This episode is sponsored by Acceleration Economy’s “Cloud Wars Top 10 Course,” which explains how Bob Evans builds and updates the Cloud Wars Top 10 ranking, as well as how C-suite executives use the list to inform strategic cloud purchase decisions. The course is available today.
00:44 — One of the key considerations in the report is the rise of Large Language Models (LLMs) and the ability of AI platforms powered by LLMs to classify malware risk. The report concludes that current LLMs can’t reliably assist in malware detection at scale; risk was accurately classified in just 5% of all cases.
Which companies are the most important vendors in cybersecurity? Check out
the Acceleration Economy Cybersecurity
Top 10 Shortlist.
01:15 — 45% of applications make no calls to security-sensitive APIs in their code base but, when dependencies are included, this drops to 5%. This demonstrates how organizations underestimate risk when they fail to analyze the use of APIs through open-source dependencies.
01:36 — Widespread implementation of ChatGPT and lack of historical data is a recipe for potential attacks. Endor Labs notes the “considerable harm” that can occur if the risks such new software introduces aren’t closely monitored. They can introduce malware and other risks in the software supply chain.