As Black Hat USA 2026 approaches, the cybersecurity industry finds itself grappling with a threat landscape reshaped by autonomous, machine-speed attacks — and vendors are racing to prove their AI claims are more than marketing gloss. Ahead of the show, VMblog caught up with Lisa Liu, corporate marketing and communications manager at Stellar Cyber, to get an inside look at what the company is bringing to the Las Vegas show floor. Stellar Cyber positions itself as the only AI-native SecOps platform purpose-built for MSSPs and lean enterprise security teams, with a mission centered on cutting false positives, easing analyst workload, and helping security operations keep pace with a threat environment increasingly defined by autonomous agents.
In this exclusive interview, Liu walks through what attendees can expect at Booth #5542, including hands-on demos of the company’s 6.5 and 6.6 platform releases, which bring expanded detection coverage and a new self-service Parser Studio. She also shares hard numbers behind Stellar Cyber’s Agentic Auto Triage capability — including time-savings metrics and a human-AI agreement rate the company says sets it apart from competitors making similar claims. From identity-based threats to supply chain blind spots to the risks of deploying AI without human oversight, Liu offers a candid look at where she believes the industry is getting it wrong, and how Stellar Cyber’s Multi-Layer AI™ approach aims to get it right.
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VMblog: For readers who may not be familiar, give us the elevator pitch — who you are, what you do, and what genuinely sets you apart in today’s crowded cybersecurity market.
Lisa Liu: Stellar Cyber is the only AI-native SecOps platform purpose-built for MSSPs and lean enterprise security teams. By reducing false positives, improving analyst productivity, and lowering operational costs, Stellar Cyber delivers more streamlined, efficient, and holistic security services to combat a contemporary threat landscape full of autonomous agents. Using machine speed response, Stellar Cyber’s solution allows our customers to filter out the noise and address the alerts that could actually escalate to incidents without overloading security analysts already confronting alert fatigue.
VMblog: Black Hat attendees are a discerning crowd. What booth experiences, live demos, or hands-on activities are you bringing to Las Vegas that will cut through the noise and leave visitors with something they can’t stop thinking about?
Liu: We’re excited to bring you demos of our product 6.5 and 6.6 launches. These updates to our platform feature improvements to our Agentic Auto Triage and extended detection coverage across identity, cloud, network, and application-driven threats, improved the platform’s operations, and introduced Parser Studio to create a self-service workspace for creating, testing, and activating custom parsers.
VMblog: What’s your Black Hat origin story? Longtime exhibitor or fresh face on the floor? What keeps your company coming back — or what made 2026 the year to finally plant your flag here?
Liu: We’re Black Hat veterans! It’s a great opportunity not only to connect with industry leaders, but also to demonstrate that we hear the pain points that have plagued the industry, that have been exacerbated by AI, and that our customer base is demanding a solution for. And we’re excited to show all the ways in which our product development over the years has been designed to address those pain points.
VMblog: If a CISO walks away from your booth remembering exactly one thing about your company, what do you want that to be?
Liu: Stellar Cyber is the only vendor on the floor with the metrics to back up our claims about Agentic Auto Triage. We’re able to report that our platform returns 19 minutes per hour per analyst, which ultimately yields 1.5 full-time analysts recovered. And with a 99.7% Human-AI agreement rate, that means that our thesis of human oversight combined with AI-driven capabilities does in fact work, and that we’re able to make you more efficient in your threat response without compromising the accuracy of your response.
VMblog: The threat landscape heading into Black Hat 2026 looks very different from even 18 months ago. Which specific threat vectors — whether that’s agentic AI attacks, identity-based intrusions, critical infrastructure targeting, or something else — is your solution most directly built to address?
Liu: Our solution is most directly built to address autonomous attacks; the way the landscape has changed means that threat volume is increasing exponentially, and will only continue to do so. Our focus is on delivering responses that also operate at machine speed, so that the human analyst can always stay on top of threats before they escalate. At the same time, our solution positions the human analyst in the most strategic position possible, so instead of combating noise, they’re going where they’re needed.
