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Joschua Schilling

Publications and source records attributed to Joschua Schilling.

3 recordsLinked to original sources

An Empirical Study of Fuzz Harness Degradation

The purpose of continuous fuzzing platforms is to enable fuzzing for software projects via fuzz harnesses -- but as the projects continue to evolve, are these harnesses updated in lockstep, or do they run out of date? If these harnesses remain unmaintained, will they degrade over time in terms of coverage achieved or number of bugs found? This is the subject of our study. We study Google's OSS-Fuzz continuous fuzzing platform containing harnesses for 510 open-source C/C++ projects, many of which are security-critical. A harness is the glue code between the fuzzer and the project, so it needs to adapt to changes in the project. It is often added by a project maintainer or as part of a, sometimes short-lived, testing effort. Our analysis shows a consistent overall fuzzer coverage percentage for projects in OSS-Fuzz and a surprising longevity of the bug-finding capability of harnesses even without explicit updates, as long as they still build. However, we also identify and manually examine individual cases of harness coverage degradation and categorize their root causes. Furthermore, we contribute to OSS-Fuzz and Fuzz Introspector to support metrics to detect harness degradation in OSS-Fuzz projects guided by this research.

cs.SE

SoK: Understanding Anti-Forensics Concepts and Research Practices Across Forensic Subdomains

Anti-forensics includes a growing set of techniques designed to obstruct forensic analysis. While cybercriminals increasingly rely on these methods, they also help researchers identify and remedy weaknesses in forensic tools, advancing the overall robustness of digital forensics. Despite repeated efforts to define it, anti-forensics remains vague and inconsistent in its use. It also poses ethical challenges regarding the appropriateness of research practices and the legitimacy of the field itself. This article presents a systematic analysis of 123 publications on anti-forensics, combining qualitative and quantitative methods. We quantify the main techniques and attack vectors, examine their occurrence in different digital forensic subdomains, and identify typical research methods, motivations, and applications. This work also discusses what these findings mean for future research and proposes directions for building a more coherent and ethically grounded understanding of anti-forensics.

cs.CR

Anota: Identifying Business Logic Vulnerabilities via Annotation-Based Sanitization

Detecting business logic vulnerabilities is a critical challenge in software security. These flaws come from mistakes in an application's design or implementation and allow attackers to trigger unintended application behavior. Traditional fuzzing sanitizers for dynamic analysis excel at finding vulnerabilities related to memory safety violations but largely fail to detect business logic vulnerabilities, as these flaws require understanding application-specific semantic context. Recent attempts to infer this context, due to their reliance on heuristics and non-portable language features, are inherently brittle and incomplete. As business logic vulnerabilities constitute a majority (27/40) of the most dangerous software weaknesses in practice, this is a worrying blind spot of existing tools. In this paper, we tackle this challenge with ANOTA, a novel human-in-the-loop sanitizer framework. ANOTA introduces a lightweight, user-friendly annotation system that enables users to directly encode their domain-specific knowledge as lightweight annotations that define an application's intended behavior. A runtime execution monitor then observes program behavior, comparing it against the policies defined by the annotations, thereby identifying deviations that indicate vulnerabilities. To evaluate the effectiveness of ANOTA, we combine ANOTA with a state-of-the-art fuzzer and compare it against other popular bug finding methods compatible with the same targets. The results show that ANOTA+FUZZER outperforms them in terms of effectiveness. More specifically, ANOTA+FUZZER can successfully reproduce 43 known vulnerabilities, and discovered 22 previously unknown vulnerabilities (17 CVEs assigned) during the evaluation. These results demonstrate that ANOTA provides a practical and effective approach for uncovering complex business logic flaws often missed by traditional security testing techniques.

cs.CR