arXiv subjects

Eleonora Losiouk

Publications and source records attributed to Eleonora Losiouk.

10 recordsLinked to original sources

arXiv2026

Towards LLM-Enhanced Android Taint Analysis

Taint analysis is a fundamental technique for detecting sensitive data leaks in Android apps. However, traditional static tools, such as FlowDroid, still face well-known challenges due to the complexity of accurately modeling the Android framework. In this paper, we investigate whether off-the-shelf Large Language Models (LLMs) can effectively reason about taint flows in Android apps. Our preliminary approach relies on an agentic interaction strategy, enabling the LLM to iteratively explore code and reason about data flows. We conduct an initial evaluation on the DroidBench benchmark against FlowDroid, where our approach outperforms the baseline: Gemini-3 Flash achieves an F1-score of 0.96, compared to 0.55 for FlowDroid. In particular, we observe improvements in challenging categories such as inter-component communication (0.95 vs. 0.17), implicit flows (0.94 vs. 0.00), and reflection (1.00 vs. 0.50), where FlowDroid typically struggles. On a small set of real-world apps, the LLM-based approach also identifies additional potential data leaks not reported by FlowDroid. These preliminary findings suggest that LLM reasoning may effectively complement traditional static taint analysis, motivating future research on hybrid LLM-enhanced taint analysis pipelines.

cs.SE↗

arXiv2026

GAPS: Targeted Execution of Android Apps via Static Path Reconstruction

Targeted execution of Android applications (apps) remains a longstanding challenge for software testing and analysis. Although recent advances in GUI testing have substantially improved app exploration, existing approaches remain largely coverage-driven and struggle to steer execution reliably toward specific methods of interest. This limitation hinders important downstream tasks, such as vulnerability detection, program comprehension, and dynamic analysis. We present GAPS (Graph-based Automated Path Synthesizer), the first approach to bridge static program analysis and dynamic GUI exploration, enabling targeted execution in Android apps. Given a target method, GAPS performs a lightweight static backward traversal of the call graph, enriched with data-flow reasoning, to identify feasible execution paths that lead to the target. It then translates these paths into actionable execution strategies that guide dynamic interactions with the app. We evaluate GAPS on the AndroTest benchmark and show that it reconstructs paths toward 88.24% of the target methods, requiring only 12.67 seconds per app on average. During dynamic execution, GAPS reaches 56.93% of the target methods, outperforming state-of-the-art alternatives. In comparison, the model-based GUI testing tool APE reaches only 11.12%, the hybrid exploration framework GoalExplorer reaches 4.75%, and the recent LLM-driven approach Guardian reaches 34%. To assess scalability in real-world settings, we further evaluate GAPS across the 50 most-downloaded apps on the Google Play Store. GAPS reconstructs execution paths toward 62.03% of the target methods, averaging 278.9 seconds per app, and dynamically reaches 54.80% of them. These results show that combining static path synthesis with guided dynamic exploration provides an effective and scalable solution for targeted method execution in Android apps.

cs.SE↗

arXiv2026

Evaluating LLM-Based Regression Test Generation

Large Language Models (LLMs) have shown tremendous promise in automated software engineering. In this paper, we investigate LLMs for just-in-time regression test generation for programs, like parsers, interpreters, or compilers, that take highly structured, human-readable inputs. When a bug fix or code change is committed, the repository (as part of CI/CD) runs an LLM for a few minutes to generate regression tests that exercise the changed code and potentially trigger bugs. We frame LLM-based regression test generation as a machine translation task that takes the developer-provided commit message, the code change, and the input format name (e.g., XML), and produces regression tests for the described change in that format. Testing 72 commits to Mujs, Libxml2, Poppler, JerryScript, Z3, PHP, JQ, and MicroPython, our feedback-directed, zero-shot prototype Cleverest performed well, even without the code change. In under 2 minutes on average, Cleverest found as many bugs as the state-of-the-art directed greybox fuzzer WAFLGo did in 24 hours, even though WAFLGo started with a commit-reaching seed corpus in most cases. Using the Cleverest-generated tests as a seed corpus in coverage-guided greybox fuzzing doubles the number of bugs found; we call this integration ClevFuzz. We also find that some commit messages are more expressive than others, thus we ask how it impacts Cleverest's effectiveness. Cleverest picks up on the change intention: e.g., given a commit message that a patch changes how floating point variables are treated in the Mujs JavaScript interpreter, Cleverest generates JavaScript programs that contain floating point variables. Minimally changing commit messages to reduce or increase their information substantially impacts effectiveness: adding 17 words on average (max. 43) to make ineffective commit messages more expressive significantly increased the number of bugs found.