VMblog: Agentic AI is reshaping both offense and defense. How is your company building security for — and with — autonomous AI systems, and what risks are you most concerned enterprises are underestimating right now?
Liu: We’ve integrated AI into every layer of our security stack, and our vision has always been to deliver the most efficient type of AI for each step of the process, from threat detection all the way to response. Different steps, from data normalization, to Auto Triage, demand different types of AI to address the challenges, and the noise around AI means that a lot of enterprises are pouncing on AI to act unsupervised. That’s a quick way for small scale threats to escalate quickly, and for AI to become a liability, rather than an asset. Our Multi-Layer AI™ customizes the AI-Driven solution for each step of the process, from threat detection to response, to ensure that you always have the right tool for the problem, while your analysts have full visibility throughout.
VMblog: “AI-native security” is quickly becoming the new “next-gen.” What does that phrase actually mean at your company, and how do you demonstrate real differentiation beyond the marketing language?
Liu: We’re AI-Native in a way that very few other companies are. What that means is that we’ve had AI at the core of our vision since we were founded over 10 years ago. Because we recognize that every security problem demands its own type of solution, we’re not just using AI for AI’s sake. AI-Native means putting the problem first, before finding an AI solution, instead of wielding AI unsupervised in any capacity possible.
VMblog: Are you unveiling any major product announcements, partnerships, or research findings at Black Hat 2026? Can you tease it or give us a preview?
Liu: We’re excited to be giving demos of our latest product releases, 6.5 and 6.6 this year at Black Hat 2026!
VMblog: Identity has become the new perimeter — and attackers know it. How has your approach to identity security, authentication, or access management evolved, and what are organizations still getting dangerously wrong?
Liu: We’ve always understood and recognized the value of effective identity threat detection and response. ITDR remains a core part of our platform capabilities. Organizations believe that securing just the network means they’ve protected themselves against all identity-based attacks, when that failure to shore up ITDR will in fact become a huge vulnerability.
VMblog: What’s the most significant cybersecurity blind spot you’re seeing across your customer base right now, and how does your technology address it?
Liu: The paradox of cybersecurity blindspots is that the more tools you accrue in your portfolio, the more blind spots you’re likely to open yourself up to. Tool overlap creates inefficiencies in analyst workflow that actually can hinder your response capabilities in a really crucial way. Our theory has always been tool consolidation; to streamline all your existing workflows to work cohesively together, instead of against each other. In cybersecurity, more isn’t always better.
VMblog: Security teams are being asked to do more with tighter budgets and leaner headcounts. How does your solution help security leaders justify ROI and actually reduce operational burden rather than add to it?
Liu: Our goal is to level up your analysts, to make them more efficient and accurate than ever, while reducing their alert fatigue. By giving them tools that filter out a lot of the noise that makes their job difficult, we’re enabling them to act hundreds of times more efficiently, while making sure that they remain in the driver’s seat to oversee their AI-Driven tools. We’re not just building another tool for the analyst. We’re creating an ecosystem where the analyst and their tools are mutually empowering each other to act better, faster, and more precisely.
VMblog: The conversation around software supply chain security has matured significantly — but has enterprise practice kept pace? What’s the current state, and where are the gaps that still keep you up at night?
Liu: Supply chain security has always been overlooked. As IT/OT environments merge, the vulnerabilities traditionally found in OT environments become huge gaps for the enterprise. Full-visibility and response flexibility become paramount. We’ve learned that being proactive means not only being aware of threats, but also being aware of your own vulnerabilities, and how those are evolving as well.
VMblog: Beyond the product pitch, what’s one piece of hard-won, actionable security wisdom you’d hand to every practitioner who stops by your booth?
Liu: We’ve been able to deliver an 83% reduction in false positives. We’re able to return a day a week per analyst. Don’t blindly trust the AI promises you’ll hear all over the floor. Our technology is meant to work in concert with your security team, not against them. Don’t believe us? Come by Booth #5542 and see for yourself!
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