significant amount of memory.

Integrated Java Bytecode Verification

Existing Java verifiers perform an iterative data-flow analysis to discover the unambiguous type of values stored on the stack or in registers. Our novel verification algorithm uses abstract interpretation to obtain definition/use information for each register and stack location in the program, which in turn is used to transform the program into Static Single Assignment form. In SSA, verification is reduced to simple type compatibility checking between the definition type of each SSA variable and the type of each of its uses. Inter-adjacent transitions of a value through stack and registers are no longer verified explicitly. This integrated approach is more efficient than traditional bytecode verification but still as safe as strict verification, as overall program correctness can be induced once the data flow from each definition to all associated uses is known to be type-safe.

Improving the official specification of Java bytecode verification

AbstractBytecode verification is the main mechanism to ensure type safety in the Java Virtual Machine. Inadequacies in its official specification may lead to incorrect implementations where security can be broken and/or certain legal programs are rejected. This paper provides a comprehensive analysis of the specification, along with concrete suggestions for improvement. Copyright © 2003 John Wiley & Sons, Ltd.

Java Bytecode Verification: Algorithms and Formalizations

Bytecode verification is a crucial security component for Java applets, on the Web and on embedded devices such as smart cards. This paper reviews the various bytecode verification algorithms that have been proposed, recasts them in a common framework of dataflow analysis, and surveys the use of proof assistants to specify bytecode verification and prove its correctness.

Bytecode Verification by Model Checking

Java bytecode verification is traditionally performed by using dataflow analysis. We investigate an alternative based on reducing bytecode verification to model checking. First, we analyze the complexity and scalability of this approach. We show experimentally that, despite an exponential worst-case time complexity, model checking type-correct bytecode using an explicit-state on-the-fly model checker is feasible in practice, and we give a theoretical account why this is the case. Second, we formalize our approach using Isabelle/HOL and prove its correctness. In doing so we build on the formalization of the Java Virtual Machine and dataflow analysis framework of Pusch and Nipkow and extend it to a more general framework for reasoning about model-checking-based analysis. Overall, our work constitutes the first comprehensive investigation of the theory and practice of bytecode verification by model checking.

Verified Bytecode Subroutines

Bytecode subroutines are a major complication for Java bytecode verification: They are difficult to fit into the dataflow analysis that the JVM specification suggests. Hence, subroutines are left out or are restricted in most formalizations of the bytecode verifier. We examine the problems that occur with subroutines and give an overview of the most prominent solutions in the literature. Using the theorem prover Isabelle/HOL, we have extended our substantial formalization of the JVM and the bytecode verifier with its proof of correctness by the most general solution for bytecode subroutines.

Proof linking

Although mobile code systems typically employ link-time code verifiers to protect host computers from potentially malicious code, implementation flaws in the verifiers may still leave the host system vulnerable to attack. Compounding the inherent complexity of the verification algorithms themselves, the need to support lazy, dynamic linking in mobile code systems typically leads to architectures that exhibit strong interdependencies between the loader, the verifier, and the linker. To simplify verifier construction and provide improved assurances of verifier integrity, we propose a modular architecture based on the concept of proof linking. This architecture encapsulates the verification process and removes dependencies between the loader, the verifier, and the linker. We also formally model the process of proof linking and establish properties to which correct implementations must conform. As an example, we instantiate our architecture for the problem of Java bytecode verification and assess the correctness of this instantiation. Finally, we briefly discuss alternative mobile code verification architectures enabled by the proof-linking concept.

Standard fixpoint iteration for Java bytecode verification

Java bytecode verification forms the basis for Java-based Internet security and needs a rigorous description. One important aspect of bytecode verification is to check if a Java Virtual Machine (JVM) program is statically well-typed. So far, several formal specifications have been proposed to define what the static well-typedness means. This paper takes a step further and presents a chaotic fixpoint iteration, which represents a family of fixpoint computation strategies to compute a least type for each JVM program within a finite number of iteration steps. Since a transfer function in the iteration is not monotone, we choose to follow the example of a nonstandard fixpoint theorem, which requires that all transfer functions are increasing, and monotone in case the bigger element is already a fixpoint. The resulting least type is the artificial top element if and only if he JVM program is not statically well-typed. The iteration is standard and close to Sun's informal specification and most commercial bytecode verifiers.

Proof linking

Security flaws are routinely discovered in commercial implementations of mobile code systems such as the Java Virtual Machine (JVM). Typical architectures for such systems exhibit complex interdependencies between the loader, the verifier, and the linker, making them difficult to craft, validate, and maintain. This reveals a software engineering challenge that is common to all mobile code systems in which a static verification phase is introduced before dynamic linking. In such systems, one has to articulate how loading, verification, and linking interact with each other, and how the three processes should be organized to address various security issues.We propose a standard architecture for crafting mobile code verifiers, based on the concept of proof linking. This architecture modularizes the verification process and isolates the dependencies among the loader, verifier, and linker. We also formalize the process of proof linking and establish properties to which correct implementations must conform. As an example, we instantiate our architecture for the problem of Java bytecode verification and assess the correctness of this instantiation. Finally, we briefly discuss alternative mobile code verification architectures enabled by our modularization.