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Emergency patching feels like progress until you realize it is an endless race you cannot win, especially in critical infrastructure. We talk with Benny Czarny Founder, Chief Executive Officer (CEO) and Chairman of the Board at OPSWAT about what it really takes to protect operational technology (OT) environments where downtime is unacceptable and “mostly secure” is not an option. From water systems to power and manufacturing, we unpack why complex IT/OT networks, specialized devices, and compliance demands require more deterministic cybersecurity than the average enterprise playbook. 

We dig into what some are calling “Black October” and why the volume of vulnerabilities keeps climbing, with AI making it easier for both researchers and attackers to find and exploit weaknesses. Then we get concrete: what should never be exposed to the internet, how air gapping buys time, and why a data diode can reduce risk compared to relying on firewall rules and perfect patch timing. If you are responsible for critical systems, this is a practical conversation about shrinking attack paths, not just reacting faster. 

A big focus is file-based intrusion risk and the prevention-first idea behind Deep CDR (Content Disarm and Reconstruction). Instead of trying to detect the next clever payload hidden in a document, image, or USB transfer, we explore the “trust no file” model that regenerates content into a known-safe version. We also talk training, awareness, and why cybersecurity education works better when it is accessible and actually interesting. Subscribe, share this with someone who owns an OT environment, leave a review, and tell us what security assumption you would change first.
Learn more about Microsoft's ISOC announcement: https://fandf.co/4iQ9b5n
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AI is getting frighteningly good at finding software vulnerabilities and stitching them into workable exploits, and security teams were already underwater long before the latest wave of zero-days. That reality raises an uncomfortable question: if offense moves at machine speed, what does credible defense look like?

We sit down with Dr. Neha Rungta, Director of Applied Science, Amazon Web Services (AWS) unpack AWS Continuum for Code Vulnerabilities, now generally available, and the practical mechanics behind “autonomous security.” We walk through the full loop from discovery to validation to prioritization to remediation, including why proving exploitability in your real cloud environment matters so much for reducing false positives. When you can combine code signals with AWS context like network reachability, permissions, encryption, and workload placement, the output stops being a giant list and becomes an actionable plan.

We also dig into the CyberGym benchmark and what an 89% success rate actually represents: generating a crashing input, producing a patch, preventing regressions by running tests, and confirming the fix resolves the historical vulnerability, not just one symptom. And we get candid about what keeps AI-generated security fixes safe: “boring” but essential engineering discipline, sandboxing, and rigorous test suites.

If you care about secure software development, DevSecOps, vulnerability management, and AI security tooling that engineers will actually use, this conversation delivers real details. Subscribe, share the episode with your security or platform team, and leave a review with the hardest part of vulnerability triage in your org.
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A single click can be the start of a breach, but the request that happens right before that click loads a page is even more revealing. We sit down with Ken Carnesi, Chief Executive Officer & Co-Founder, DNSFilter to unpack why DNS security is such a powerful point of control in modern cybersecurity and why so many attacks touch the domain name system somewhere along the way. If you’ve ever heard the saying “it’s always DNS,” you’ll understand it at a deeper level by the end of this conversation. 

We walk through how DNS filtering works in real life, from blocking obvious malicious domains to catching brand-new phishing links before traditional tools have time to catch up. Ken shares how machine learning can categorize and re-categorize domains fast, why “good yesterday” does not mean “safe today,” and what that means for enterprise security teams trying to protect employees, guest Wi‑Fi, and hard-to-manage devices like IoT and specialized equipment. We also get honest about limits: DNS is not the only layer you need, and defense in depth still matters. 

Then we go straight into the AI shift. Ken explains DNSFilter’s Luminate launch, including Agent Shield, built for a world where AI agents generate their own traffic and may soon outnumber humans online. We also talk about the attacker side, why the pace of “Black October” feels different, and a practical takeaway for CISOs: start using the same AI-powered tools against your own environment more frequently so you can react in days and hours, not weeks. 

If you care about DNS security, phishing protection, threat intelligence, and what AI means for the next era of network security, hit subscribe, share this with a teammate, and leave a review with your biggest question about securing AI agents.
Learn more about Microsoft's ISOC announcement: https://fandf.co/4iQ9b5n
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AI agents can shrink security work from days to minutes, but only if you can trust what you’re running. That’s why we sat down with Justin Buchanan, practice leader for Tenable’s Agentic AI Accelerator, to unpack a problem we don’t talk about enough: security teams are building powerful agentic AI workflows in private silos, even though cybersecurity has always thrived on sharing.

We dig into the Cyber Agents Exchange, an open source repository built for cybersecurity professionals to share AI agents, skill files, MCP servers, and playbooks across the tools you actually use. Justin walks us through concrete examples that hit daily SOC pain, like an agent that answers the brutally practical question “what do I need to fix today?” by combining vulnerability context with sources like MITRE and CISA KEV. We also cover hunt automation that ties together SIEM and EDR data so analysts spend less time reconciling timestamps and more time making decisions.

Then we get serious about AI security risk and governance. Justin explains how contributions are baseline reviewed to catch credential exposure, undocumented outbound calls, and unsafe behavior, plus what it takes to earn a higher-confidence “vetted” status with deeper inspection and sandbox testing. We also talk about Swarm community build events, why more non-traditional builders are shipping real cybersecurity automation, and what CISOs need to scale agentic AI safely inside the enterprise.

If you’re experimenting with AI agents for cybersecurity, threat hunting automation, SOC efficiency, or secure open source adoption, this conversation gives you a practical framework. Subscribe, share this with your team, and leave a review with the AI agent you most want to build next.
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AI didn’t make application security “new” so much as it made it faster. When exploits can be drafted, refined, and scaled with AI assistance, the window to detect and fix vulnerabilities gets brutally short. That urgency is why we sat down with Grant Ongers — OWASP Foundation, a longtime application security leader and OWASP project lead, to talk about what’s changing, what isn’t, and what teams should do right now.

We start with how OWASP works in the real world: open source security projects, global AppSec conferences, and local chapters that help grow the next generation of AppSec talent. From there, we dig into the two big AI shifts Grant sees everywhere: accelerated exploitation and a lowered barrier to entry for attackers. If the “bad guys” can move faster, we need to move faster too, and that means pairing solid fundamentals with smarter, AI-assisted defense.

Threat modeling is the practical backbone of that defense. Grant breaks it down into an approachable four-question framework and explains how AI can help teams explore “what can go wrong” without outsourcing responsibility. We also talk about OWASP Cornucopia, a card-based, gamified approach that helps developers surface security abuse cases and connect them to concrete guidance like OWASP ASVS. Finally, we get blunt about agentic AI: treat agents like employees, scope access tightly, watch for toxic combinations of permissions, and keep a human accountable for anything that ships.

If this conversation helps you, subscribe, share it with a builder on your team, and leave a review so more developers can find it.
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