Abstract Symbolic execution is a popular program analysis technique that has been successfully used for bug-finding and bounded verification in various modern programming languages. Despite its popularity, however, symbolic execution suffers from two main limitations when applied to real-world code: interactions with the runtime environment and path explosion. Symbolic summaries are the standard solution to tackle these challenges. Yet, the development of summaries remains to this day a manual task that is known to be highly error-prone. To address this, we propose SumGen , a new tool for automatically generating correct-by-construction summaries from function specifications. With SumGen , we were able to generate a total of 131 summaries for 47 libc functions, demonstrating the effectiveness of our methodology in producing correct summaries for real-world, highly complex code.

SMT solvers are essential for applications in artificial intelligence, software verification, and optimisation. However, no single solver excels across all formula types, and different applications may require the use of different solvers. While the SMT-LIB language enables multi-solver support, it also incurs heavy I/O overhead. To address this, we introduce Smt.ml , an SMT-solver frontend for OCaml that simplifies integration with various solvers through a consistent interface. Its parametric encoding facilitates the easy addition of new solver backends, while optimisations like formula simplification, result caching, and detailed error feedback enhance performance and usability. Furthermore, Smt.ml is the only SMT frontend that includes a simplification-management engine for streamlining the integration of new formula simplifications and the verification of their correctness. Our evaluation demonstrates that Smt.ml ’s results are consistent with those of its backend solvers and that its optimisations are highly effective on formulas generated from the symbolic execution of an extensive program-analysis benchmark.

Cybersecurity has become important, especially during the last decade. The significant growth of information technologies, internet of things, and digitalization in general, increased the interest in cybersecurity professionals significantly. While the demand for cybersecurity professionals is high, there is a significant shortage of these professionals due to the very diverse landscape of knowledge and the complex curriculum accreditation process. In this article, we introduce a novel AI-driven mapping and optimization solution enabling cybersecurity curriculum development. Our solution leverages machine learning and integer linear programming optimization, offering an automated, intuitive, and user-friendly approach. It is designed to align with the European Cybersecurity Skills Framework (ECSF) released by the European Union Agency for Cybersecurity (ENISA) in 2022. Notably, our innovative mapping methodology enables the seamless adaptation of ECSF to existing curricula and addresses evolving industry needs and trend. We conduct a case study using the university curriculum from Brno University of Technology in the Czech Republic to showcase the efficacy of our approach. The results demonstrate the extent of curriculum coverage according to ECSF profiles and the optimization progress achieved through our methodology.

WebAssembly (Wasm) is a new binary instruction format that allows targeted compiled code written in high-level languages to be executed by the browser’s JavaScript engine with near-native speed. Despite its clear performance advantages, Wasm opens up the opportunity for bugs or security vulnerabilities to be introduced into Web programs, as pre-existing issues in programs written in unsafe languages can be transferred down to cross-compiled binaries. The source code of such binaries is frequently unavailable for static analysis, creating the demand for tools that can directly tackle Wasm code. Despite this potentially security-critical situation, there is still a noticeable lack of tool support for analysing Wasm binaries. We present WASP, a symbolic execution engine for testing Wasm modules, which works directly on Wasm code and was built on top of a standard-compliant Wasm reference implementation. WASP was thoroughly evaluated: it was used to symbolically test a generic data-structure library for C and the Amazon Encryption SDK for C, demonstrating that it can find bugs and generate high-coverage testing inputs for real-world C applications; and was further tested against the Test-Comp benchmark, obtaining results comparable to well-established symbolic execution and testing tools for C.

Automating the repair of vulnerabilities is emerging in the field of software security. Previous efforts have leveraged Automated Program Repair (APR) for the task. Reproducible pipelines of repair tools on vulnerability benchmarks can promote advances in the field, such as new repair techniques. We propose Maestro, a decentralized platform with RESTful APIs for performing automated software vulnerability repair. Our platform connects benchmarks of vulnerabilities with APR tools for performing controlled experiments. It also promotes fair comparisons among different APR tools. We compare the performance of Maestro with previous studies on four APR tools in finding repairs for ten projects. Our execution time results indicate an overhead of 23 seconds for projects in C and a reduction of 14 seconds for Java projects. We introduce an agnostic platform for vulnerability repair with preliminary tools/datasets for both C and Java. Maestro is modular and can accommodate tools, benchmarks, and repair workflows with dedicated plugins.

