Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Lisa Ventura shares her personal struggle with imposter syndrome and how it almost held her back from launching a cybersecurity association. Learn about her journey in overcoming self-doubt and raising awareness through an annual imposter syndrome day.

Lisa Ventura explains why small business owners and SMEs often have a false sense of security when it comes to cyber threats. She highlights the risks in supply chains and the importance of taking cybersecurity seriously, regardless of size.

Welcome to Razorwire, the podcast where I, Jame Rees, cover the cybersecurity topics that matter with expert guests from across the industry. We aim to help cybersecurity professionals enhance their skills, improve their work performance, and boost their overall quality of life in this demanding field.

Josh Neil explains why large language models (LLMs) can exacerbate the issue of false positives in threat detection. Discover why more AI isn't always the answer in reducing alert noise.

Richard Cassidy addresses the misconception that LLMs are a 'hive mind' capable of making autonomous decisions. Discover how LLMs actually work and why they're not the magic solution some believe them to be.

Josh Neil explains how LLMs predict word combinations based on probability. Learn how these models generate language and why the prompt you give them significantly influences the output.

Josh Neil explains the concept of deep learning and how it was designed to discover structure in unstructured data, such as images and text. Learn why this technology is key to advancements in cybersecurity. #DeepLearning #StructuredData #CyberSecurity.

Josh Neil; highlights the difficulty LLMs face in detecting rare, complex cybersecurity threats. Discover why LLMs struggle with unique threat patterns and how this impacts threat detection accuracy.

Learn about the risks of prompt engineering in threat detection. Josh Neal highlights how asking leading questions can cause LLMs to agree with incorrect assumptions, increasing the likelihood of false positives.