In response to challenges in software supply chain security, several organisations have created infrastructures to independently build commodity open source projects and release the resulting binaries for Java/Maven and other software ecosystems. Build platform variability can strengthen security as it facilitates the detection of compromised build environments. Furthermore, by improving the security posture of the build platform and collecting provenance information during the build, the resulting artifacts can be used with greater trust. Such offerings are now available from Google, Oracle and RedHat. The availability of multiple binaries built from the same sources creates new challenges and opportunities, and raises questions such as: “Does build A confirm the integrity of build B?” or “Can build A reveal a compromised build B?”. To answer such questions requires a notion of equivalence between binaries. We demonstrate that the obvious approach based on bitwise equality has significant shortcomings in practice, and propose an alternative approach based on levels of equivalence, inspired by clone detection types. We demonstrate the value of these new levels through several experiments. For this purpose, we construct a dataset consisting of Java binaries (jar files) built from the same sources independently by different providers, resulting in 14,156 pairs of binaries in total. We then compare the compiled class files in those jar files and find that for$\mathbf{3, 7 5 0}$pairs of jars ($\mathbf{2 6. 4 9 \%}$) there is at least one such file that is different, also forcing the jar files and their cryptographic hashes to be different. However, based on the new equivalence levels, we can still establish that many of them are practically equivalent; the number of pairs of jars with non-equivalent classes drops to 13.65 % in some cases. We evaluate several candidate equivalence relations on a semi-synthetic dataset that provides oracles consisting of pairs of binaries that either should be, or must not be equivalent. This technique has been applied to evaluate artifacts built from source and used within Oracle's Graal Development Kit for Micronaut (GDK) product.

Modern web applications are getting more sophisticated by using frameworks that make development easy, but pose challenges for security analysis tools. New analysis techniques are needed to handle such frameworks that grow in number and popularity. In this paper, we describe Gelato that addresses the most crucial challenges for a security-aware client-side analysis of highly dynamic web applications. In particular, we use a feedback-driven and state-aware crawler that is able to analyze complex framework-based applications automatically, and is guided to maximize coverage of security-sensitive parts of the program. Moreover, we propose a new lightweight client-side taint analysis that outperforms the state-of-the-art tools, requires no modification to browsers, and reports non-trivial taint flows on modern JavaScript applications. Gelato reports vulnerabilities with higher accuracy than existing tools and achieves significantly better coverage on 12 applications of which three are used in production.

Enterprise applications are a major success domain of Java, and Java is the default setting for much modern static analysis research. It would stand to reason that high-quality static analysis of Java enterprise applications would be commonplace, but this is far from true. Major analysis frameworks feature virtually no support for enterprise applications and offer analyses that are woefully incomplete and vastly imprecise, when at all scalable.