AI & Cybersecurity

In this episode, James Walker, Gareth Williams, and Dai Kennett discuss the intersection of AI and cybersecurity, exploring the challenges and opportunities presented by AI integration in enterprises. They delve into the importance of context management in AI development, the security concerns associated with AI in coding, and the role of AI in vulnerability detection. The conversation also touches on the overwhelming amount of data in cybersecurity, the evolution of AI agents, and the future landscape of cybersecurity.

Episode Hosts

James Walker (PhD)

Entrepreneur & academic who loves creating innovative solutions to hard challenges.

Dai Kennett

Dai is Co-Founder of a Cyber Security company, bringing extensive hands-on experience in offensive cybersecurity and AI/ML development and security research.

Episode Description

This podcast episode of Autonify features hosts James Walker and Gareth Williams interviewing Dai Kennett, founder of a stealth-mode cybersecurity startup focused on CTEM (Continuous Threat Exposure Management) and vulnerability management. Dai's company aims to build a "central brain" for cybersecurity systems in large organizations. The conversation explores why the world needs more AI startups beyond simple ChatGPT wrappers, emphasizing that while implementing AI models in production is challenging, there's significant value in distilling expertise into specialized models and creating easier integrations for enterprises.

The discussion delves into the security implications of AI-powered development tools like Cursor's agent mode. Dai, drawing from his penetration testing background, highlights emerging attack vectors including AI models suggesting vulnerable libraries, compromised API keys, and the potential for training data poisoning. The conversation covers how AI could enable sophisticated attacks through agent swarms targeting corporate systems, while also noting positive developments like Claude's new security features that can detect and report unethical behavior. The hosts discuss the challenge enterprises face in making their vast amounts of data accessible and structured for AI systems to provide context-aware solutions.

Looking toward the future, the panelists predict a shift toward more autonomous agent-to-agent communication, with Microsoft's vision of an "agentic internet" serving as an example. They see data management and quality as critical bottlenecks that will determine successful AI adoption in enterprises. The conversation concludes with Dai's perspective on the cybersecurity landscape, warning that we're entering a "Wild West" period where defenders must catch up to attackers who are early adopters of AI technology. He emphasizes the need for AI-powered defense systems that can process the "oceans of security data" to provide early warning systems against increasingly sophisticated AI-enabled attacks.