Survey the existing method of lateral movement detection and focus on the methods based on network traffic analysis and the technique of pivoting. Review scientific literature, compare the proposed approaches and their implementations, and discuss their technology readiness level. Compare the signature-based detection methods and machine learning-based methods separately and then compare these two groups. Conduct experimental evaluation of publicly available implementations using artificial datasets and also live network traffic, if possible. When analyzing the experiment results, focus on the overall number of detected events and false positive rates and discuss the usability of the compared methods with respect to the information overload and alert fatigue issues faced by cybersecurity teams. Finally, design and implement modular and extensible pivoting detection pipeline. The pipeline will deconstruct the pivoting detection process into partial steps and allow for using modules implementing different approaches to the particular step. For example, it will enable the user to choose or configure detection methods. Illustrate the use of the pipeline for experiments over real-world network traffic using at least two different pipeline settings.