Jose Rodriguez is a Data Scientist with 8 years of experience specializing at the intersection of threat hunting and data science within the InfoSec community. He leverages practical data engineering and visualization skills—pandas, Altair, Jupyter—not just to analyze MITRE ATT&CK datasets but to make security telemetry more usable through documentation automation. His open-source contributions to OSSEM and the ATTACK-Python-Client include scripts that convert markdown/Excel into YAML and notebooks that normalize and visualize STIX/TAXII data, highlighting a focus on reproducible, machine-readable security data dictionaries. Colleagues rely on him to translate complex security frameworks into actionable analytics and streamlined documentation that scale across teams.
Python Script to access ATT&CK content available in STIX via a public TAXII server
Role in this project:
Data Scientist
Contributions:9 commits, 6 PRs, 7 pushes in 3 years 3 months
Contributions summary:Jose primarily worked on a Jupyter Notebook to explore and analyze MITRE ATT&CK framework data sources using Python. Their contributions involved importing and utilizing libraries like pandas, altair, and attackcti to access, process, and visualize the data. They normalized JSON data, demonstrating data wrangling skills and used the ATT&CK client to get information from the MITRE ATT&CK framework. They also documented and expanded the functionality of the notebook.
Contributions:20 commits, 13 PRs, 13 pushes in 2 years 11 months
Contributions summary:Jose primarily focused on updating documentation, specifically a Jupyter Notebook. These updates involved modifying the existing content, including references, and adding new information related to correlating security telemetry. The contributions also included the creation of a markdown-to-YAML parser script and a script to convert Excel files to YAML, which suggests a focus on automating documentation and data dictionary generation. These changes aim to streamline the documentation process and potentially improve the usability of the OSSEM data dictionaries.
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