To better understand the potential uses of large language models (LLMs) and their impact, a team of researchers at the Carnegie Mellon University Software Engineering Institute CERT Division conducted four in-depth case studies. The case studies span multiple domains and call for vastly different capabilities. In this podcast, Matthew Walsh, a senior data scientist in CERT, and Dominic Ross, Multi-Media Design Team lead, discuss their work in developing the four case studies as well as limitations and future uses of ChatGPT.
A Penetration Testing Findings Repository
Understanding Vulnerabilities in the Rust Programming Language
We Live in Software: Engineering Societal-Scale Systems
Secure by Design, Secure by Default
Key Steps to Integrate Secure by Design into Acquisition and Development
An Exploration of Enterprise Technical Debt
The Messy Middle of Large Language Models
An Infrastructure-Focused Framework for Adopting DevSecOps
Software Security in Rust
Improving Interoperability in Coordinated Vulnerability Disclosure with Vultron
Asking the Right Questions to Coordinate Security in the Supply Chain
Securing Open Source Software in the DoD
A Model-Based Tool for Designing Safety-Critical Systems
Managing Developer Velocity and System Security with DevSecOps
A Method for Assessing Cloud Adoption Risks
Software Architecture Patterns for Deployability
ML-Driven Decision Making in Realistic Cyber Exercises
A Roadmap for Creating and Using Virtual Prototyping Software
Software Architecture Patterns for Robustness
A Platform-Independent Model for DevSecOps
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