Notebooks, Datasets, & Clouds for Offensive Automation & Threat Analysis
Ryan Ekins demonstrates leveraging cloud-hosted Jupyter notebooks, large datasets, and serverless pipelines to automate offensive reconnaissance and analysis.
Summary
The Intersection of Data Science and Offensive Security
Modern security operations generate massive datasets during reconnaissance and fuzzing, requiring scalable data processing pipelines.
Leveraging Jupyter Notebooks for Offensive Workflows
Ryan Ekins illustrates using cloud-hosted Jupyter notebooks and Python data science libraries (pandas, matplotlib) to analyze network attack surfaces.
Building Scalable Serverless Automation Pipelines
The speaker demonstrates deploying cloud functions and containers to orchestrate distributed port scans, asset discovery, and credential validation.
Operationalizing Big Data for Red and Purple Teams
The presentation showcases how data-driven automation streamlines attack planning and enables repeatable security telemetry analysis.
Related talks
Red Team Village·53 min
Michael Wylie
Michael Wylie details automated reconnaissance techniques to discover unauthenticated AWS S3 buckets, Azure Blob containers, and GCP storage leaks.
The Linux Foundation·49 min
Relational Observability for Cloud-Native Security and Data Science- Frederico Araujo & Teryl Taylor
Details relational Observability for Cloud-Native Security and Data Science- Frederico Araujo & Teryl Taylor and evaluates key implications for security practitioners.
Recon Conference·10 min
Engineers explore architecture and security mechanisms for Recon 2018 Montreal - Cloudy With a Chance of Malware.


