SEI Podcasts

3 Key Elements for Designing Secure Systems

Oct 2, 2024

To make secure software by design a reality, engineers must intentionally build security throughout the software development lifecycle. In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Timothy A. Chick, technical manager of the Applied Systems Group in the SEI’s CERT...

Using Role-Playing Scenarios to Identify Bias in LLMs

Sep 16, 2024

Harmful biases in large language models (LLMs) make AI less trustworthy and secure. Auditing for biases can help identify potential solutions and develop better guardrails to make AI safer. In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Katie Robinson and...

Best Practices and Lessons Learned in Standing Up an AISIRT

Sep 9, 2024

In the wake of widespread adoption of artificial intelligence (AI) in critical infrastructure, education, government, and national security entities, adversaries are working to disrupt these systems and attack AI-enabled assets. With nearly four decades in vulnerability management, the Carnegie Mellon...

3 API Security Risks (and How to Protect Against Them)

Aug 22, 2024

The exposed and public nature of application programming interfaces (APIs) come with risks including the increased network attack surface. Zero trust principles are helpful for mitigating these risks and making APIs more secure. In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI),

Evaluating Large Language Models for Cybersecurity Tasks: Challenges and Best Practices

Jul 25, 2024

How can we effectively use large language models (LLMs) for cybersecurity tasks? In this Carnegie Mellon University Software Engineering Institute podcast, Jeff Gennari and Sam Perl discuss applications for LLMs in cybersecurity, potential challenges, and recommendations for evaluating...