cs.SE↗

arXiv2025

E-Trojans: Ransomware, Tracking, DoS, and Data Leaks on Battery-powered Embedded Systems

Battery-powered embedded systems (BESs) have become ubiquitous. Their internals include a battery management system (BMS), a radio interface, and a motor controller. Despite their associated risk, there is little research on BES internal attack surfaces. To fill this gap, we present the first security and privacy assessment of e-scooters internals. We cover Xiaomi M365 (2016) and ES3 (2023) e-scooters and their interactions with Mi Home (their companion app). We extensively RE their internals and uncover four critical design vulnerabilities, including a remote code execution issue with their BMS. Based on our RE findings, we develop E-Trojans, four novel attacks targeting BES internals. The attacks can be conducted remotely or in wireless proximity. They have a widespread real-world impact as they violate the Xiaomi e-scooter ecosystem safety, security, availability, and privacy. For instance, one attack allows the extortion of money from a victim via a BMS undervoltage battery ransomware. A second one enables user tracking by fingerprinting the BES internals. With extra RE efforts, the attacks can be ported to other BES featuring similar vulnerabilities. We implement our attacks and RE findings in E-Trojans, a modular and low-cost toolkit to test BES internals. Our toolkit binary patches BMS firmware by adding malicious capabilities. It also implements our undervoltage battery ransomware in an Android app with a working backend. We successfully test our four attacks on M365 and ES3, empirically confirming their effectiveness and practicality. We propose four practical countermeasures to fix our attacks and improve the Xiaomi e-scooter ecosystem security and privacy.

cs.CR↗

arXiv2023

Beware of Pickpockets: A Practical Attack against Blocking Cards

Today, we rely on contactless smart cards to perform several critical operations (e.g., payments and accessing buildings). Attacking smart cards can have severe consequences, such as losing money or leaking sensitive information. Although the security protections embedded in smart cards have evolved over the years, those with weak security properties are still commonly used. Among the different solutions, blocking cards are affordable devices to protect smart cards. These devices are placed close to the smart cards, generating a noisy jamming signal or shielding them. Whereas vendors claim the reliability of their blocking cards, no previous study has ever focused on evaluating their effectiveness. In this paper, we shed light on the security threats on smart cards in the presence of blocking cards, showing the possibility of being bypassed by an attacker. We analyze blocking cards by inspecting their emitted signal and assessing a vulnerability in their internal design. We propose a novel attack that bypasses the jamming signal emitted by a blocking card and reads the content of the smart card. We evaluate the effectiveness of 11 blocking cards when protecting a MIFARE Ultralight smart card and a MIFARE Classic card. Of these 11 cards, we managed to bypass 8 of them and successfully dump the content of a smart card despite the presence of the blocking card. Our findings highlight that the noise type implemented by the blocking cards highly affects the protection level achieved by them. Based on this observation, we propose a countermeasure that may lead to the design of effective blocking cards. To further improve security, we released the tool we developed to inspect the spectrum emitted by blocking cards and set up our attack.

cs.CR↗

arXiv2023

Security and Privacy of IP-ICN Coexistence: A Comprehensive Survey

Today Internet is experiencing a massive number of users with a continuously increasing need for data, which is the leading cause of introduced limitations among security and privacy issues. To overcome these limitations, a shift from host-centric to data-centric is proposed, and in this context, Information-Centric Networking (ICN) represents a promising solution. Nevertheless, unsettling the current Internet network layer, i.e., Internet Protocol (IP), with ICN is a challenging, expensive task since it requires worldwide coordination among Internet Service Providers (ISPs), backbone, and Autonomous Services (AS). Therefore, researchers foresee that the replacement process of the current Internet will transition through the coexistence of IP and ICN. In this perspective, novel architectures combine IP and ICN protocols. However, only a few of the proposed architectures place the security-by-design feature. Therefore, this article provides the first comprehensive Security and Privacy (SP) analysis of the state-of-the-art IP-ICN coexistence architectures by horizontally comparing the SP features among three deployment approaches, i.e., overlay, underlay, and hybrid, and vertically comparing among the ten considered SP features. Lastly, the article sheds light on the open issues and possible future directions for IP-ICN coexistence. Our analysis shows that most architectures fail to provide several SP features, including data and traffic flow confidentiality, availability, and anonymity of communication. Thus, this article shows the secure combination of current and future protocol stacks during the coexistence phase that the Internet will definitely walk across.

