The Cyber Business Podcast

Welcome to The Cyber Business Podcast where we feature top founders and entrepreneurs and share their inspiring stories.

The Cyber Business Podcast is a technology podcast hosted by Matthew Connor, with 238 episodes on record and a Required Pod Score of 80.

Matthew Connor hosts The Cyber Business Podcast, a technology show with 238 episodes published.

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  Episode #242

  Why You Can't Commit to One AI Provider Anymore with Matthew Sanders - Ep 242

  Oct 2, 202645 min

  Guest Introduction Matthew Sanders is the CISO at Slingshot Aerospace , a company that combines a global sensor network with AI and advanced analytics to help government and commercial customers understand what's happening in space and operate safely. Because of the nature of Slingshot's work, Matthew's biggest concern isn't financially motivated criminals, it's patient nation-state actors willing to linger inside a system undetected for extended periods. He joins the show to talk through prompt injection and model poisoning risk, a striking recent Anthropic threat intelligence report on real world misuse of its own models, and why depending on a single AI provider has become a genuine supply chain risk for organizations in the defense industrial base. Here's a Glimpse of What You'll Learn Why Matthew says nation-state actors, not financially motivated criminals, are his top concern at Slingshot How a recent Anthropic security report revealed threat actors building entire phishing campaigns with minimal prompting Why Matthew believes patching no longer means what it used to against AI-discovered zero days How Matthew uses Claude daily as a second opinion to catch his own team's missed security settings Why defense industrial base policy shifts are forcing security teams away from single-provider AI lock-in How Matthew thinks AI assisted testing could finally solve the oldest blocker in patch management Why Matthew believes the tide in the AI arms race may finally be shifting toward defenders In This Episode Matthew opens by laying out just how much AI has reshaped the security conversation at a company built entirely around AI-driven space intelligence. He walks through the layered risk: prompt injection and model poisoning inside Slingshot's own products, attackers using AI to iterate on attacks faster than ever, and a governance challenge every security leader now faces, trying to understand what tools employees are actually using without slowing the business down. He references a security report Anthropic published just before the recording, detailing how threat actors, including a Russian group targeting Ukraine-based companies, used Claude with only basic instructions to build complete phishing campaigns, compromise hotel Wi-Fi, and create malware targeting iOS, all capability that would have required far more sophistication just a year earlier. He also points back to the MGM breach as a reminder that attackers don't need to target end users at all, since in that case it was a sophisticated IT team itself that got socially engineered. The conversation turns to where Matthew sees real opportunity rather than just risk. He's candid that watching Darktrace's Secure AI product gives him a genuine glimpse of the future, tools that let security professionals finally see what their own organization is doing with AI in real time, the same visibility advantage attackers have enjoyed for longer than defenders have. He argues the fundamentals, zero trust, least privilege, patching, matter more than ever precisely because AI defense tools don't replace them, and describes using Claude personally as a daily second opinion, feeding in his own SSP and compliance documentation to check whether his team is actually doing what they claim to be doing, catching missed settings in minutes rather than letting them slip through unnoticed. He also sees a major unsolved opportunity in AI-assisted testing, arguing the oldest blocker in patch management, the fear that an update will quietly break something else, could finally be addressed if AI could validate changes before they ship rather than after. The back half of the episode gets into the operational realities of running security in the defense industrial base during a moment of real policy upheaval. Matthew describes watching organizations get caught flat-footed when a model provider gets restricted for supply chain reasons overnight, forcing a scramble to alternative tools like Cursor or Codex, and argues this volatility means security leaders can no longer commit to a single AI provider the way they once committed to a single cloud vendor. He connects this to the ongoing pause on CMMC Level 2 requirements and the broader shift toward FedRamp's newer, more automation-driven approach, predicting that continuous AI monitoring will eventually replace much of the paperwork-heavy compliance process entirely. He closes on what he calls a genuinely exciting use case: feeding a full SSP into Claude to get instant gap analysis and self-auditing that used to take a human auditor a full week, compressed down to hours. Sponsor for this episode This episode is brought to you by Cyberlynx CyberLynx is a Bethesda managed IT and cybersecurity company. Local techs you know, not a call center. Month-to-month. 24/7 intrusion detection. We help growing companies with managed IT, help desk, backup and recovery, and a fractional CIO. Talk to us at https://cyberlynx.com/contact , info@cyberlynx.com , or 301-798-9170.

