AI Security Brief

How close are we to an autonomous SOC?

AI-enabled attacks are on the rise, your analysts are drowning in alerts, and vendors are positioning an autonomous SOC as the solution. But what can AI agents actually do today? How will analyst roles evolve? And how much autonomy can you safely give? Cybersecurity researcher Jon Oltsik joins Johnny and Dustin to separate AI automation from AI autonomy. They explore what it takes to bring AI agents into the SOC safely, from testing agents in shadow mode to establishing clear guardrails and human oversight, and why trust in an agent has to be earned through proven performance.

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How do you plan for AI system failure?

Your AI initiative gets the green light. But now all the parameters and guardrails you built into your plan need to be executed. Who owns AI once it goes live? Who’s watching as AI use expands? And if the AI workflow fails, can anyone still run the process it replaced? In this episode, Maria Haight, Global Information Security Officer at Joyson Safety Systems, joins Dustin Childs to unpack the operational realities of AI security. She advocates for preserving human know-how, assigning business ownership, and backing up critical data to keep the business running should an AI system fail or dare we say it, go rogue.

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Is trust holding back automated remediation?

The “AI trust paradox” in cybersecurity goes like this: organizations invest in AI automation, then hold back from fully implementing it. Yet as attackers continue to use AI to move faster, defenders need to leverage AI to fix things as fast as it finds them. In this episode, Tyler Shields, Chief Marketing Officer at Allstacks and a cybersecurity industry analyst with more than 25 years advising security vendors and teams, shares the steps needed to build trust in autonomous remediation without sacrificing human judgment and control.

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Can you trust AI with critical infrastructure?

In traditional IT, isolating a compromised endpoint can stop an attack. In operational technology (OT) environments, that same action could disrupt control of a pipeline, cause a rupture, or trigger environmental damage. That’s why adopting AI in critical infrastructure requires a fundamentally different security approach. Drawing on more than 25 years of experience across energy, pipelines, aerospace, and defense, Jason Cradit, CTO and CISO at Everline, explains how security leaders can move beyond blanket restrictions and establish practical AI governance and guardrails.

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Is a closed or an open AI model more trustworthy?

There's no silver bullet when it comes to AI security strategy, and treating one model, tool, or vendor as the answer can limit an organization’s ability to adapt. Morgan Adamski, who leads PwC’s Cyber, Data & Technology Risk practice, joins us to tackle two pressing questions: How should organizations choose between closed frontier models and open-weight alternatives? And how can they build a multi-model architecture flexible enough to keep pace as AI technology rapidly evolves? Drawing on her work with boards, CISOs, and security teams, Morgan cuts through the “paralysis by analysis” surrounding these questions and offers security leaders a practical path forward.

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