Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

The emergence of advanced large language models like Anthropic's Mythos represents an epochal shift in cybersecurity, fundamentally altering how zero-day vulnerabilities are surfaced and remediated. In this episode, host Richard Bejtlich sits down with Corelight Co-founder Greg Bell to analyze the security implications of this AI-driven bug explosion, highlighting recent AI-assisted vulnerability discoveries across infrastructure mainstays like FreeBSD and Firefox.

Modern enterprise solutions—ranging from cloud data and power platforms to agentic AI and API connections—require rigorous oversight. Every platform integration must be evaluated through the lenses of risk, data compliance, and privacy to ensure secure operations. Netskope provides the necessary visibility and control for all data paths, including APIs and cloud-based AI platforms, helping Embecta enforce the data compliance and privacy standards required when integrating disparate applications.

Organizations like Renesas face critical risks when utilizing AI, as these platforms often incorporate user-submitted data into their models. Significant security incidents have occurred where sensitive source code, firmware, and proprietary designs were inadvertently made public after being uploaded for testing. A major business risk involves the potential loss of intellectual property, which can directly impact an organization's primary revenue streams. Beyond data leakage, AI presents risks through "poisoning" and the fact that AI-generated output is frequently inaccurate.