Software Engineering Institute (SEI) Podcast Series

Latest Episodes:

Temporal Memory Safety in C and C++: An AI-Enhanced Pointer Ownership Model Feb 09, 2026

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In October 2025, CyberPress reported a critical security vulnerability in the Redis Server, an open-source in-memory database that allowed authenticated attackers to achieve remote code execution through a use-after-free flaw in the Lua scripting engine. In 2024, another prominent temporal memory safety flaw was found in the Netfilter subsystem in the Linux kernel: CVE-2024-1086. Bugs related to temporal memory safety, such as use-after-free and double-free vulnerabilities, are challenging issues in C and C++ code. In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Lori Flynn, a senior software security researcher in the SEI's CERT Division, and David Svoboda, a senior software engineer, also in CERT, sit down with Tim Chick, technical manager of CERT's Applied Systems Group, to discuss recent updates to the Pointer Ownership Model for C, a modeling framework designed to improve the ability of developers to statically analyze C programs for errors involving temporal memory.

AI for the Warfighter: Acquisition Challenges and Guidance Jan 29, 2026

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On November 7, the Department of War released an acquisition transformation strategy that seeks to remove bureaucratic hurdles and streamline acquisition processes to enable even more rapid adoption of technologies, including artificial intelligence. Getting AI into the hands of warfighters requires disciplined AI Engineering. In this podcast from the Carnegie Mellon University Software Engineering Institute, Carol Smith, lead of human-centered research in the SEI's AI Division, and Brigid O'Hearn, the SEI's lead of software modernization policy for the Department of War, sit down with Eileen Wrubel, the SEI's technical director of Transforming Software Acquisition Policy and Practice, to discuss AI Engineering challenges and guidance in the defense acquisition space.

Visibility Through the Clouds with Network Flow Logs Jan 15, 2026

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Organizations, including the U.S. military, are increasingly adopting cloud deployments for their flexibility and cost savings. The shared security model utilized by cloud service providers removes some of the adopting organization's responsibility for system administration and security. But it leaves them on the hook for monitoring hosted applications and resources. Cloud flow logs are a valuable source of data for supporting these security responsibilities and attaining situational awareness. The SEI has a long history of supporting flow log collection and analysis, including tools for collection in Azure and AWS. In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), two leading researchers in this area, principal researcher Tim Shimeall and security data analyst Ikem Okafo, both with the SEI's CERT Division, sit down with Dan Ruef, technical manager of the CERT Division's Network Situational Awareness Group, to discuss how to enhance security with cloud flow analysis as well as available tools and resources.

Orchestrating the Chaos: Protecting Wireless Networks from Cyber Attacks Dec 02, 2025

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From early 2022 through late 2024, a group of threat actors publicly known as APT28 exploited known vulnerabilities, such as CVE-2022-38028, to remotely and wirelessly access sensitive information from a targeted company network. This attack did not require any hardware to be placed in the vicinity of the targeted company's network as the attackers were able to execute remotely from thousands of miles away. With the ubiquity of Wi-Fi, cellular networks, and Internet of Things (IoT) devices, the attack surface of communications-related vulnerabilities that can compromise data is extremely large and constantly expanding.

In the latest podcast from the Carnegie Mellon University Software Engineering Institute (SEI) Joseph McIlvenny, a senior research scientist, and Michael Winter, vulnerability analysis technical manager, both with the SEI's CERT Division, discuss common radio frequency (RF) attacks and investigate how software and cybersecurity play key roles in preventing and mitigating these exploitations.

From Data to Performance: Understanding and Improving Your AI Model Nov 10, 2025

Show notes

Modern data analytic methods and tools—including artificial intelligence (AI) and machine learning (ML) classifiers—are revolutionizing prediction capabilities and automation through their capacity to analyze and classify data. To produce such results, these methods depend on correlations. However, an overreliance on correlations can lead to prediction bias and reduced confidence in AI outputs.