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  Episode #241

  Your Internal Network Is No Longer Trusted with Michael Foster - Ep 241

  Sep 30, 202643 min

  Guest Introduction Michael Foster is the CISO for the Wisconsin Department of Revenue , an agency he describes as functioning much like the IRS for the state, but with a scope that extends well beyond taxes into the Wisconsin State Lottery and three separate police forces covering everything from lottery fraud to alcohol and tobacco enforcement. His purview covers information security alongside portions of physical security, managing what stays inside the agency and what limited access outside entities are allowed. He joins the show to talk candidly about zero trust architecture, why he's skeptical of pure fight-fire-with-fire thinking, why security has to be sold internally as a business enabler rather than a cost center, and a genuinely unsettling real world story about how a single social media post led directly to a home invasion. Here's a Glimpse of What You'll Learn Why Michael says attackers no longer need a skilled hacker, just a purchased tool set to run on autopilot How Michael's least access philosophy extends zero trust to internal networks, not just external threats Why Michael is cautious about a pure fight-fire-with-fire approach to AI powered attacks How Michael reframes security spending as a business enabler instead of a cost center to get buy-in Why Michael still runs security awareness training even if workplace tools eventually make it obsolete Michael's explanation for why AI hallucinations often come from an organization's own bad data, not the model itself The real story from Michael's own community about a funeral post on social media leading to a home invasion In This Episode Michael opens by describing the unusual breadth of his role, protecting an agency that handles business taxes, the state lottery, and three distinct law enforcement divisions, all of which face constant daily attacks. He's direct that the nature of those attacks has changed fundamentally: attackers no longer need to be skilled, since AI agents can now be set up once and left running indefinitely to probe for openings, discovering the kind of zero day exploits that used to require deep technical expertise. When asked whether fighting AI with AI is simply the obvious answer, Michael pushes back with more nuance than that framing usually gets, warning that an arms race mentality can leave everyone burned, and that the real fix is architectural. He describes a least access philosophy that extends zero trust internally, treating even an organization's own network as untrusted, requiring every user and every AI agent employees build to be segmented down to only the specific applications and data they actually need, monitored the same way a service account would be. The conversation turns to the practical challenge of getting organizations to actually fund this kind of security, and Michael is clear that the winning argument isn't fear, it's framing security spending as a business enabler rather than a cost center, forcing leadership to weigh what could be lost in time, money, and trust against the investment required to prevent it. He's candid that responsibility for security can no longer sit only with IT, and that everyone in an organization has to own some piece of it. On the question of whether AI will eventually make user security awareness training obsolete entirely, Michael offers a genuinely distinct perspective from the more optimistic take Matthew proposes: even if workplace tools someday catch everything automatically, employees still won't have those same protections at home, and Michael continues training specifically to close that gap, since an employee who gets hit personally often ends up missing work to recover from it. The back half of the episode covers two threads that stick with the listener. First, Michael explains that many of the AI hallucinations organizations blame on the model are actually a symptom of poor internal data, meaning the fix is rewriting and cleaning up an organization's own source material before feeding it into any system, not distrusting the AI itself. Second, he shares a story from his own small community of roughly 4,000 people: after a local fire captain passed away, someone used the publicly posted funeral details to determine exactly when his house would be empty and broke in, only to be caught waiting by police, the intruder turning out to be a deputy sheriff. Michael uses the story to make a simple, memorable point about privacy: any piece of information posted publicly will eventually be used by someone, for something, and understanding that risk is now as much a part of the job as any technical control. Sponsor for this episode This episode is brought to you by Cyberlynx CyberLynx is a Bethesda managed IT and cybersecurity company. Local techs you know, not a call center. Month-to-month. 24/7 intrusion detection. We help growing companies with managed IT, help desk, backup and recovery, and a fractional CIO. Talk to us at https://cyberlynx.com/contact , info@cyberlynx.com , or 301-798-9170.

