We present Rusty-Cracker, a high-performance Rust library that implements a parallel version of the Cracker algorithm for efficiently identifying connected components in large-scale graphs. Designed to address the growing demands of graph analytics in fields such as social network analysis, bioinformatics, and infrastructure modeling, Rusty-Cracker leverages Rust's concurrency and memory safety features to ensure both speed and reliability. The adapted Cracker algorithm capitalizes on modern multi-core architectures through parallel processing, effectively minimizing synchronization overhead and optimizing workload distribution. This design significantly reduces computational time while maintaining accuracy. We present the implementation details and evaluate its performance on a real-world dataset of undirected graphs.