# Automated CAN Payload Reverse Engineering > Research Python and R scripts that automate reverse engineering of Controller Area Network (CAN) payloads recorded from passenger vehicles, implementing the pipeline from Brent Stone's AFIT dissertation. The Python pipeline pre-processes a CAN log into per-arbitration-ID data frames, pulls out public SAE J1979 diagnostic data, runs a lexical analysis that guesses individual signal time-series boundaries, then a semantic analysis that builds a correlation matrix and hierarchically clusters related signals, with plots and a dendrogram as output. A separate R script set applies the rEDM empirical dynamic modeling package to engine-RPM, brake-pressure and vehicle-speed time series to study causal relationships. - Type: Tool - Targets: Protocol - Category: Protocol analysis tools - Relationship: Foundation tool - Sources reviewed: 2026-10-20 - Added to the catalog: 2026-11-02 - Original resource: - Primary source: - Catalog page: - Record JSON: - Chinese version: [简体中文](https://awesomerea.org/zh/resources/can-reverse-engineering/index.md) ## Requirements & limits - Dissertation research code with no releases or tags; the reviewed commit dates to 2022-02-01. The README says the scripts were developed and tested on Python 3.6 and need NumPy, Pandas, scikit-learn and (for plotting) matplotlib listed in requirements.txt; the R scripts need R with the rEDM package. There is no packaging or install step, and the README says the scripts will not run immediately after cloning. - Two Python folders implement the same concept: Pipeline is the basic single-file version driven from Main.py, and Pipeline_multi-file is the more complete batch version that the README says contains bug fixes not back-ported to Pipeline. Input is a CAN capture in the bundled loggerProgram0.log delta-time/ID/DLC/hex format; an April 2020 addition also reads the can-utils log format via a -c/--can-utils argument, and other formats require editing PreProcessor.py. - The user supplies their own CAN capture. The repository bundles the author's own example data: the loggerProgram0.log vehicle capture, example pipeline output, an OBD2 PID table, and R-folder CSV time series of engine RPM, brake pressure and vehicle speed for different driving conditions, plus the author's dissertation PDF. The results are signal-boundary and clustering estimates that need analyst validation, not confirmed signal definitions. - The repository includes a GPL-3.0 LICENSE file, while the README states the code is a work of the U.S. Government not subject to copyright protection in the United States, cleared for public release (case 88ABW-2019-0910). The scripts read passive logs and perform analysis only; no device interaction or frame transmission is described. ## Primary sources 1. 2. 3. 4. 5. 6. ## More in Protocols - [Deluder](https://awesomerea.org/resources/deluder/index.md) · Tool - [PiCCANTE](https://awesomerea.org/resources/piccante/index.md) · Tool - [VanBus](https://awesomerea.org/resources/vanbus/index.md) · Tool - [Apple Continuity Reverse Engineering Toolkit](https://awesomerea.org/resources/apple-continuity-tools/index.md) · Tool - [Cabana (standalone openpilot-cabana)](https://awesomerea.org/resources/openpilot-cabana/index.md) · Tool - [eCapture](https://awesomerea.org/resources/ecapture/index.md) · Tool ## About this entry The description was reviewed against primary sources. Original editorial content: MIT. Linked projects, papers and assets retain their own rights and licenses.