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  Episode #240

  Shared Governance in the Age of AI: Keeping the Institution Safe with Bill Guerrero - Ep 240

  Sep 27, 20261h 4m

  Guest Introduction Bill Guerrero is the VP of IT at Sacred Heart University , a private, faith-based, residential institution in Fairfield, Connecticut with roughly 10,000 students, 50 buildings, and nearly 2,000 cameras across campus. A proud alum who earned his master's there in 1999, Bill brings an unusual dual background to the role, having started his career at Gartner before spending years as a CFO, a financial lens he now applies directly to how the university budgets for AI. He joins the show during the first week of a new semester to talk through a live third-party security incident his team resolved in real time, why token and credit costs deserve the same budget scrutiny as any other line item, and why he believes the new professional standard is AI-assisted work refined by a human, not work produced by a human alone. Here's a Glimpse of What You'll Learn How Bill's team resolved a third-party zero-day breach affecting a campus vendor in just 24 hours Why Bill treats tokens and credits as a budget item universities can't afford to leave unaccounted for How Bill uses Claude with read-only access to run low-cost internal pen tests against the university's own framework Why Bill believes the new professional standard is AI-assisted work with a human review layer on top How Sacred Heart's shared governance model keeps AI adoption fast without letting any department run rogue Why Bill still uses AI for the small, personal tasks in his life outside the office, including coaching baseball How a real, current incident at a major learning management system provider shaped Bill's own continuity planning In This Episode Bill opens during the exact week cybersecurity pressure peaks for any university, the first week of a new semester, when thousands of students and their devices hit the network at once across a campus with door access systems, high end classroom technology, and nearly 2,000 cameras. He describes a proactive approach built around education before problems start, emailing students, faculty, and staff ahead of time with what to expect and what scams to watch for, while his cybersecurity team, led by his own CISO, works to keep pace with a threat landscape he compares to a constant game of ping pong against attackers who are also upgrading every day. He's candid that Sacred Heart isn't trying to be a bleeding edge leader, running as a Copilot enterprise shop for the past three years, but that shared governance lets academic leaders, faculty, and cybersecurity students get meaningful access without compromising the institution's data. The conversation turns sharply concrete when Bill describes a live incident from the exact weekend of the interview: a third-party vendor supporting the university's mobile credential printing system was hit by a zero-day exploit. Because of layered security defenses including CrowdStrike, Bill's team caught and remedied the breach within 24 hours, and in a notable twist, it was Sacred Heart's own team that first alerted the vendor to the intrusion. He connects this to a broader shift he's watched happen in real time, referencing a recent incident at a major learning management system provider that affected 900 universities, one Sacred Heart avoided, as a reminder that continuity plans written months ago need to be revisited constantly rather than treated as a one-time compliance exercise. The back half of the episode gets into how Bill actually manages AI adoption without letting cost or fear derail it. Drawing on his background as a recovering CFO, he explains why tokens and credits function like a printing budget that can quietly run out, an unbudgeted surprise if leadership isn't paying attention, and why total cost of ownership needs to include this line item explicitly. He describes using Claude with carefully scoped, read-only access to walk through the university's own firewall and network settings, comparing it against Sacred Heart's existing framework to run what amounts to a no-cost internal pen test rather than paying six figures for an external one. He closes on a personal note entirely outside of IT, describing how he used AI to rebuild a baseball practice schedule for a coaching role he's returning to after years away, tweaking the output himself rather than accepting it wholesale, a small example of the exact philosophy he argues the whole university should adopt: let AI produce the polished first draft, then apply the human judgment that makes it genuinely yours. SPONSOR FOR THIS EPISODE: This episode is brought to you by Cyberlynx CyberLynx is a Bethesda managed IT and cybersecurity company. Local techs you know, not a call center. Month-to-month. 24/7 intrusion detection. We help growing companies with managed IT, help desk, backup and recovery, and a fractional CIO. Talk to us at https://cyberlynx.com/contact , info@cyberlynx.com , or 301-798-9170.

