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While multiple recent publications on detecting Java Deserialization Vulnerabilities highlight an increasing relevance of the topic, until now no proper benchmark has been established to evaluate the individual approaches. Hence, it has become increasingly difficult to show improvements over previous tools and trade-offs that were made. In this work, we synthesize the main challenges in gadget chain detection. More specifically, this unveils the constraints program analysis faces in the context of gadget chain detection. From there, we develop Gleipner: the first synthetic, large-scale and systematic benchmark to validate the effectiveness of algorithms for detecting gadget chains in the Java programming language. We then benchmark seven previous publications in the field using Gleipner. As a result, it shows, that (1) our benchmark provides a transparent, qualitative, and sound measurement for the maturity of gadget chain detecting tools, (2) Gleipner alleviates severe benchmarking flaws which were previously common in the field and (3) state-of-the-art tools still struggle with most challenges in gadget chain detection.