Sleeping giants: activating dormant java deserialization gadget chains through stealthy code changes
2025 (Engelska)Ingår i: CCS 2025 - Proceedings of the 2025 ACM SIGSAC Conference on Computer and Communications Security, Association for Computing Machinery (ACM), 2025, s. 2668-2682Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]
Java deserialization gadget chains are a well-researched critical software weakness. The vast majority of known gadget chains rely on gadgets from software dependencies. Furthermore, it has been shown that small code changes in dependencies have enabled these gadget chains. This makes gadget chain detection a purely reactive endeavor. Even if one dependency's deployment pipeline employs gadget chain detection, a gadget chain can still result from gadgets in other dependencies. In this work, we assess how likely small code changes are to enable a gadget chain. These changes could either be accidental or intentional as part of a supply chain attack. Specifically, we show that class serializability is a strongly fluctuating property over a dependency's evolution. Then, we investigate three change patterns by which an attacker could stealthily introduce gadgets into a dependency. We apply these patterns to 533 dependencies and run three state-of-the-art gadget chain detectors both on the original and the modified dependencies. The tools detect that applying the modification patterns can activate/inject gadget chains in 26.08% of the dependencies we selected. Finally, we verify the newly detected chains. As such, we identify dormant gadget chains in 53 dependencies that could be added through minor code modifications. This both shows that Java deserialization gadget chains are a broad liability to software and proves dormant gadget chains as a lucrative supply chain attack vector.
Ort, förlag, år, upplaga, sidor
Association for Computing Machinery (ACM), 2025. s. 2668-2682
Nyckelord [en]
Bug Injection, Dependency, Deserialization, Gadget Chain, Java, Serializable, Software Supply Chain
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Sannolikhetsteori och statistik
Identifikatorer
URN: urn:nbn:se:umu:diva-247646DOI: 10.1145/3719027.3765031Scopus ID: 2-s2.0-105023841964ISBN: 9798400715259 (digital)OAI: oai:DiVA.org:umu-247646DiVA, id: diva2:2023308
Konferens
32nd ACM SIGSAC Conference on Computer and Communications Security, CCS 2025, Taipei, Taiwan, October 13-17, 2025.
Forskningsfinansiär
Wallenberg AI, Autonomous Systems and Software Program (WASP)2025-12-192025-12-192025-12-19Bibliografiskt granskad