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  Episode #239

  Playing With Fire: Securing AI Without Shutting Off the Stove with Nakeea Neischer - Ep 239

  Sep 23, 202639 min

  Guest Introduction Nakeea Neischer is the Director of IT and CISO at RxVantage , a healthcare SaaS platform that serves as a bridge between medical providers and life science companies. With more than 10 years in security, Nakeea has built her approach around a philosophy she describes through baking, gathering the right ingredients of people, process, and tools, then figuring out how those pieces combine into something the whole business can actually use. She joins the show to talk candidly about blast radius risk with AI agents, why she believes the industry has quietly shifted from prevention to recovery as the true measure of a security program, and why she thinks fear, not the technology itself, is security's biggest obstacle right now. Here's a Glimpse of What You'll Learn Why Nakeea compares building a security program to being the chef who has to bake a cake everyone enjoys How Nakeea thinks about blast radius as her single biggest concern with deploying AI agents Why Nakeea uses fire as her central analogy for AI, dangerous, necessary, and not something you can simply avoid How third party vendor risk has quietly gotten worse as vendors move faster on AI than the organizations that use them Why Nakeea argues patching alone is already too late against machine speed zero day exploits Why Nakeea believes the industry has shifted from asking can we prevent a breach to asking how fast can we recover Nakeea's take on why security teams need to extend AI the same grace they've started giving breached organizations In This Episode Nakeea opens by describing the core tension every SaaS security leader faces, protecting an organization internally while also defending an entire platform full of client data, all while AI reshapes both sides of that equation at once. She leans on her baking analogy to explain why security can't be only about tools, arguing that leadership habits, employee behavior, and business priorities all have to be understood before any framework or technical control gets layered on top, and that a security leader's real job is producing an outcome the whole business can live with, not simply locking everything down. She's candid that this balance is uncomfortable by design, since being too secure creates the same kind of failure as being too loose. The conversation turns to where Nakeea sees the sharpest risk in AI adoption, and she keeps returning to a single word, blast radius. She argues that comfort is the real danger, the same way a homeowner who has never been robbed eventually forgets to lock the back door, and that once an AI agent has access inside a network, the questions that matter are how much segmentation exists and what is truly off limits to it. She uses fire as her governing metaphor throughout, arguing that AI is exactly like fire in a home: genuinely dangerous, capable of burning everything down, and yet not something any household actually gives up, because the answer is learning to use it correctly rather than refusing to use it at all. She connects this to the Hugging Face sandbox incident as a preview of the test-and-learn process the industry is now going through, and argues that fighting AI with AI, rather than trying to out-work it manually, is the only realistic path forward. She also floats a concrete use case, feeding an organization's SSPs and frameworks into an AI system with carefully scoped, read only access to audit compliance gaps far faster than a manual review, while cautioning that the right approach is feeding in pieces at a time rather than dumping a sensitive document in all at once. The back half of the episode gets pointed about how fast organizations actually need to move. Nakeea explains that third party vendor risk has quietly gotten worse, since a company that is behind on AI internally is still relying on vendors who are moving fast on AI regardless, and that bureaucratic approval timelines that once felt normal are now themselves a security liability given how quickly zero day exploits move. She argues patching can no longer be treated as sufficient on its own, and that organizations need AI actively watching their own networks for abnormal behavior in real time, catching an intrusion the moment it happens rather than waiting for a SOC analyst to notice hours later. Drawing a comparison to her own daughters navigating early adulthood after years of academic perfectionism, she argues mistakes are only failures when people stop trying to learn from them, a lesson she believes applies just as much to AI vendors as to young adults. She closes with a broader argument that the industry has shifted from asking whether a breach can be prevented to asking how well an organization recovers from one, and makes the case that AI, like human security teams, deserves the same grace to learn through mistakes the industry has already extended to breached organizations. This episode is brought to you by Cyberlynx CyberLynx is a Bethesda managed IT and cybersecurity company. Local techs you know, not a call center. Month-to-month. 24/7 intrusion detection. We help growing companies with managed IT, help desk, backup and recovery, and a fractional CIO. Talk to us at https://cyberlynx.com/contact , info@cyberlynx.com , or 301-798-9170.