cs.CR↗

arXiv2020

Contact Tracing Made Un-relay-able

Automated contact tracing is a key solution to control the spread of airborne transmittable diseases: it traces contacts among individuals in order to alert people about their potential risk of being infected. The current SARS-CoV-2 pandemic put a heavy strain on the healthcare system of many countries. Governments chose different approaches to face the spread of the virus and the contact tracing apps were considered the most effective ones. In particular, by leveraging on the Bluetooth Low-Energy technology, mobile apps allow to achieve a privacy-preserving contact tracing of citizens. While researchers proposed several contact tracing approaches, each government developed its own national contact tracing app. In this paper, we demonstrate that many popular contact tracing apps (e.g., the ones promoted by the Italian, French, Swiss government) are vulnerable to relay attacks. Through such attacks people might get misleadingly diagnosed as positive to SARS-CoV-2, thus being enforced to quarantine and eventually leading to a breakdown of the healthcare system. To tackle this vulnerability, we propose a novel and lightweight solution that prevents relay attacks, while providing the same privacy-preserving features as the current approaches. To evaluate the feasibility of both the relay attack and our novel defence mechanism, we developed a proof of concept against the Italian contact tracing app (i.e., Immuni). The design of our defence allows it to be integrated into any contact tracing app.

cs.CR↗

arXiv2020

Mascara: A Novel Attack Leveraging Android Virtualization

Android virtualization enables an app to create a virtual environment, in which other apps can run. Originally designed to overcome the limitations of mobile apps dimensions, malicious developers soon started exploiting this technique to design novel attacks. As a consequence, researchers proposed new defence mechanisms that enable apps to detect whether they are running in a virtual environment. In this paper, we propose Mascara, the first attack that exploits the virtualization technique in a new way, achieving the full feasibility against any Android app and proving the ineffectiveness of existing countermeasures. Mascara is executed by a malicious app, that looks like the add-on of the victim app. As for any other add-on, our malicious one can be installed as a standard Android app, but, after the installation, it launches Mascara against the victim app. The malicious add-on is generated by Mascarer, the framework we designed and developed to automate the whole process. Concerning Mascara, we evaluated its effectiveness against three popular apps (i.e., Telegram, Amazon Music and Alamo) and its capability to bypass existing mechanisms for virtual environments detection. We analyzed the efficiency of our attack by measuring the overhead introduced at runtime by the virtualization technique and the compilation time required by Mascarer to generate 100 malicious add-ons (i.e., less than 10 sec). Finally, we designed a robust approach that detects virtual environments by inspecting the fields values of ArtMethod data structures in the Android Runtime (ART) environment.

cs.CR↗

arXiv2019

The Road Ahead for Networking: A Survey on ICN-IP Coexistence Solutions

In recent years, the current Internet has experienced an unexpected paradigm shift in the usage model, which has pushed researchers towards the design of the Information-Centric Networking (ICN) paradigm as a possible replacement of the existing architecture. Even though both Academia and Industry have investigated the feasibility and effectiveness of ICN, achieving the complete replacement of the Internet Protocol (IP) is a challenging task. Some research groups have already addressed the coexistence by designing their own architectures, but none of those is the final solution to move towards the future Internet considering the unaltered state of the networking. To design such architecture, the research community needs now a comprehensive overview of the existing solutions that have so far addressed the coexistence. The purpose of this paper is to reach this goal by providing the first comprehensive survey and classification of the coexistence architectures according to their features (i.e., deployment approach, deployment scenarios, addressed coexistence requirements and architecture or technology used) and evaluation parameters (i.e., challenges emerging during the deployment and the runtime behaviour of an architecture). We believe that this paper will finally fill the gap required for moving towards the design of the final coexistence architecture.

cs.NI↗

arXiv2019

ScaRR: Scalable Runtime Remote Attestation for Complex Systems

The introduction of remote attestation (RA) schemes has allowed academia and industry to enhance the security of their systems. The commercial products currently available enable only the validation of static properties, such as applications fingerprint, and do not handle runtime properties, such as control-flow correctness. This limitation pushed researchers towards the identification of new approaches, called runtime RA. However, those mainly work on embedded devices, which share very few common features with complex systems, such as virtual machines in a cloud. A naive deployment of runtime RA schemes for embedded devices on complex systems faces scalability problems, such as the representation of complex control-flows or slow verification phase. In this work, we present ScaRR: the first Scalable Runtime Remote attestation schema for complex systems. Thanks to its novel control-flow model, ScaRR enables the deployment of runtime RA on any application regardless of its complexity, by also achieving good performance. We implemented ScaRR and tested it on the benchmark suite SPEC CPU 2017. We show that ScaRR can validate on average 2M control-flow events per second, definitely outperforming existing solutions.

cs.CR↗