Drift in data and concept, evolving edge cases, and emerging phenomena can undermine the correlations that AI classifiers rely on. As the U.S. government increases its use of AI classifiers and predictors, these issues multiply (or use increase again). Subsequently, users may grow to distrust results. To address inaccurate erroneous correlations and predictions, we need new methods for ongoing testing and evaluation of AI and ML accuracy. In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Nicholas Testa, a senior data scientist in the SEI's Software Solutions Division (SSD), and Crisanne Nolan, and Agile transformation engineer, also in SSD, sit down with Linda Parker Gates, Principal Investigator for this research and initiative lead for Software Acquisition Pathways at the SEI, to discuss the AI Robustness (AIR) tool, which allows users to gauge AI and ML classifier performance with data-based confidence.

What Could Possibly Go Wrong? Safety Analysis for AI Systems Oct 31, 2025

Show notes

How can you ever know whether an LLM is safe to use? Even self-hosted LLM systems are vulnerable to adversarial prompts left on the internet and waiting to be found by system search engines. These attacks and others exploit the complexity of even seemingly secure AI systems.

In our latest podcast from the Carnegie Mellon University Software Engineering Institute (SEI), David Schulker and Matthew Walsh, both senior data scientists in the SEI's CERT Division, sit down with Thomas Scanlon, lead of the CERT Data Science Technical Program, to discuss their work on System Theoretic Process Analysis, or STPA, a hazard-analysis technique uniquely suitable for dealing with AI complexity when assuring AI systems.

Getting Your Software Supply Chain In Tune with SBOM Harmonization Oct 23, 2025

Show notes

Software bills of materials or SBOMs are critical to software security and supply chain risk management. Ideally, regardless of the SBOM tool, the output should be consistent for a given piece of software. But that is not always the case. The divergence of results can undermine confidence in software quality and security. In our latest podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Jessie Jamieson, a senior cyber risk engineer in the SEI's CERT Division, sits down with Matt technical director of Risk and Resilience in CERT, to talk about how to achieve more accuracy in SBOMs and present and future SEI research on this front.

API Security: An Emerging Concern in Zero Trust Implementations Oct 08, 2025

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Application programing interfaces, more commonly known as APIs, are the engines behind the majority of internet traffic. The pervasive and public nature of APIs have increased the attack surface of the systems and applications they are used in. In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), McKinley Sconiers-Hasan, a solutions engineer in the SEI's CERT Division, sits down with Tim Morrow, Situational Awareness Technical Manager, also with the CERT Division, to discuss emerging API security issues and the application of zero-trust architecture in securing those systems and applications.

Delivering Next-Generation AI Capabilities Sep 29, 2025

Show notes

Artificial intelligence (AI) is a transformational technology, but it has limitations in challenging operational settings. Researchers in the AI Division of the Carnegie Mellon University Software Engineering Institute (SEI) work to deliver reliable and secure AI capabilities to warfighters in mission-critical environments. In our latest podcast, Matt Gaston, director of the SEI's AI Division, sits down with Matt Butkovic, technical director of the SEI CERT Division's Cyber Risk and Resilience program, to discuss the SEI's ongoing and future work in AI, including test and evaluation, the importance of gaining hands-on experience with AI systems, and why government needs to continue partnering with industry to spur innovation in national defense.

The Benefits of Rust Adoption for Mission-and-Safety-Critical Systems Sep 16, 2025

Show notes

A recent Google survey found that many developers felt comfortable using the Rust programming language in two months or less. Yet barriers to Rust adoption remain, particularly in safety-critical systems, where features such as memory and processing power are in short supply and compliance with regulations is mandatory. In our latest podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Vaughn Coates, an engineer in the SEI's Software Solutions Division, sits down with Joe Yankel, initiative Lead of the DevSecOps Innovations team at the SEI, to discuss the barriers and benefits of Rust adoption.

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