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  Episode #238

  Build Versus Buy: The Risk of Vibe Coding Your Security Stack with Andrew Dutton - Ep 238

  Sep 16, 202652 min

  Guest Introduction Andrew Dutton is the Regional Cybersecurity Architect for Sumitomo Chemical America , part of a global chemical manufacturing organization with roots stretching back more than 400 years, from copper mining in Japan to fertilizer production to the diversified chemical business that exists today. The company employs roughly 30,000 people worldwide, and Andrew's region also serves as its global center of excellence for cybersecurity. Andrew, himself an Army veteran, brings both a technical architect's precision and genuine appreciation for how the company operates. He joins the show to lay out a vision he has spent years developing for an AI operations layer, a way to get plain language answers about an organization's entire security posture instead of digging through disconnected tools, and to talk candidly about where the industry is already there and where real risk remains. Here's a Glimpse of What You'll Learn How Andrew's AI operations layer concept would let a CEO get a real, honest answer to are we secure Why Andrew says showing someone a raw count of 100,000 vulnerabilities is worse than useless How a real threat actor actively targeting chemical manufacturers shows proactive AI defense in practice Why Andrew calls traditional email gateways obsolete compared to modern AI powered alternatives The build versus buy risk Andrew sees in constructing an AI security stack without the right expertise Why Andrew believes the real barrier to good decisions is a decline in critical thinking, not the technology Andrew's take on how AI could reshape careers and the outdated idea of job security tied to one employer In This Episode Andrew opens by describing a concept he has developed for years, an AI operations layer sitting on top of every tool in the security stack with read only access, connecting inventory systems, EDR platforms, and CMDBs that often disagree with each other into one place a security leader can question in plain language. He walks through a concrete example: asking which servers aren't running EDR sounds simple, but reconciling an inventory system against an EDR platform against a CMDB that all define server ownership differently is exactly the tedious work an AI layer should absorb. He argues this layer should prioritize problems, telling a team the specific top ten things to fix rather than dumping a raw vulnerability count with no actionable meaning. From there he describes a proactive use case: asking which threat actor is currently targeting chemical manufacturers most aggressively, learning the specific technique that group uses, checking whether current defenses actually stop it, and kicking off a purple team exercise to verify the answer rather than trusting the tool's word for it. The conversation moves into how mature this vision already is, and Andrew is blunt that machine learning built directly into security products, tools like Darktrace and ThreatLocker that catch abnormal behavior or block unauthorized actions outright regardless of how an attacker got in, is no longer the future but table stakes today. He connects this to the MGM breach, arguing behavioral AI would have flagged a brand new admin account performing wildly unusual actions long before a human analyst noticed, and he is equally direct that traditional email gateways are obsolete, pointing to how Proofpoint acquired specialized players like Tessian to bolt AI powered behavioral analysis onto legacy filtering that can no longer keep pace with attacks arriving through legitimate services like DocuSign. He is also candid about the real risk of building these systems in house without the right expertise, describing how easy it is to vibe code an impressive prototype without understanding what it is doing underneath, burning through token costs on the wrong model, and comparing the temptation to the early rush to the cloud that left organizations with runaway bills. The back half broadens into how AI reshapes work and opportunity. Andrew argues the biggest barrier isn't the technology but a decline in critical thinking, and that organizations need people who can analyze a problem within its full business context rather than accepting whatever an AI tool outputs at face value. He shares a grounded perspective on job security as something that no longer comes from loyalty to one employer, describing his volunteer work helping high school students in rural Tennessee see paths beyond the local plant, and arguing that financial stability and a strong personal skill set matter more than tenure. He closes on an optimistic note about where AI could take society, from reducing domestic violence through in-home monitoring to enabling small, highly leveraged companies built by a handful of people, while acknowledging some of the hardest human problems are unlikely to be solved by technology alone. This episode is brought to you by Cyberlynx CyberLynx is a Bethesda managed IT and cybersecurity company. Local techs you know, not a call center. Month-to-month. 24/7 intrusion detection. We help growing companies with managed IT, help desk, backup and recovery, and a fractional CIO. Talk to us at https://cyberlynx.com/contact , info@cyberlynx.com , or 301-798-9170.

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