Balbix

I’m thrilled to share that Balbix has been recognized as a Visionary in the 2025 Gartner® Magic Quadrant™ for Exposure Assessment Platforms. Security leaders everywhere are feeling the frustration — endless vulnerabilities, constant noise from threat intel, and mounting pressure from boards and regulators to demonstrate real risk reduction. This recognition reflects Balbix’s differentiated approach to: - Business-aligned exposure assessment and risk quantification built on our Cyber Risk Graph - AI-native exposure discovery and prioritization to cut through the noise - Executive-ready insights that tie exposures directly to business impact - Full slew of exposure mobilization capabilities Our mission is simple, to help organizations move from raw vulnerabilities to prioritized action, measurable risk reduction and increased cyber resilience. Being named a Visionary reinforces what our customers already know: 10× better attack surface visibility, 90% less remediation/mitigation workload, and 95% faster remediation. We’re helping security teams focus on what truly matters! Kudos to the incredible Balbix team for pushing boundaries, innovating every day with our domain-specfic AI models, and delivering real results for our customers. 📘 Gartner subscribers can read the full Magic Quadrant report here: https://lnkd.in/gp8zN2JA #GartnerMQ #CyberRisk #CTEM #ExposureManagement #AI #Balbix

Proud to be named a Visionary in the inaugural Gartner® Magic Quadrant™ for Exposure Assessment Platforms. For teams ready to sharpen their focus, boost resilience, and advance their CTEM journey, this report offers valuable insights. 👉 Download the full report: https://lnkd.in/ggphN3GV #ExposureManagement #CTEM #CRQ #AI #GartnerMQ

I could not be more proud of our team here at Balbix! It is a privilege to share that Balbix has been named a Visionary in the 2025 Gartner® Magic Quadrant™ for Exposure Assessment Platforms, the first report defining this category. From the beginning, our goal has been to treat cyber exposure as an engineering and data problem rather than a checklist exercise. We built Balbix on the Cyber Risk Graph to unify telemetry, context, and business data at scale, enabling every asset, control, and vulnerability to be analyzed in real time and in the context of what it means to the business. The strength of our platform lies in its architecture. A highly optimized graph data layer, large-scale correlation engines, and explainable models work together to transform billions of telemetry points into insights that drive measurable outcomes. What differentiates Balbix is not just the analytics and workflows, but the system design that makes this speed and precision possible. This recognition reflects the work of an extraordinary team. Engineers who obsess over scalability and correctness. Product and design teams who turn complexity into clarity. The AI team that ensures every model and inference remains transparent and grounded in reality. And customer-facing teams who continuously translate feedback into meaningful enhancements. To our customers and partners, thank you for your trust and collaboration. This milestone validates our approach and reinforces our commitment to building the most reliable and transparent platform for understanding and reducing cyber exposure. Gartner subscribers can read the full report here: https://lnkd.in/gp8zN2JA #ctem #gartnermq #balbix #eap #exposure #vulnerabilitymanagement

Fireside Chat: From Risk to Remediation — A CISO’s Playbook for Measurable Impact CISOs today are under the microscope — juggling rising vulnerabilities, shrinking budgets, and constant board pressure to prove ROI. Join Baidyanath Kumar, CISO at JK Lakshmi Cement Ltd., and Gaurav Banga, Founder & CEO of Balbix, for a no-fluff conversation on how to turn exposure chaos into measurable outcomes. 📅 Monday, Nov 10 | 8 AM PT / 9:30 PM IST 💬 Expect real stories and pragmatic takeaways on: Moving beyond vulnerability counts to risk-based prioritization Quantifying cyber risk in a language the board actually understands Accelerating remediation without adding complexity 👉 Save your seat: https://lnkd.in/gXGQNBpB #CyberSecurity #CISO #RiskManagement #CTEM #CRQ #Balbix #CyberResilience

Richard Seiersen recently shared a diagram comparing the attack surface and risk surface — it’s a great spark for a deeper conversation. The diagram in question has the risk surface portrayed as larger than the attack surface. That framing has always struck me as backwards. The attack surface is everything that can be attacked or defended — your assets, apps, users, and third-party vendors, along with their exposures (vulns, misconfigs, EOLs, risky behaviors) and the controls that protect them. The risk surface lives inside that universe. It’s the subset where exposures, active threats, and business impact combine to exceed the organization’s risk appetite. Exposures, threats and controls shape the attack surface. Historical loss data, relevant scenarios, and risk transfer shape the risk surface. Where Richard's framing really breaks down is in the math: It models risk as a simple chain — asset → vuln → control → threat → loss — with no incorporation of appsec, user risk, 3rd parties, scenarios, historical loss data, or the quantitative foundations of SLE, ALE, and VaR. That’s how you end up with risk “scores” that feel scientific but don’t reflect real-world loss potential. Without these inputs, the model can’t tell you what’s material, can’t estimate likelihood, and can’t tie security outcomes to dollars. The attached picture has both models. - Top: the diagram shared by Richard Seiersen. - Bottom: the risk model we use at Balbix — where risk is derived from the attack surface, calibrated continuously using exposures, controls, scenarios, and empirical loss data to produce quantifiable, defensible results. The probabilistic complexities are addressed by 100+ domain specific AI models. Richard — appreciate you starting this conversation. I’d love to hear how others view this: Can a model that omits historical loss data and scenario analysis ever produce accurate, board-ready risk numbers? #cyberrisk #riskmanagement #attackSurface #riskSurface #riskappetite #riskquantification #exposuremanagement #cyberresilience #balbix #CISO

Most of you use ChatGPT or Claude daily, and you’ve probably noticed (or should have noticed) the constant little struggles, confident answers that are just… wrong. Hallucinated facts. Misremembered numbers. Smooth language masking shaky grounding. And yet, the hype train keeps rolling: “Agentic AI will solve everything!” Agents that reason, plan, and act autonomously — as if a few more layers of reasoning will somehow erase hallucination. In cybersecurity, that’s not just optimistic — it’s dangerous. - A “slightly wrong” AI answer in chat could be harmless, or not?. - A “slightly wrong” autonomous action in an enterprise network could mean a broken system, a compliance failure, or an actual breach. In my latest blog, I explore why “good enough” hallucination rates aren’t actually good enough, and why the real path forward isn’t more autonomy with bigger models, but more structure, grounding, and accountability in how we design AI systems. https://lnkd.in/gkKUxR9R I am very curious how others in AI or cyber are thinking about this. #AI #Cybersecurity #LLMs #ResponsibleAI Balbix #AgenticAI