In the past years, research on automatic program repair (APR), in particular on test-suite-based approaches, has significantly attracted the attention of researchers. Despite the advances in the field, it remains unclear how these techniques fare in the context of security—most approaches are evaluated using benchmarks of bugs that do not (only) contain security vulnerabilities. In this paper, we present our observations using 10 state-of-the-art test-suite-based automatic program repair tools on the DARPA Cyber Grand Challenge benchmark of vulnerabilities in C/C++. Our intention is to have a better understanding of the current state of automatic program repair tools when addressing security issues. In particular, our study is guided by the hypothesis that the efficiency of repair tools may not generalize to security vulnerabilities. We found that the 10 analyzed tools can only fix 30 out of 55 vulnerable programs—54.6 % of the considered issues. In particular, we found that APR tools with atomic change operators and brute-force search strategy (AE and GenProg) and brute-force functionality deletion (Kali) overall perform better at repairing security vulnerabilities (considering both efficiency and effectiveness). AE is the tool that individually repairs most programs with 20 out of 55 programs (36.4%). The causes for failing to repair are discussed in the paper, which can help repair tool designers to improve their techniques and tools.

In complex networks, filters may be applied at different nodes to control how packets flow. In this paper, we study how to locate filtering functionality within a network. We show how to enforce a set of security goals while allowing maximal service subject to the security constraints. To implement our results we present a tool that given a network specification and a set of control rules automatically localizes the filters and generates configurations for all the firewalls in the network. These configurations are implemented using an extension of Mignis - an open source tool to generate firewalls from declarative, semantically explicit configurations. Our contributions include a way to specify security goals for how packets traverse the network, an algorithm to distribute filtering functionality to different nodes in the network to enforce a given set of security goals, and a proof that the results are compatible with a Mignis-based semantics for network behavior.

The management and specification of access control rules that enforce a given policy is a non-trivial, complex, and time consuming task. In this paper we aim at simplifying this task both at specification and verification levels. For that, we propose a formal model of Net filter, a firewall system integrated in the Linux kernel. We define an abstraction of the concepts of chains, rules, and packets existent in Net filter configurations, and give a semantics that mimics packet filtering and address translation. We then introduce a simple but powerful language that permits to specify firewall configurations that are unaffected by the relative ordering of rules, and that does not depend on the underlying Net filter chains. We give a semantics for this language and show that it can be translated into our Net filter abstraction. We then present Mignis, a publicly available tool that translates abstract firewall specifications into real Net filter configurations. Mignis is currently used to configure the whole firewall of the DAIS Department of Ca' Foscari University.

In the past few years, cryptographic key management APIs have been shown to be subject to tricky attacks based on the improper use of cryptographic keys. In fact, real APIs provide mechanisms to declare the intended use of keys but they are not strong enough to provide key security. In this paper, we propose a simple imperative programming language for specifying strongly-typed APIs for the management of symmetric, asymmetric and signing keys. The language requires that type information is stored together with the key but it is independent of the actual low-level implementation. We develop a type-based analysis to prove the preservation of integrity and confidentiality of sensitive keys and we show that our abstraction is expressive enough to code realistic key management APIs.

In their seminal work, Abadi and Rogaway show that the formal (Dolev–Yao) notion of indistinguishability is sound with respect to the computational model: messages that are indistinguishable in the formal model become indistinguishable messages in the computational model. However, this result leave s two problems unsolved. First, it cannot tolerate key cycles. Second, it makes the too-strong assumption that the underlying cryptography hides all aspects of the plaintext, including its length. In this paper we extend their work in order to address these problems. We show that the recently-introduced notion of KDM-security can provide soundness even in the presence of key cycles. For this, we have to consider encryption that reveals the length of plaintexts, which we use to motivate a general examination information-leaking encryption. In particular, we consider the conditions under which an encryption scheme that may leak some partial information will provide soundness and completeness to some (possibly weakened) version of the formal model.

We consider expansions of the Abadi-Rogaway logic of indistinguishability of formal cryptographic expressions. We expand the logic in order to cover cases when partial information of the encrypted plaintext is revealed. We consider not only computational, but also purely probabilistic, information-theoretic interpretations. We present a general, systematic treatment of the expansions of the logic for symmetric encryption. We establish general soundness and completeness theorems for the interpretations. We also present applications to specific settings not covered in earlier works: a purely probabilistic one based on one-time pad, and computational settings of the so-called type-2 (which-key revealing) and type-3 (which-key and length revealing) encryption schemes based on computational complexity.